Abstract Proceedings ICOSCM 2016 - RCOSCM | … · 2016-08-19 · Moderating the effects of Lean...

Abstract Proceedings

ICOSCM 2016

2 Page

Contents

Symbiosis International University (SIU) ....................................................................................................... 6

Symbiosis Institute of Operations Management (SIOM) .............................................................................. 6

Patron’s Message .......................................................................................................................................... 8

Convener’s Message ..................................................................................................................................... 9

Co‐Convener’s Message .............................................................................................................................. 10

Key Note Speakers ....................................................................................................................................... 11

Prof. S.G. Deshmukh......................................................................................................................... 11

Prof. Nyoman Pujawan .................................................................................................................... 11

Prof. S. Rangnekar ............................................................................................................................ 12

Prof. Padmanav Acharya .................................................................................................................. 12

Prof Jitesh J Thakkar ......................................................................................................................... 13

Prof. Kamapan Mukherjee ............................................................................................................... 13

Prof. Jaideep Motwani ..................................................................................................................... 14

Prof. Manoj Dash .............................................................................................................................. 14

Mr. Ashish Tanwar ............................................................................................................................ 15

Mrs. Ramya Mishra ........................................................................................................................... 15

Schedule: 11th Aug. 2016 (Day 1) ............................................................................................................... 16



Technical Sessions: Day 1 ............................................................................................................................ 19




List of Accepted Abstracts ........................................................................................................................... 23

1. Green Evolution in Hospitality Management.......................................................................................... 23

2. Deciding the Vendor Selection Criteria for Capital Procurement ........................................................... 24

3. Utilization of Big Data to Enhance Speed of Idea Generation ................................................................ 24

4. A framework for locating and equipping marine oil‐response facilities ................................................. 25

5. An analytical approach to rail‐truck intermodal transportation of hazardous materials with

capacity selection & terminal congestion ................................................................................................... 28

6. Idea for a Lean‐Agile supply chain for the Armed Forces. ...................................................................... 30

7. Synchronizing Electrical Energy Generation and Distribution Supply Chains ......................................... 31

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8. Greener Supply Chains towards Environmental Protection in Food Processing Industries ................... 31

9. A review on the experimental usage of classical, Shanin and Taguchi design of experiment (DOE)

with Data Mining approach using six sigma DMAIC. .................................................................................. 32

10. Performance Measurement of supply chain: a changing paradigm ..................................................... 34

11. Optimal replenishment policy and preservation technology investment for a non‐instantaneous

deteriorating item with stock‐dependent demand .................................................................................... 38

12. Role of HR in Lean Manufacturing Implementation – a Comprehensive Study ................................... 40

13. Coordinating a Three‐echelon Supply Chain with Uncertain Demand and Random Yield ................... 41

14. Investigations on Raw Material Supplier Selection Methodology Using Fuzzy Logic ........................... 43

15. A Hybrid Model Based On SWARA And WASPAS MCDM Methods For Supplier Selection. ................. 43

16. Routing Alternative Fuel‐powered Vehicles for Garbage Collection .................................................... 43

17. Role of Big Data in Decision Making ..................................................................................................... 44

18. Service Quality in Selected Hospitals in Indore City: An Empirical Study ............................................. 44

19. Reverse logistics network design and re manufacturing using new module supplier.......................... 45

20. A taboo search heuristic with discrete‐event simulation for scheduling staff in call centers .............. 46

21. ISM Based modeling of supply chain management enablers ............................................................... 48

22. Price and credit period sensitive competitive supply chain model ...................................................... 50

23. Ergonomics Enhancing Agricultural Systems Productivity .................................................................... 51

24. Application of TQM in Resolving E‐Commerce Challenges in Rural Markets ....................................... 51

25. Mobile Computing, Cloud & Internet of Things in SCM ........................................................................ 52

26. An Examination of Supply Chain Performance Factors based on the Quality of Relationships ........... 55

27. Moderating the effects of Lean manufacturing: A contextual framework with respect to process

industry ....................................................................................................................................................... 59

28. Logistics Management: Opportunities and Challenges with Reference to Selected Organizations ..... 59

29. Does magnitude of penalties matter? An empirical investigation in the healthcare context .............. 60

30. Category Management: Enriching Customers private label purchase ................................................. 61

31. Assessing Risk by the High Net worth Investors of India in Financial Decision .................................... 62

32. Application of Behavioral Finance and econometrics to understand the High Net worth

Individuals investors during Uncertainties and Risk in India ...................................................................... 63

33. Application of Optimizing Techniques in Indian Auto Ancillary Industries for SCM. ............................ 64

34. Building the foundation for Supply Chain Costing by identifying and prioritizing the elements

involved using TOPSIS. ................................................................................................................................ 65

35. Military Aircraft LRUs with MRO Supply chain improvement: Self Reliance in Aircraft MRO

business and Sustainability for future ........................................................................................................ 68

36. Redesign of Supply Chain Network of Footwear Manufacturing Company and impact of GST using

Sensitivity Analysis tool ............................................................................................................................... 69

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37. Energy efficient reconfigurable architecture for motion estimation in video coding .......................... 72

38. Lot‐Sizing for Forecasted Demand at Metal Finishing Industry ............................................................ 72

39. Vendor Rating & Inventory Management in an Indian Start‐up: A combined AHP‐TOPSIS

approach ..................................................................................................................................................... 75

40. Demand forecasting, Economic Order Quantity and Reorder point calculation of a hypothetical

company producing solar panels ................................................................................................................ 78

41. Research on Procurement Management of MSE using system dynamics methodology ..................... 80

42. Approaches for combining operational decisions for maintenance and quality control: A review ..... 82

43. Multicommodity Network Design under Congestion ........................................................................... 84

44. Stepping on the Scale: SOLAS’ Container Weight Amendment ............................................................ 84

45. Benefits & Scope of GPS in Logistics and in Different Works of Life .................................................... 85

46. Interdependence among dimensions of Sustainable Supply Chain: evidence from Indian leather

industry ....................................................................................................................................................... 87

47. Integrating SME’s of Indian Switchgear and Transformer Industry using Lean Supply Chain

Management Practices ............................................................................................................................... 89

48. Supplier Selection Using Combined SWARA and WASPAS – A Case study of Indian Cement

Industry ....................................................................................................................................................... 90

49. Extending Green Practices in Supply Chain Management .................................................................... 90

50. Lean Production Supply Chain Management as Driver towards Enhancing Product Quality and

Business Performance ................................................................................................................................. 91

51. Lean Supply Chain in Manufacturing Unit using Value Stream Mapping. ............................................ 92

52. Supply chain performance measurement framework for small and medium scale enterprises ......... 92

53. Lean assessment parameters and roadblocks in implementation of Lean Management in Indian

Auto component Industry: A combined AHP & MICMAC approach ........................................................... 94

54. Benefits, Challenges and Bridges to Effective Supply Chain Management. ......................................... 95

55. Prioritization of Antecedents for the Adoption and Execution of Supply Chain Management using

TOPSIS ......................................................................................................................................................... 96

56. Digital Retail: A Sustainable Opportunity ............................................................................................. 96

57. A Comparative Study on Automation Feasibility across Two Tools and Report Benefit Assessment .. 97

58. New product development through quality function deployment ...................................................... 99

59. Interpretive Structural Modeling of Supply Chain Risks in a Manufacturing Firm ............................. 100

60. Evaluation of Supplier(s) for an Automobile Firm. ............................................................................. 101

61. A case on Business Process management........................................................................................... 102

62. Overall Equipment Effectiveness (OEE) to increase productivity of work centre. ............................. 103

63. Risk Analysis in Global Supply Chain Management: Application of AHP and DEMATEL .................... 105

64. Process development using ISM in Ecommerce business. ................................................................. 106

5 Page

65. Identification and evaluation of parameters affecting ERP System Implementation in a

manufacturing firm ................................................................................................................................... 106

66. Interpretive Structural modelling of Supply Chain Risk Management ............................................... 107

67. Kumbh Mela: Nasik City Logistics study of the state shuttle‐bus transportation system using

simulation approach ................................................................................................................................. 108

68. Customer Roll out ‐ Operationalization of Customer Contract .......................................................... 110

69. Supply Chain Management: Asset Control and its impact on the value of firm ................................. 110

70. Sector analysis‐An automotive supply chain model for demand driven environment ...................... 111

71. Performance Issues in Supply Chain Management Using SAP‐LAP Framework: A Case Study

Evidence from Manufacturing Industry .................................................................................................... 113

72. Strategic Alignment of future supply chain with existing supply chain of LNG distributing

organization in India ................................................................................................................................. 114

73. Transporter selection using AHP analysis & Central warehouse Planning ......................................... 115

74. Strategic Initiative for Supply Chain Management in Different Sectors. ............................................ 116

75. Extending Green Practices across supply chain: an empirical study .................................................. 117

76. Performance Measurement of supply chain: A Balance Score Card (BSC) approach ......................... 121

77. Modeling Supply Chain Network Design and Product Recovery Planning Under Demand

Uncertainty ............................................................................................................................................... 122

78. A Comparative Study between AHP and TOPSIS to Prioritize Supply Chain Flexibility Dimensions:

A Case Study of Indian FMCG Sector ........................................................................................................ 125

79. A combined AHP‐ANP approach to evaluate supply chain of electronic business ............................. 126

80. Identifying dimensions of Student Support Systems in eLearning courses and their causal

relationship using AHP and DEMATEL ...................................................................................................... 126

81. The Role of Information Uncertainty on Cement Industry‐ (Using Combined AHP‐DEMATEL

Analysis) .................................................................................................................................................... 128

Authors’ Index ........................................................................................................................................... 132

Leadership ................................................................................................................................................. 144

Organizing Team ....................................................................................................................................... 144

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Symbiosis International University (SIU)

Padma Bhushan, Dr. S.B Mujumdar established Symbiosis on the principles of Vedic thought of “World as One Family” and is resplendent of the activities and students of several countries. With changes sweeping across India's higher education environment, SIU has established need based institutes across the 7 faculties of Law, Management, Computer studies, Health & Bio‐medical Sciences, Media, Communication & Design, Humanities & Social Sciences and Engineering. Symbiosis International University continues to grow, evolving by benchmarking itself against the best in the world. The University also has MOU'S of collaboration with several renowned universities of the world and encourages students & faculty to participate in its programmes. The University is re‐accredited by NAAC with Grade 'A'. Symbiosis International University has 28 academic institutions spread over ten locations in Pune, Noida, Bangalore, Hyderabad and Nashik.

Research at SIU

Symbiosis International University offers a Ph.D. programme under the guidelines prescribed by the University Grants Commission (2009). The programme is offered in the 7 faculties of Law, Management, Computer Studies, Health & Biomedical Sciences, Media, Communication & Design, Humanities & Social Sciences and Engineering. Main focus:

Development of institutional research agenda and formulation of policy to reflect a

conscious effort for creating a congenial climate to nurture a research culture in the University.

Setting up a systematic procedure for administration of research programmes.

Research capacity building and mentoring to translate our efforts into high quality

research outcome.

Symbiosis Institute of Operations Management (SIOM)

Symbiosis Institute of Operations Management (SIOM) is born out of the conviction that ENGINEERS, if forged and chiseled in an exclusive B ‐School environment can be outstanding ''Techno ‐Business'' leaders. SIOM is India's only Institute dedicated to Operations Management, constituted with a vision of Empowering and Leading Operations Excellence. The curriculum includes SAP ERP training, Six Sigma Certification by KPMG, and facilitates CPIM, CSCP Certification. SIOM has been awarded the title of ''Institute with Best Industry Related Curriculum in Operations Management'' by the Dewang Mehta B ‐School Awards (2009), Dainik Bhaskar B ‐School Awards (2010) & Star News B –School Awards (2011), ABP news National School awards (2012), ET Now Awards (2013). SIOM bagged 3 prestigious awards at the 2nd Asia's Best Emerging B School Awards held in Singapore, viz., B School with Best Industry interface. Recently it is also the recipient of ''Education Excellence award at the 2nd CPO forum for its best education in SCM.

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Over the years the thirst to achieve operational excellence has led Symbiosis Institute of Operations Management to set newer benchmark every year for propelling the pedagogy provided in this institution. In its ambitious mission to create techno business leaders, capable of excelling in the field of operations, the institution throws in a perfect milieu of good academic curriculum and industry interface for students to learn and grow as operations professionals. In that spirit, Symbiosis Institute of Operations Management is organizing the “International Conference on Operations and Supply Chain Management” which solely focuses on the broader aspect of operations and supply chain management. This conference aims to bring together management professionals from industry and academics, research scholars, students, business leaders and entrepreneurs. The main theme of this conference is “Contemporary Trends in Operations and Supply Chain Management”. The conference intends to initiate discussions and create a platform to share knowledge and current trends in the field of Supply Chain Management and related topics like Risk Management, Global Business Operations, and Procurement Management etc. Each is of great importance to the current and possible future trends in Operations and Supply Chain Management. In a span of just three days (11‐13th August, 2016) many research papers will be presented by people from across the globe, exploring potentials of this field in today’s world. It will be a great opportunity for everyone in broadening their horizon of knowledge by being a part of ICOSCM.

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Patron’s Message

Dr. Vandana Sonwaney

Director, Symbiosis Institute of Operations Management Patron, ICOSCM 16

SIOM has always proven itself in the field of operations. It has evolved over years achieving laurels and recognitions for attaining operational excellence. SIOM, with a vision to lead in the field of operations has laid a strong foothold in academics especially through perseverance, adherent commitment and dedication. A way forward in this scenario is ICOSCM‐ International conference on operations and supply chain management. This would serve a rostrum for students, research scholars, business leaders, management professional from industries and many academicians to share their views, ideas and insights on particular theme. The theme chosen for this discussion is “Contemporary research trends in operations and supply chain management”. There are other areas put forth for discussion such as lean, agile manufacturing, procurement management etc., that will provide a comprehensive analysis of operations world. This would not only enable paper presentations, but also act as an estuary wherein young, vibrant innovators meet distinguished, imminent leaders from academics and business world. More than just a conference, it is a catalyst for pure and efficient knowledge transfer. For such an initiative which will serve a greater significance in chiseling a sustainable future, I cordially invite all for being a vital link in this supply chain network. Looking forward to a greater participation.

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Convener’s Message

Dr. Rohit Singh

Convener and Organizing Secretary, ICOSCM 16

This is the first one of a new series of annual academic international conferences Organized by Symbiosis Institute of Operations Management exploring on the theme “Contemporary research trends in operations and supply chain management”. Over the years SIOM has proved its mettle in academia and research. It is one of the pioneers in the field of operations and is now emerging as a center for excellence in operations management. This conference is the next big step to its glory which would witness many academic and industry stalwarts sharing their views on the recent trends in operations and supply chain management on a single platform. As the business progresses towards a new revolution, focus on operations and supply chain management is essential as they form the major factors for an organization’s profit. Hence it is imperative that strong and innovative ideas are put forth to realize the true potential for sustainable operational environment. I assure that the three days will keep you busy and productive.

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Co‐Convener’s Message

Dr. Ratna Paluri

Co‐Convener, ICOSCM 16

Symbiosis Institute of Operations Management (SIOM) has been contributing extensively to research in Operations Management. With increasing emphasis on sustainable operations, agility, digitalization and innovation, the field of operations and supply chain management is becoming more challenging and competitive. Against this backdrop the three‐day International Conference on Operations and Supply Chain Management at SIOM, is a confluence of the best of the brains from across the globe throwing light on the various aspects of Operations and SCM. Given the core theme of the conference being “Contemporary research trends in operations and supply chain management”, the conference provides a platform for knowledge sharing, deliberating and networking, thereby offering a lot on the platter for the participants.

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Key Note Speakers

Prof. S.G. Deshmukh DIRECTOR, IIIT GWALIOR

Prof. S. G. Deshmukh is currently associated as the director of IIIT, Gwalior. Post

obtaining his B.Tech and M.Tech degrees from I.I.T., Bombay in the years 1982 and

1984, he completed his Ph.D from the same institute in 1990. He has received

certificate of Appreciation as Proctor by American Society for Quality (2001).

Prof. Nyoman Pujawan ITS INDONESIA

Prof. Nyoman Pujawan is a renowned personality in Supply Chain Engineering and the

Head of Graduate Program at the Department of Industrial Engineering, Sepuluh

Nopember Institute of Technology (ITS), and Surabaya, Indonesia. He received a

bachelor degree in Industrial Engineering from ITS, Indonesia, Master of Engineering

in Industrial Engineering from Asian Institute of Technology (AIT) Bangkok, Thailand,

and PhD in Management Science from Lancaster University, UK. He is the CSCP

(Certified Supply Chain Professional) holder from APICS (USA).

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Prof. S. Rangnekar IIT ROORKEE

Prof. Santosh Rangnekar is associated with Indian Institute of Technology, Roorkee.

Dr.Santosh Rangnekar studied at Indore and obtained Ph.D., M.B.A. (H.R.M.) from

Devi Ahilya Viswavidyalay, Indore. He has also studied LL.B. (Hons) from Indore and

Post – Graduate Diploma in Personnel Management and Industrial Relations from

Vikram University of Ujjain.

Prof. Padmanav Acharya NITIE MUMBAI

Prof. Padmanav Acharya is currently working at NITIE Mumbai. A Bachelor of

Engineering (Hon’s) in Mechanical, he has done his M.Tech and Ph.D in the area of

Industrial Engineering from I.I.T. Kharagpur. He continues his pursuit of research at

the highest level in aforementioned areas of interest in collaboration with other

institutes and industry.

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Prof Jitesh J Thakkar IIT KHARAGPUR

Prof. Jitesh Thakkar is associated with the department of Industrial and Systems

Engineering in IIT Kharagpur. He has done his Ph.D. from IIT Delhi. He is a member of

Indian Institute of Industrial Engineering, The Institution of Engineers (India),

Operational Research Society of India and POMS, USA.

Prof. Kamapan Mukherjee DEAN, IIM KASHIPUR

As an established management educator with rich experience of teaching (21 years

as Professor) Dr Kampan Mukherjee established the Department of Management

Studies and became University Dean (Academic) at Indian School of Mines. He has

joined IIM Kashipur as a Professor in August 2014. He earned PhD from Moscow

Institute of Economics and Statistics as government sponsored research scholar in

1988 and subsequently was associated with LAMSADE, University Paris Dauphine as

Senior Visiting Fellow of Government of France in 1998. Prof Mukherjee pioneered

research activities in India on management of Remanufacturing/ Reverse Logistics.

He was conferred Life Time Achievement award in Operations Management by

Society of Operations Management in 2012.

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Prof. Jaideep Motwani SEIDMAN COLLEGE OF BUSINESS, USA

Prof. Jaideep Motwani currently acting as the chair and Professor of Management,

Seidman college of business is an award winning and highly accomplished scholar,

administrator, and consultant with 25 years of experience in the field of supply chain

management and process improvement. He has published 17 books and more than

225 articles in prestigious journals such as Operations Research, European Journal of

Operations Research, IEEE Transactions of Engineering Management etc., Dr.

Motwani was ranked among the Top 1% Researcher in the field of Technology

Management and the recipient of the Michigan Outstanding Educator’s Award

granted by the Governor of Michigan. He works with professionals in the area of

lean, customer services excellence, supply chain management, performance

measurement, leadership, teambuilding, and service operations. He also serves on

the advisory board of a dozen international journals.

Prof. Manoj Dash IIIT GWALIOR

Professor Manoj Dash is currently associated with IIIT Gwalior. Manoj Kumar Dash

has earned his M.A. with specialization in Econometrics, M.Phil. with specialization in

Econometrics, Ph.D. in Economics on topic ‘Econometrics of Complete Demand

System’ and M.B.A. in Marketing from Berhampur University, Berhampur (Orissa). He

has published more than 67 research paper in various journals of International and

National repute.

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Mr. Ashish Tanwar UNIVERSITY RELATIONS COUNTRY MANAGER – DELL INDIA

Mr. Ashish Tanwar is a HR professional with 8 years of experience. Having completed

his post‐graduation in Xavier Institute of Social Service, Ranchi he has worked as a HR

professional in TCS for 6 years. He is a strong analytical person who is an expert in

relation building. He is currently employed in Dell as University Relations Country

Manager – India and is responsible for heading University hiring & relations for all of

Dell’s businesses in India. He has been awarded the dell championship award for

2015.His areas of expertise include campus recruitment / relations, employer

branding, lateral recruitment, strategic planning, orientation, grievance handling,

r&r, employee engagement, retention and high potential development. He is Dell

brand certified and Social media & community professional of dell. He is also a

certified advanced internet recruiter from OS2i.

Mrs. Ramya Mishra Director, PR365, New Delhi

Ramya Mishra carries over 14 years of experience in Brand and Product

Development. She is today's leading communication expert especially in the field of

hospitality. In her work experience, she has served both agency and client. She has

designed communication strategy for corporate and human brands at National and

International level. Due to her crucial strategic input many brands gained immense

popularity. She is an expert in Content Development, Media Management, Crisis

Management, Digital PR, Internal Communication and External Communication. Few

of the clients who have benefited from her experience are Marico, Raddison, Hyatt,

Claridges, Park Plaza, Godrej etc.

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Schedule: 11th Aug. 2016 (Day 1)

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Technical Sessions: Day 1

Day1 Time Theme/Papers Author (s) / PresentorA Hybrid model based on SWARA and WASPAS MCDM methods for

supplier selection.

Naveen Jain, Amitraj Singh and Akhilesh

Kumar Choudhary.

Performance Measurement of supply chain: A Balance Score Card (BSC) PRS Sagar, Ankur Shukla, Rohit Kumar.

Multicommodity Network Design under CongestionNavneet Vidyarthi, Sachin Jayaswal and

Sagnik Das.

Building the foundation for Supply Chain Costing by identifying and

prioritizing the elements involved using TopsisShilpa Parkhi and Gary Cokins.

A combined AHP‐ANP approach to evaluate supply chain of electronic Abhishek Tuli, Ankit Karir.

Application of TQM in Resolving E‐Commerce Challenges in Rural Markets Vandana Sonwaney and Sunny Oswal.

Role of Big Data in Decision Making Sneha Kumari, Shirish Jeble and Yogesh

Supplier selection using combined SWARA and WASPAS Jitendra Vishnolia & Anand Singh.

Stepping on the Scale: SOLAS’ Container Weight Amendment Saroj Koul.

Evaluation of Supplier(s) for an Automobile FirmMoumita Saha, Vivek Alamadi, Aditya

Bapat and Sudhanshu Pandey.

Does magnitude of penalties matter? An empirical investigation in the

healthcare context

Gopalakrishnan Narayanamurthy and

Rachna Shah.

Role of HR in Lean Manufacturing Implementation – a Comprehensive Protik Basu and Pranab K Dan.

Moderating the effects of Lean manufacturing: A contextual framework

with respect to process industry

Anand Sasikumar and Dr. Padmanav

Acharya.

Integrating SME’s of Indian Switchgear and Transformer Industry using

Lean Supply Chain Management PracticesMrunalini Dodkey.

Lean Production Supply Chain Management as Driver towards Enhancing

Product Quality and Business Performance

Sunil Das,Arun Koonammave, Prasanjit

Biswal.

11:30 AM TO 1:15 PMSession 3

11:30 AM TO 1:15 PM

11:30 AM TO 1:15 PM

Session 1

Session 2

20 Page


Day1 Time Theme/Papers Author (s) / PresentorVendor Rating & Inventory Management in an Indian Start‐up: A

combined AHP‐TOPSIS approach

Nishant D. Singh, Dr Rohit Singh, Chetan

Saxena and Naman Singh.

Military Aircraft LRUs with MRO Supply chain improvement: Self Reliance Krishana Kant Shukla, Ravindra Kumar

Kumbh Mela: Nasik City Logistics study of the state shuttle‐bus

transportation system using simulation approachJitendra Vishnolia and Prof.Rohit Singh.

Benefits & Scope Of GPS In Logistics In Different Works of Life Arijit Poddar.

Identification and evaluation of parameters affecting ERP System

Implementation in a manufacturing firm.

Priya Daware, Videtha Ghai, Mayank

Mehrotra, Saikat Chandra.

Green Evolution in Hospitality Industry Arshiya Mahajan.

Performance Measurement of supply chain: A changing paradigm Anil Sathe.

Transporter selection using AHP analysis & Central warehouse PlanningSaqibullah Choudhary, Rohit Kapoor, Viraj

Raut.

Deciding the Vendor Selection Criteria for Capital Procurement Dr. Anil Kumar and Dr. Manoj Kumar Dash.

Implementation of supply chain Management and its impact on the value Elvin Clements.

Demand forecasting, Economic Order Quantity and Reorder point

calculation of a hypothetical company producing solar panels

Rishabh Dua, Tanusha Sharma, Kartik

Gupta and Puneet Bhatia.

Extending Green Practices in Supply Chain Management Sonal Surabhi, Suman Sowrabh and Aditya Research on Procurement Management of MSE using system dynamics Shubham Kakde, Manas Agrawal and

Investigations on Raw Material Supplier Selection Methodology Using K KALIDAS and Dr.K.Sundararaj

An Examination of Supply Chain Performance Factors based on the Quality Rajeev Sharma and Gaurav Tripathi.

Digital Retail: A Sustainable OpportunityYashomandira Kharde, Prasad Madan,

Sonal Surabhi, Pravin Kharde.

Redesign of Supply Chain Network of Footwear Manufacturing Company

and impact of GST using Sensitivity Analysis toolShilpa Parkhi and Udgar Antani.

Session 5

Session 6 3:45 PM TO 5:45 PM

3:45 PM TO 5:45 PM

3:45 PM TO 5:45 PM

Session 4

21 Page


Day2 Time Theme/Papers Author (s) / PresentorIdea for a Lean‐Agile supply chain for the Armed Forces Pankaj Sharma and Makarand Kulkarni.

Routing Alternative Fuel‐powered Vehicles for Garbage Collection Yuvraj Gajpal, Shuai Zhang, Mohamed

Approaches for combining operational decisions for maintenance and

quality control: A reviewPravin Tambe and Makarand Kulkarni.

Application of Behaviourial Finance and econometrics to understand the

High Net worth Individuals investors during Uncertainties and Risk in IndiaShiba Parhi.

Application of AHP and DEMATEL in Production SystemsPradeep Kumar Jain, Prasang Jain, Tarun

Garg, Akshay Gupta.

Utilization of Big Data to Enhance Speed of Idea Generation Ridhima Arora, Dr. Anil Kumar and Dr.

Category Management: Enriching Customers private label purchase Vilas Nair and Dr Susan Abraham.

Customer Roll out ‐ Operationalization of Customer ContractAnil Choudhary, Himanshu Thakur, Kavin

M.

Application of Optimizing Techniques in Indian Auto Ancillary Industries Karan Venkatesh.

"Identifying dimensions of Student Support Systems in eLearning courses

and their causal relationship using AHP and DEMATEL"Prashant Barge

Lot‐Sizing for Forecasted Demand at Metal Finishing Industry Pranav Dange, Pranay Daharwal and Pravin

Ergonomics Enhancing Agricultural Systems Productivity Dr Ashok Matani .

Logistics Management: Opportunities and Challenges with Reference to

Selected OrganizationsDr.Parikshit Kala.

Interpretive Structural modelling of Supply Chain Risk ManagementNirmal Shah, Nikhil Mohite, Ashish

Nannaware, Vishesh Khandelwal.

A case on business process management. Shrikant Shinde.

Assessing Risk by the High Net worth Investors of India in Financial

Decision

Shiba Parhi, Dr Mohammad Khalid Azam

and Dr M Venkateshawrlu.

Session 3

10:45 AM TO 12:45 PM

10:45 AM TO 12:45 PM

Session 2

10:45 AM TO 12:45 PMSession 1

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Day2 Time Theme/Papers Author (s) / PresentorGreener Supply Chains Towards Environmental Protection in Food Dr Ashok Matani .

Synchronizing Electrical Energy Generation and Distribution Supply Chains Dr Ashok Matani.

A Comparative Study between AHP and TOPSIS to Prioritize Supply Chain

Flexibility Dimensions: A Case Study Of Indian FMCG Sector Shreyash Bansal, Nupur Prajapati .

New product development through quality function deployment. Preeti Shri Agrahari, Takshil Nagar.

Lean Supply Chain in Manufacturing Unit using Value Stream Mapping.Ashish Singh Yadav, Ashwini Awale and

Zoheb Meraj.

Lean assessment parameters and roadblocks in implementation of Lean

Management in Indian Auto component Industry: A combined AHP &

Akshay Kumar, Rohit Singh, Tanmay

Borulkar and Partha Paramanik

Supply chain performance measurement framework for small and Akansha Rammaiya.

Benefits, Challenges and Bridges to Effective Supply Chain Management Pooja Shah.

Overall Equipment Effectiveness (OEE) to increase productivity of work Shiladitya Adhikary , Arijit Roy, Bir Pratap Modeling Supply Chain Network Design and Product Recovery Planning Apoorv Jha, Sana Ibrahim, Sudarshan K, Performance Issues In Supply Chain Management Using SAP‐LAP Akshay Gathekar and Hemant Extending Green Practices across supply chain: an empirical study Ajay Kaushik.

Strategic Alignment of future supply chain with existing supply chain of Parth Gandhi, Mayukh Saha, Navaneeth Strategic Initiative for Supply Chain Management in Different Sectors Sanuj Das, Vishvas Luhana, Aditya Bhagwat. Sector analysis‐An automotive supply chain model for demand driven

environment

Subhro ghosh , Sandipan Show, Manish

Ghosh.

A Comparative Study on Automation Feasibility across Two Tools and

Report Benefit AssessmentAyona Chakraborty.

Session 4

01:45 PM TO 03:45 PM

10:45 AM TO 12:45 PM

01:45 PM TO 03:45 PMSession 5

Session 6

23 Page

List of Accepted Abstracts

1. Green Evolution in Hospitality Management

Arshiya Mahajan.

The Tourism Industry in its journey towards excellence has ignored the other very important

aspect of environment and ecology. However with emerging environment consciousness and

concern for posterity the importance of ecological balance has gained prominence. Tourism

today, is not just a simple holiday activity, it has evolved as a phenomena. It is clearly based on

environment. Negative impacts from tourism occur when the level of visitor use is greater than

the environment's ability to cope with this use within the acceptable limits of change.

Uncontrolled conventional tourism poses potential threats to many natural areas around the

world

The Author,( Arshiya Mahajan),has already presented her paper(ME‐MC‐18) in Fifteenth Global

Conference on Flexible Systems Management held at Symbiosis Institute of Technology, Pune

held on October 23‐25,2015 wherein the undersigned has attempted to identify and present

the various extrinsic &intrinsic factors that affect customers“ preference to visit green hotels in

Indian context that can be generalized in the context of the world. Now through this paper will

further analyze the various attributes affecting customers “preference to visit green hotels and

weighted average of each factor on the customers intention to visit a green hotel. In the study

we will discuss various attributes which are affected due to tourism and thus how the

customer’s choice of hotel selection is thus being affected. A green hotel is an environmental

friendly lodging property that institutes and follows ecologically sound programs/practices

(e.g., water and energy savings, reduction of solid waste, and cost saving) to help protect our

planet (GHA, 2008).As the number of customers heading towards green operations increase,

being a green hotel provides a good strategic position in terms of marketing, in this competitive

arena.

Hence, the main objectives of this study included the following:

1. Explore consumers’ perceptions of various attributes that affect a customer’s choice of the

hotel.

In the further future studies we will have a questionnaire survey and make empirical testing of

these factors. Theory proposed will be established in Indian context that is generalized to other

world context for green hotel.

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2. Deciding the Vendor Selection Criteria for Capital Procurement

Anil Kumar and Manoj Kumar Dash.

Vendor selection for capital procurement is increasingly essential and important for most of the

manufacturing units in all over the world. The need of the best selection is for survival of the

firms as world‐wide globalization and cost cutting concepts are emerged in the competitive

markets. It is helping the firms to produce the products at comparatively low cost .The selection

criterion involves various qualitative & quantitative factors on which basis best suitable supplier

to be selected and this selection basis are also have essentially to build long term relationship

with vendor in the form of tangible & intangible ground. Involving the experts’ guidance &

choice of the vendor section some scientific and analytical tool can be used to derive the

validity of the factors involving in selection criterion such as AHP (Analytical hierarchy Process)

and another technique available is DEMATEL (Decision Making Trial & Evaluation Laboratory).

By using these two selection models, we can found out the best vendor for capital procurement

through the vendor & buyer interactions for selection requirement & with the help of valid data

collection and matrix method. Process of vendor selection for capital procurement has the

multidimensional approach to get confirm information & history chart of the vendor’s

performance in the desired field.

3. Utilization of Big Data to Enhance Speed of Idea Generation Ridhima Arora, Anil Kumar and Shrawan Kumar Trivedi.

Erevelles et al., (2016) examined that analytics is at the epicenter of a Big Data revolution in

every domain of business. The study is an attempt to understand the utilization of big data to

enhance speed of idea generation with applications in different domains of business i.e.

marketing, operation management, finance, human recourse etc. To capture huge data and

plentiful data, technology is helping us. Coming to Big data, there are mainly three “V’s” which

helps in defining the Big data phenomenon, these criteria’s are volume, velocity and variety,

also two more sub‐criteria’s are veracity and value of data captured. Big Data is a new source of

idea generation for product development, customer service, shelf location, distribution,

dynamic pricing, and so on (Erevelles et al., 2016). In a hyper‐competitive marketplace where

great ideas are easily copied, a firm must enhance its speed of idea generation to achieve a

sustainable competitive advantage; Big Data may enable firms to accomplish such a desirable

goal (Erevelles et al., 2007). Researchers are encouraged to study the role of Big Data in

generating ideas and enhancing creativity within a firm to improve its performance.

To better comprehend the effect of Big Data on different business exercises, empowering firms

to better endeavor its advantages, a reasonable structure that expands on asset based

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hypothesis is proposed. Three assets physical, human, and authoritative capital‐direct the

accompanying:

(1) The procedure of gathering and putting away confirmation of customer movement as Big Data, (2) The procedure of extricating shopper knowledge from Big Data, and (3) The procedure of using buyer understanding to upgrade dynamic/versatile abilities. Besides, exceptional asset prerequisites for firms to profit by Big Data Big data is helpful in understanding so many sub‐sections of marketing analytics such as consumer analytics, operations analytics, supply‐chain analytics and people analytics etc. which leads to the development of new marketing strategies or implementation of marketing analytics. Exploitation of Big Data can be clearly termed as a future for Marketing Analytics. A Marketing Analytics refers to the identification and implantation of most effective and specific strategies with the use of tools and technology which would help in evolving the market ways for selling a product/brand/service. Sub‐parts of marketing analytics a) Consumer analytics is the process of understanding consumer’s behavior and analyzing their insights about a particular company’s products and services. b) Operations analytics is the process of using technologies and resources to use the Big Data to make business decisions and matching supply with demand, also in prediction of future demand uncertainties. c) A supply chain analytics consists of the complete process from getting raw materials from suppliers on time, maintaining contingency stocks, stages of production till the development of finished goods, the delivery in accord to customer expectations effectively and efficiently before other suppliers/business. This all requires the help of big data analytics, i.e., using customer‐related data to draw adequate conclusions about information. The general benefits which can be easily identified from the use of big data are improved buyer and seller relations, lower average cost of production and supply, diminished delivery times. d) People analytics involves using the Big Data to recruit and manage human resources more effectively irrespective to the traditional approaches and relation building styles.

4. A framework for locating and equipping marine oil‐response facilities

Manish Verma

Introduction: Marine transportation, the primary mode for moving oil in Canada, was also

responsible for a country‐high 60 million tons of crude oil and petroleum products transiting

the Newfoundland maritime infrastructure. These numbers have been increasing since 2000,

and the trend is likely to continue given the proposed development of additional off‐shore

petroleum platforms and new refineries in southern Newfoundland. While the region has

benefited tremendously from increased oil‐related activities, there is a concern, especially

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among the neighboring communities about the province’s preparedness to deal with potential

oil‐spill emergencies. This is an extremely crucial concern because this region experiences over

20,000 vessel movements annually, and hence even a minor oil‐spill episode could be

devastating for the human and marine population, and the tourism‐based economy.

Problem Description: This study deals with location under uncertainty, and is concerned with

both the strategic and tactical aspects of the oil‐spill response problem for this region. More

specifically, we will answer two questions: first, where to locate adequate emergency response

facilities; and second, what types of equipment to stockpile at each facility. Given the strategic

(and tactical) focus of this work, it is important to take into consideration the different known

and uncertain factors likely to impact the spill event, as well as the consequent response

planning. For example, emergency response center location decisions should incorporate: the

projected marine accidents and vessel traffic over the planning horizon; the critical time

associated with each spill location; the estimates of economic and environment damage

resulting from various oil spills; and the estimates of different oil‐spill volumes. Note that while

some of these factors could be reasonably captured via deterministic estimates, others cannot.

For instance, the exact location, volume and type of spill, as well as weather conditions are

uncertain. Hence, probabilistic estimates of various oil‐spill profiles were developed using the

extensive data made available through Transport Canada and Canadian Coast Guard.

Modeling Approach: Although many techniques have been developed to deal with uncertainty

in mathematical programming, stochastic programming with recourse is cited as a general‐

purpose technique that can deal with uncertainty in model parameters. Stochastic programs

with recourse are employed to make decisions prior to the realizations of some random

variables such that the total expected costs of possible recourse actions are minimized. More

specifically in our two‐stage model, the first stage focuses on facility location and equipment

package acquisition decisions, whereas the recourse problem solved in the second stage uses

information about oil spill to make equipment response and dispatch decisions. Subsequently,

the two‐stage stochastic programming model is equivalently stated as a single optimization

program, which has both deterministic and stochastic parameters.

Parameter Estimation: In an effort to take advantage of the extensive information developed

through numerous studies and also to test our model on realistic data, we estimated the values

of the relevant parameters from the Transport Canada reports. In addition, the authors had

personal communication with the environmental response unit of the Canadian Coast Guard.

Computational Results: We used CPLEX 12.4.2 to solve the resulting problems to optimality for

all combinations involving the three different facility costs, three different equipment costs and

both linear and non‐linear settings, and three different spill volumes (i.e., 54 scenarios). The

resulting analyses revealed that with higher equipment acquisition costs, fewer equipment

packages were stockpiled at the open facilities, thereby reducing the overall coverage. On the

other hand, with decreasing facility costs, one noticed an increase in the number of open

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facilities, which in turn had an equivalent impact on coverage. Hence, it was evident that since

coverage resulted from the trade‐off between expected environment cost with respect to

facility and equipment costs, some results may not do much to assuage the concerns of the

general public. This is because the “expected environmental cost” does not capture the impact

of intangible attributes such as public disutility or adverse perception of catastrophic events

such as an oil spill. In an effort to conduct additional analyses by incorporating such intangibles,

we applied a multiplier to the expected consequence cost term in the objective function and

then solved the problem instance for different values of the multiplier, i.e., disutility factor.

It was evident that larger values of the multiplier put greater emphasis on the expected

environmental cost, thereby yielding better coverage through increased facility and equipment

costs. This was not surprising since larger values of the multiplier meant that not covering an

oil‐spill situation was more expensive, and hence resulted in better coverage. In addition, it was

possible to deduce that the total cost curve under the non‐linear setting was definitely concave,

and somewhat concave under the linear equipment cost setting. This implies that the total cost

will increase at a decreasing rate with increasing disutility factor value, and hence it will cost

proportionately less to provide better coverage.

Finally, since we did not know the budget of the policy makers nor their precise mandated

coverage requirement, we conducted further analyses to facilitate future decision making with

respect to adding new facilities, equipping them and the resulting coverage. To this end, we

generated two types of solutions: first, we used the current location of the response facility to

generate the incremental solutions; and second, we specified the number of facilities to be

opened and then generated the so‐called Greenfield solutions. The resulting analyses under

both the settings revealed that locating more than two facilities was not reasonable because

the percentage of oil‐spill situations covered did not improve with more facilities. In addition,

we also noticed that the variable cost did not change since opening a new facility just forced a

portion of the required equipment package to be bought by the newly added facility, and had

no impact on the total number of equipment.

Conclusion: The south coast of Newfoundland accounts for a significant portion of marine

transportation of crude oil and petroleum products in Canada, and has been a source of

concern due to the potential for oil‐spill emergencies. In this work, we have proposed a two‐

stage stochastic programming approach that answers two questions: the location of emergency

response facilities, and the appropriate equipment stockpile at each facility. The proposed

optimization program was tested on realistic data collected from publicly available reports and

through personal communications. In an effort to account for the stochastic nature of input

parameters, a number of scenarios were generated using the base numbers procured from the

above sources.

Through extensive computational experiments, we can conclude that in general the number of

facilities and equipment stockpiles is a function of the trade‐off between expected

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environmental costs versus facility and equipment cost. Furthermore, the size of the equipment

stockpile for the region depends on the societal disutility factor, and increases with higher

values of the factor. More specifically, for the area of interest, a maximum of two facilities is

most appropriate since any additional facility will not improve oil‐spill coverage, but will merely

result in the redistribution of equipment packages among various open facilities.

5. An analytical approach to rail‐truck intermodal transportation of

hazardous materials with capacity selection & terminal congestion

Manish Verma.

Introduction: Intermodal transportation, defined as the transportation of goods by a sequence

of at least two different modes, continues to be one of the dominant segments of the

transportation industry. Rail‐truck intermodal transportation, which exploits the positive

attributes of both trains and trucks referred to as drayage, has experienced phenomenal

growth in the last four decades and continues to grow. Note that the attractiveness of rail‐truck

intermodal transportation, in part, stems from two sources: first, the significant reduction in

both delivery and lead‐time certainty because of the schedule‐based operation of intermodal

trains; and, second a more efficient and cost‐effective overall movement ensured by combining

the best attributes of the two modes. Although intermodal transportation, in general, has

received increasing attention from researchers over the past two decades, most of the

discussion is focused on regular freight. Fortunately, this area has received some attention from

academic researchers over the past decade, and the relevant effort has been primarily at the

strategic and tactical levels involving transportation and terminal location decisions.

Problem Description: The proposed study investigates the impact of congestion at the rail

intermodal terminals and its impact on hazmat shipments, and thus extends our earlier

contributions in this domain. Our problem is to determine the best shipment plan for both

hazardous and non‐hazardous freight in a rail‐truck intermodal network, wherein a set of pre‐

defined lead times must be satisfied in choosing the truck routes and the intermodal train

services to be used. The objective is to minimize the total cost as well as the total public risk

associated with intermodal hazmat shipments. Note that this task is complicated because

hazmat risk at terminals needs to be determined by modeling congestion using Markovian

queues, which in turn will drive the decision about equipment capacity (acquisition or

operations) decisions, and only then intermodal freight routing decisions can be made.

Furthermore, it is necessary to streamline the inbound drayage, intermodal rail haul and

outbound drayage activities while making the trade‐off between total cost and total public risk.

Modeling Approach: We propose a bi‐criteria nonlinear optimization model with cost and risk

objectives. The cost objective contains inbound drayage cost, rail haul cost, outbound drayage

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cost, fixed cost to operate different types of intermodal train services, and the equipment

acquisition cost at the terminals. The risk objective, on the other hand, contains population

exposure due to drayage, various intermodal trains, and from terminal congestion. We simulate

the congestion risk by finding the product of the terminal risk and the average number of

hazmat containers waiting to be served. We used realistic size problem instance data from

earlier peer‐reviewed works, and consulted the appropriate sources for updated information

on cost and risk parameters.

Solution Methodology: In the presence of nonlinear expressions in the risk objective and one of

the constraints, it was not possible to solve realistic‐size problem instances through the

general‐purpose optimization software. Hence, we proposed a customized solution

methodology that exploits the problem structure. More specifically, we combine simulation

with non‐dominated sorting Genetic Algorithm to simulate a set of arrival rates for terminal

equipment, which is then used to estimate average waiting time and consequent hazmat risk.

The algorithm continues until no improvement is encountered in 1000 consecutive offspring.

The conference presentation will contain complete details of the proposed algorithm,

Computational Results: The solution methodology was coded in C#, and numerical experiments

were performed on Intel Core i5 CPU 1.80 GHz with 8 GB RAM. Two of the most common

techniques for solving multi‐objective models are pre‐emptive optimization and weighted

sums, and we make use of the latter approach. In addition, we perform a parametric analysis by

attaching different weights to the two objectives. The resulting analyses revealed significant

lowering of waiting times for hazmat traffic compared to regular traffic, thanks to the

implementation of non‐preemptive priority queuing principle. This is important since most of

the rail intermodal terminals are close to population centers in North America, and thus both

the average waiting time and the number of hazmat containers waiting to be processed

become critical in determining public risk. Hence, conceivably, any effort to lower the waiting

time and number in the queue should reduce terminal risk.

In an effort to get managerial insights into the problem instance, we conducted the standard

risk‐cost analysis by emphasizing one objective over the other, and then examined factors that

affect terminal congestion.

Risk‐Cost Tradeoff: We noticed that ten of the eleven solutions were clustered around the

minimum cost, which in general signals the dominance of cost over public risk. We investigated

this further by solving additional problem instances, and it was noticed that the dominance of

cost starts waning when risk has a weight of at least 0.95 (i.e., cost would have a maximum

weight of 0.05). This is important since, in this instance, attaching equal weight to the cost and

public risk objectives is unlikely to provide a solution acceptable to both the regulatory agencies

and the transport companies. Other related insights and interpretations would be provided at

the conference presentation.

Factors impacting congestion risk: The computational experiments revealed three factors likely

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to impact congestion risk. First, utilization rate of the cranes is crucial –since higher rate implies

longer average waiting time for hazmat containers. Hence, either purchasing more cranes or

using better technology such that waiting times are reduced could be one of the ways to

mitigate public risk at the terminals. Second, shorter delivery times forced the purchase of

more equipment and use of faster trains thereby increasing the cost, but have a positive

bearing on congestion risk. Third, higher demand would result in increased cost and congestion

risk.

Conclusion: In this paper, we propose a bi‐objective optimization framework for planning rail‐

truck intermodal shipments, when terminal equipment capacity and congestion are considered.

Congestion was captured by implementing a non‐preemptive priority queue discipline on the

containers arriving at various cranes (equipment), with higher priority being accorded to

hazmat. The existence of non‐linear terms in the risk objective and the constraints necessitated

developing a customized solution methodology that makes use of the attributes of genetic

algorithm for multi‐objective problems with CPLEX, which was applied to realistic size problem

instances generated using the problem instance from existing literature.

Through extensive computational experiments, we conclude the following. First, congestion at

the terminals is a non‐negligible source of public risk, and could be a significant source if

intermodal terminals are close to population centers. Second, terminal congestion risk can be

mitigated using a variety of measures. For example, using better technology to process

incoming hazmat containers would ensure lower transit time, which in turn has a positive

bearing on risk.

6. Idea for a Lean‐Agile supply chain for the Armed Forces.

Pankaj Sharma and Makarand Kulkarni.

Armed forces are characterized by huge inventories collected because of the "Just in Case"

concept of stocking. Such large inventories are no more acceptable as there is always a

pressure on the army logistics to cut costs and be lean. This will help in reducing the logistics

footprint in the tactical battle area and also make the fighting force more maneuverable.

However, when the army is fighting a war, it requires quick replenishment of spare parts and

other war like supplies. Cost cutting takes a back seat and mission reliability assumes

paramount importance. In other words, the spare parts supply chain of army is required to be

both lean and agile. These two contradictory requirements are proposed to be fulfilled by using

a dynamically changing time‐separated lean‐agile spare parts replenishment system. The spare

part supply chain needs to be lean during peace and agile during wars. This paper will present a

framework for such a dynamic lean‐agile system for replenishment of spare parts in the army.

The paper then identifies the decision variables that are required to be changed in order to

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dynamically shift the system from lean to agile and vice‐versa. The values of these decision

variables in each of the emergency levels is also discussed in the paper.

7. Synchronizing Electrical Energy Generation and Distribution Supply Chains Ashok Matani.

In India, though power theft is one of the strongest incentives to install smart meters, there are

other compelling factors such as the need to reduce technical power losses and peak power

deficit and bringing in more efficient transmission of electricity to rewarding consumers who

help in reducing peak power demand. A smart meter is an electronic device that records

consumption of electric energy in intervals of an hour or less and communicates that

information daily for monitoring or billing. Smart meters also enable two‐way communication

between the meter and the central system. They also put consumers in control of their energy

use, allowing them to adopt energy efficiency measures that can help save money on their

energy bills. With the smart meter, one can keep a track of power usage at home in his or her

absence curbing the energy wastage by their children or servants. This can also be connected

with the solar power generating units and even with the grid connected solar systems

effectively.

Ministry for Power, Coal and New and Renewable Energy of Government of India have asked

the meter manufacturers to design a multi‐tasking smart meter displays power consumption at

home in real‐time with giving details of usage of every appliance and point using electricity. The

smart meter would be for those who use more than 200 units a month.

8. Greener Supply Chains towards Environmental Protection in Food

Processing Industries

Ashok Matani

In present economic scenario, organizations are trying to achieve sustainable competitiveness

in global markets. Sustainability incorporates the concepts of economic, social, and

environmental performance. Green supply chain management (GSCM) practices comprise

green design, reducing energy consumption, reusing/recycling material and packaging, reverse

logistics and environmental collaboration in the supply chain. This paper highlights latest

developments in supply chain management practices towards making green supply chain

management more effective and environmental friendly in various industries

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9. A review on the experimental usage of classical, Shanin and Taguchi design

of experiment (DOE) with Data Mining approach using six sigma DMAIC.

Karuppanna Prasad N, Sekar K and Manohar M.

In present days, the organizational work environment run day in and day out with the daily

routine work environment where preparing and conducting an offline design of experiment

(DOE) in the steady state work environment leads to impact on organization Productivity,

Quality, Cost, Delivery, Safety and Morale(PQCDSM). Organization faces a heat waves due to

market pressure that urges organization to build up a reliable decision with proactive for

making the process in control that will contributes towards organization achieving on technical,

financial and strategic issues. In modern era, a new phrase is coined by the name “Continuous

quality improvement” that plays a focal role in for strengthening and sustaining an organization

sector. The organization are thriving to enhance the quality continuously by using competitive

strategies. The Total Quality Management (TQM) is one of the endemically applied strategies in

organization to sustain the heat waves external market, TQM a people and analytical approach

uses tools, techniques and system like cause and effect diagram, kaizen, quality functional

deployment (QFD) and ISO 9000 series based quality management system (QMS) with operator

level skill matrix for enhancing the operator skill. In present day conditions practicing and

implementing TQM makes myriad of concern failed for achieving the process quality

improvement day in and day out. To overcome, six sigma as proposed by Motorola provide a

pathway for achieving “Continuous quality improvement” through belt based training using six

sigma Define, Measure, Analyze, Improve and Control (DMAIC) stratum and creating of training

cum infrastructure in the organization premises. In afore mention ways for process

improvement the belt based six sigma DMAIC training proves to be an inexpensive yardstick

approach for continuous process improvement and process satisfaction. In DMAIC stratum each

word provide a meaning on the same such as in define the problem faced by the customer most

frequently are addressed by measuring the processing stages for data collection followed by

analyzing the data for causes and root causes for action on choosing the optimal process

parameter setting for continuous quality improvement culminated by incorporating the

changes in Quality Control and Process Control (QCPC) and Standard Operating Procedure

(SOP). In Six sigma DMAIC the application of design of experiment (DOE) plays an imperative

role in the improvement stage to identify the optimum settings for process parameters. DOE an

experimental tool was used for identifying the focal input variable that create variation in

product and process. The variability in the performance of process impacts the profit of an

organization, thus declination in process variability will create a defect free production system.

DOE an experimental tool for enhancing the product performance was firs established by Sir

Ronald fisher in the year 1930 by the name as classical DOE or “one factor at a time” in the field

of agriculture. The one factor at a time was said to be time consuming for choosing the

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optimum process parameter setting that gives the birth to shanin DOE in the year 1970

developed by Dorian shanin is a statistical tool for identifying the red‐x, pink‐x and pale pink‐x

causes that contribute towards 80% of machine variation. Prolong years of working by box and

hunter in service and manufacturing organization provide a new pathway for conducting

experiments and converting theory to practical by the name Hunter – Box – Hunter (B H2)

experimental design in the year 1980. Later stages, there evolve a discussion in academic circles

in the year 1990 to make DOE simpler and can be used by the manager through the name

taguchi DOE later crafted by the name Taguchi robust design. The present day problem on

using DOE is as we are well aware that organization GEMBA revolve around a routine work

environment, since DOE an offline conduction tool impacts the routine work that leads to a

consequence of unpleasant results. Another concern in DOE was inclusion of more variables

leads to more experimental run that impact cost to company.

In the previous dual decade there arise a huge scope and development in an interdisciplinary

knowledge field known as data mining that stratify the data from data history sheet .The

decision tree model is one of the most familiar data mining method due to it intelligent decision

making, some of the common algorithm based on decision tree model used in data mining are

C4.5 developed by Quinlan (1986) and its extended version C5 followed by Classification and

Regression Tree Algorithm(CART) developed by Breiman (1984) and Chi‐squared Automatic

Interaction Detection (CHAID) by Kass (1980).The usage of data mining have a huge scope in the

organization sector without effecting the routine work environment on one side and

technological advancement in the information technology and sensor technology on the other

side that had made data mining a fruitful tool in the manufacturing process. Real time in the

shop floor of the manufacturing process the process condition or process parameter setting or

control parameter setting was adjusted by the process engineers that impact the quality of the

product due to least awareness cum capability of the process engineers for using an

interdisciplinary tool like data mining in the organization work environment. From all the afore

said statements, it is clear that data collection during routine environment and ineffective

process adjustment were two red‐x causes that impact process performance on quality. To

overcome from dual red x causes that impact the organization work environment data mining

proves to be a focal tool in the field of process control, quality improvement, fault decision and

diagnosis, process design and maintenance over classical, Shanin, Taguchi DOE and data mining

approach for process improvement with an aid of applying it in six sigma Define, Measure,

Analyze, Improve and Control (DMAIC) to enhance organization effectiveness in manufacturing,

service and unconventional sector.

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10. Performance Measurement of supply chain: a changing paradigm

Anil Sathe.

Preamble: Organizations promise customers, a range of deliverables /solutions through various

products /services. Nobody can deny the contribution supply chains make in delivering these

promises.

At the same time, supply chain management has become much more complex due to global

sourcing, highly demanding customers, shorter product life etc.

when some leading stores announce “same day delivery”, it is obvious that they have done lot

of work to keep the product ready whenever asked.

This means that we need to transform the whole cycle from planning to distribution to deliver

customized solutions “wherever required, whenever required”.

Performance measurement: With realignment of supply chain to new expectations, its

performance measurement needs realignment too.

While the focus will remain on costs, quality and delivery, the definition of these terms will

become wider, sustainability will be a key consideration, customer‐centric approach will be the

decision making factor and technology will provide competitive advantage…

Multiple dimensions of this process are nicely explained in framework below (source: Journal of

business logistics). Key is to strike balance across the entire three axis load.

Few things before we begin…

• Performance measurements have to be in sync with changing organization objectives and

customer requirements. This makes it a process which is “subject to continuous

review/update”

• KPIs will have to have a balanced approach

• Localizing priorities will damage business particularly when there is conflict between

stakeholders

• While looking at terminologies like costs, efficiency, optimization etc. one has to ensure that it

has organizational perspective

• What you set to achieve will depend on where you are today (as is status), where you wish to

be (future status) and the timelines

Irrespective of where maturity level in supply chain, focus on the following areas will be a

common feature:

1. Agility, Adoptability, Alignment

2. End‐To‐End Visibility

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3. Building customer loyalty

4. Sustainability

5. Innovation

6. Deployment of IT solutions

7. Skill development and retention

Let us look at each one in detail:

1. Agility, Adoptability, Alignment:

• Together they represent SCM’s ability to respond to external stimulus: could be disruption in

supplies, natural calamities, sudden order etc.

• As per Dr. Hau Lee of Stanford, this has to be measured against time (ref Supply chain digest

article dated July 23rd 2010). Ability to respond in one month may be dramatically different

that one week

• Second important aspect would be likely correction (% change in output, time) required.

• It is important to balance this with costs… Gene Tyndall of Tompkins Associates says “Supply

chain managers to be cautious about flexibility. Flexibility usually comes with an added cost,

and this must be weighed against the value proposition for it.”

• As we can see, measurement of this is not easy. However we can recognize the agility based

on the approach to the situation. We can see in the chart below the few examples of

Traditional approach V/s Agile approach.

• Measurement for each supply chain will vary depending on the type of business and

competitive strategy of the organization. For e.g. Productions processes, Type of product

“Made to order or Made to stock) etc. can create different situations to handle /respond

2. End‐To‐End Visibility

• Aberdeen report (May 2013) defines Supply chain visibility as the awareness of, and control

over, specific information related to forecast, capacities, orders and physical shipments, and

other data such as customer preferences /feedback/returns etc.

• Visibility is a prerequisite to supply chain agility and responsiveness

• Decisions to be made are data points, sources for data, frequency, analytical support and

distribution of the data etc.

Depending on role in the organization, performance measurement can be set to cover these

areas. One such approach has been highlighted below. Simple principle to be followed is

“sharing information / making things visible allows people to take informed decision”

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3. Building customer loyalty:

Chief supply chain officer’s report (2014) highlights importance of SCM contribution to

customer service and loyalty in different industries. It is an eye opener.

SCM at all levels contributes to this and following is one way to implement /measure the same

at all levels;

• At Micro level focus is on improving ‐ demand, manufacturing, supply, distribution,

transportation ‐ within a company's supply chain. The goal is to accelerate the efficiency and

performance and measure could be reducing miles, safety stock, and idle capacity, while

increasing production utilization and quality

• At Macro level focus is on improving the performance of supply chain in totality. The goal is to

optimize the efficiency and performance between multiple areas and measure could be

increasing return on assets, working capital and market share

• At enterprise level focus is on integrating supply chain with the supply chains business

partners, vendors and customers, to satisfy mutual needs. Goals could be being first to the

market; long‐term deals etc. and measures could be time to introduce new products and

services, redundant process quality checks etc. Even measures like repeat business are very

important

4. Sustainability

• The well‐adopted definition of sustainability is that of the Brundtland Commission (World

Commission on Environment and Development, 1987, p. 8): “development that meets the

needs of the present without compromising the ability of future generations to meet their

needs.”

• Balanced approach can be evolved when we understand relationship between the integration

of the concepts of sustainability and supply chain management, and long‐term economic

success.

• Areas to look at in Supply Chain would be:

Logistics: Mode of transport, distance travelled, energy efficiency, handling of hazardous

cargo, safety of people involved etc.

Packaging: Extent of packaging, recycling, conservation of wood etc. Choice of materials: Avoid the ones which damage environment

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Wastages and Disposal: Wastage percentage, disposal method, damage to environment etc.

(for e.g. Handling E‐waste, recycling of plastic etc.)

Best way to build sustainability goals in these areas will be to ensure that benchmarks are

established and measure year‐on‐year improvements.

5. Innovation

• In his seminal work “The Innovator’s Dilemma,” thought leader Clay Christensen describes

two types of product innovation: sustaining and disruptive. Both types of innovation are likely

in SCM.

• Few suggestions to build innovative culture;

Variation: Take a concept such as “self‐serve” operations and apply it to your business. For e.g.: Web‐check in process, electronic fund transfers etc.

Reversal: Outline a current process, and then reverse it. Vendor‐managed inventory is a

classic example.

“What if?” Ask what would happen if you had to design a new way of serving your customers.

Sharing of infrastructure within competitors is an example

Starting over: If you were redesigning your product or service, what changes would you make? Would they alter your competition? Would they change your customer base, locations,

or resources?

• Measurement:

No of processes changed Growth without additional resources Development of lead indicators

Customer empowerment etc.

Some examples of supply chain innovations are given below:

6. Deployment of IT solutions:

• Use of Information Technology (IT) across the supply chain can become source of competitive

advantage. Deloitte supply chain leadership survey of 2015 gives us a very clear picture on this.

• The objectives of IT in SCM are (Simchi‐Levi, 2003):

Providing information availability and visibility

Enabling a single point of contact for data

Allowing decisions based on total supply chain information

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Enabling collaboration with partners

• Application areas are many and lot depends on present status. However, area such as e‐

sourcing, mobility solutions, customer interaction are few of the key areas today

• Measurement again will largely depend on present status but could be from “assessment to

full scale deployment” of the solutions

7. Skill development and retention

• Skill set required in supply chain today has dramatically changed and calls for constant up

gradation

• Big supply chain trends include:

The rising role of the cloud and digitization of products Mobility

Social media’s influence

Huge information base / data available with customers

Increasing need to provide end‐of‐life solutions to products • Skill development must bring in readiness to be prepared for this

• This would also have to include innovation, creativity, ethics, compliance etc.

• Lastly this must be done for complete team and hence measurement has to include both the

head of SCM and subordinates from identifying needs to effectiveness

To sum up:

We firmly believe that these changes in performance management have already begun across

the world and will decide the leaders of tomorrow.

It is time all recognize contribution made by supply chain in meeting corporate objectives and

change measurements which will bring out the best: in individuals and supply chain itself.

11. Optimal replenishment policy and preservation technology investment

for a non‐instantaneous deteriorating item with stock‐dependent demand

Haimanti Pal, Sudarshan Bardhan and Bibhas Giri.

Purpose: The purpose of the work is to develop and analyze an inventory model under certain

realistic business assumptions and to derive optimal business strategies so as to maximize

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average profit.

Assumptions and methodology: An inventory model for a retailer facing deterministic stock‐

dependent demand (with exponential form of dependence) has been developed and analyzed.

The item is assumed to start perishing at a constant rate after a certain time period from when

it reaches the retailer. The retailer has the option to invest in preservation technology to reduce

the effective deterioration rate. To keep the model realistic, the expenditure on preservation

technology is assumed to have a diminishing return. The model has been analyzed to find

optimal amount of investment as well as business cycle length so that average profit is

maximized. An algorithm is provided to find the optimal values of decision variables quickly.

Findings: Optimal values of the decision values have been obtained here. Certain conditions

have been derived to distinguish between the situations where the retailer should or should

not invest in preservation technology. A condition on the time‐point when deterioration starts

has been derived, which acts as a lower bound. Situations have also been identified when it is

always beneficiary to invest in reducing deterioration. Sensitivity analysis has been performed

to examine the stability of the solution as well as its inherent dependency on other

uncontrollable parameters.

Practical implications: In reality, the deterioration rate may be controlled by taking certain

measures in preserving the items. As higher deterioration rate has considerable impact on

system profit, supply chain managers may think of investing in preservation technology to

reduce the effective deterioration. As the technology comes at a cost, the decision of investing

(or not investing) is always a concern for the retailer, particularly when the selling season is

sufficiently short. The retailer may shorten the replenishment period instead in order to reduce

deterioration in his inventory, and thereby bear lesser preservation cost. When and how much

to invest for preservation is therefore a very important decision for the retailer. The present

research throws some light in that direction, and identifies situation when it should be wise to

invest (and how much), or how much the cycle length should be reduced so as to avoid the

effect of deterioration successfully, without compromising the profit.

Originality: The present work is a two‐step generalization of Hsu et al. (2010) as (i) the

assumption of constant demand has been extended to be stock sensitive, and (ii) instantaneous

deterioration is generalized as the non‐instantaneous one. The present work may somewhat be

considered as a partial extension of the work of Dye (2013) too, which studied non‐

instantaneous time‐dependent deterioration under constant demand scenario.

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12. Role of HR in Lean Manufacturing Implementation – a Comprehensive

Study

Protik Basu and Pranab K Dan.

Purpose: Lean management is a process improvement technique (Bamber et al., 2014) and lean

principles have been recognized as a competitive advantage (Pakdila and Leonard, 2014).

Although there have been a few studies for the various aspects of HR in lean implementation,

there is no comprehensive study of the same. The purpose of this study is to have a detailed

study of the relationship and role of HR in the implementation of lean manufacturing, enabling

the manufacturing industries to strategize towards successful lean implementation.

Design/methodology/approach: The methodology followed by the authors in this study has

three fundamental parts. The first part is to analyze the current literature on the role of HR for

lean initiatives in manufacturing industries. Based on this literature survey, a questionnaire has

been designed for collection of responses with respect to HR practices for lean implementation.

The third part is to suggest a framework incorporating the entire set of HR practices required

for lean implementation. This framework is expected to be empirically tested using statistical

techniques on the responses from manufacturing firms.

Findings: Lean manufacturing is gaining popularity as an approach that can achieve significant

performance improvement in the industry (Susilawati et al., 2015). Lean has been distinguished

as ‘a bottom up approach where management plays a supportive and facilitating role in

engaging shop‐floor workers to form cross‐functional self‐directed work teams and apply Lean

tools’ (Shah et al., 2008). Management commitment has been considered as a significant critical

success factor for lean six sigma deployment. (Bakar et al., 2015). Long‐term philosophy of

growth is at the heart of lean (Pakdila and Leonard, 2014). Multifunctional workers, expansion

of autonomy and responsibility, few levels of management, worker involvement in continuous

quality improvement programmes, work time flexibility, team decision making, worker training,

innovative performance appraisal and performance related pay systems have been considered

as the best practices of HR for a lean enterprise (Panizzolo et al., 2012). Additionally, teamwork,

cooperation, and, involvement, commitment and motivation of the employees are considered

as critical parameters for successful lean implementation. Training and education of individuals

towards lean orientation (Bakar et al., 2015) accompanied by effective leadership (Ravikumar et

al., 2013) and right corporate culture (Bhasin and Burcher, 2006, Wong and Cheah, 2011) will

ensure a smooth and effective implementation process of lean manufacturing. Managerial

action needs to be taken to minimise any negative effects of lean implementation, if any

(Angelis and Fernandes, 2012). Lean was initially viewed as another downsizing method and

such misconceptions must be handled with care (Cudney and Elrod, 2011). An expert full time

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lean consultant as facilitator is critical for successful lean implementation (Ravikumar et al.,

2013). 22 such HR practices, including role of top management, have been considered in the

framework thus developed for successful lean implementation. Analysis of the survey data is

expected to validate the key constructs identified.

Research limitations/implications: This research is applicable primarily to the manufacturing

sector and is expected to provide further insights for lean implementation. Further research is

required to explore the relationship between HR and lean manufacturing. Technical aspects of

lean adoption are not covered in this paper but should be taken into account by companies

willing to undergo lean implementation.

Originality/value: There are researches on lean implementation but this work is one of the very

first researches to have a comprehensive study of the HR practices for implementation of lean

manufacturing. Piecemeal research studies have been done in the past on HR parameters but

this study intends to bridge the gap and integrate all the parameters into a single

comprehensive study, aimed at practical implementation of lean manufacturing. This is a

notable and promising outcome of the current study, especially from a strategic viewpoint.

Keywords: Lean manufacturing, HR practices, lean implementation, critical parameters.

13. Coordinating a Three‐echelon Supply Chain with Uncertain Demand and

Random Yield

Sudarshan Bardhan, Bibhas Giri and Tarun Maiti.

Purpose: One of the major objectives of modern supply chain management is to deal with

the growing decentralization among the entities and hence minimizing the double

marginalization effect inside the chain, especially when the end‐customers' demand is not

deterministic. The problem of deciding optimal supply/production quantity becomes even

more complicated when the production process of the manufacturer(s) becomes subject to

random yield. Also, to improve the performance of the members as well as total chain in

terms of accumulating more profit by the members of the chain, some kind of coordination

mechanism is necessary. The purpose of the present work is to address all the issues by

formulating a suitable mathematical model, pave the way to coordination leading to

satisfactory channel performance, and provide relevant managerial insights to the supply

chain managers.

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Assumptions and Methodology: A three‐layer supply chain consisting of one raw‐material

supplier, one manufacturer and one retailer for trading a single product over a single period

of time is assumed here. The market demand is assumed to be stochastic. Productions at

both the raw‐material supplier as well as the manufacturer are instantaneous, and are

subject to random yield. After the raw‐material supplier declares unit wholesale price of the

raw‐material, the manufacturer declares unit wholesale price of the finished product,

depending on which the retailer places an order of finished goods. Depending on the order

quantity, the manufacturer decides his optimal production quantity and places order of the

same amount to the raw‐material supplier. Depending on the order placed by the

manufacturer, the raw‐material supplier decides his optimal production quantity and starts

production. If the amount produced by the raw‐material supplier is lesser than that ordered

by the manufacturer, the supplier buys the deficit amount from the spot market at a higher

price and supplies the whole batch to the manufacturer; otherwise, the excess amount is

sold by the supplier at the secondary market at a reduced price. Similar procedure is

followed by the manufacturer too. The retailer faces shortage or over‐stocking after the

selling season. The centralized model is provided as the benchmark case. The expected

profit for each channel member is maximized under decentralized scenario, and

corresponding optimal values are decided. Finally, a composite coordination mechanism is

proposed to coordinate the chain successfully.

Findings: It has been seen that no simple contract is able to coordinate such a complex

chain alone. A new composite contract is framed combining buyback and two‐way sales

rebate and penalty contracts together, and shown that it is able to coordinate the chain.

The contract has been made flexible enough to alleviate the risk of production/demand

uncertainty for a wide range. The way changes in market scenario (through varying

parameter values) affect both optimal decisions as well as channel performance has also

been exhibited through sensitivity analysis.

Originality: He and Zhao (2012) generalized previously studied three echelon supply chain

models by considering randomness in production process at the supplier's end. However,

their model assumed deterministic production rate at the manufacturer, a limitation

towards modeling real life business companies' network. The limitation has been removed

in the current paper as random yield at the manufacturer has also been considered,

reflecting all the uncertainties a three‐echelon supply chain may face. The added

uncertainty enforces the manufacturer to realign the terms of coordination contracts, and

bring the supplier under the hood of it.

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14. Investigations on Raw Material Supplier Selection Methodology Using

Fuzzy Logic

K. Kalidas, K. Sundaraj

Several factors make new suppliers important. First, there may exist new suppliers that are

superior in some way to a firm’s existing suppliers. For example, a new supplier may have

developed a novel production technology or streamlined process which allows it to significantly

reduce its production costs relative to predominate production technology or processes or a

new supplier may have a structural cost advantage over existing suppliers, for example, due to

low labor costs or favorable import/export regulations in its home country. Second, existing

suppliers may go out of business, or their costs may be increasing. Third, the buyer may need

additional suppliers simply to drive competition, reduce supply disruption risks, or meet other

business objectives such as supplier diversity. In recognition of these reasons, buyers and their

internal customers may be obliged by company policy to locate a minimum number of viable,

potential suppliers for every product or service procured. So it is important to have a supplier

rating for raw material suppliers. The main focus of the paper is on foundry raw material

suppliers where the quantity required is high. Fuzzy Logic Tool in Matlab is used for rating.

15. A Hybrid Model Based On SWARA And WASPAS MCDM Methods For

Supplier Selection.

Naveen Jain, Amitraj Singh and Akhilesh Kumar Choudhary.

In the competitive global market scenario, selection of potential supplier offers a solution to

gain competitiveness. Selection of potential supplier depends on quantitative and qualitative

criteria’s. Further these criteria’s are conflicting in nature. Hence supplier selection is Multi

Criteria Decision Making (MCDM) problem. This paper proposes a frame work for the selection

of most reliable and suitable supplier for industry. This study proposes a MCDM model that

combines two new MCDM methods, Step‐wise Weight Assessment Ratio Analysis (SWARA) and

Weighted Aggregated Sum Product Assessment (WASPAS) method for supplier selection. The

proposed methodology is demonstrated with a numerical example.

16. Routing Alternative Fuel‐powered Vehicles for Garbage Collection

Yuvraj Gajpal, Shuai Zhang, Mohamed Abdulkader and S. S. Appadoo.

This paper considers the garbage collection problem in which multiple compartment vehicles

are used to collect the garbage. The vehicle is considered to be an Alternative Fuel‐powered

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Vehicle (AFV) with small fuel tank capacity compared to the tank capacity of traditional fossil

fuel powered vehicle. The AFV is allowed to refill the fuel from the main depot only. We provide

mathematical formulation for the proposed problem. We develop two solution methods to

solve the problem. The first solution method is based on the saving algorithm while the second

method is based on the ant colony algorithm. We generate new problem instances to evaluate

and to compare the performance of the proposed algorithms.

17. Role of Big Data in Decision Making

Sneha Kumari, Shirish Jeble and Yogesh Patil.

Purpose: Information systems coupled with internet, cloud computing, mobile devices and

Internet of Things have led to a massive volumes of data, commonly referred as Big Data. It

includes structured, semi‐structured and unstructured real time data, constituting of data

warehouse, OLAP, ETL and information. Business firms and academicians have designed unique

ways of tapping value from Big Data. There is great scope of using these large datasets as an

additional input to Decision Support Systems in strategic, tactical and operational domains. The

aim of the paper is to explore the role of Big Data in these areas for making better decisions.

Here we explore, how Big Data can be used to make smart and real‐time decisions for

improving business results in the areas of time, cost, and quality and customer service.

Methodology: The paper undergoes literature review and secondary data to provide a

conceptual overview of potential opportunities of Big Data in decision making.

Findings: The paper discusses the concept of Big Data, its role in decision making and also the

competitive advantage of Big Data for different firms. The paper also discusses a framework for

managing data in decision making.

Originality: The topic must be addressed for taking better decisions for firms which will

contribute to high quality knowledge.

18. Service Quality in Selected Hospitals in Indore City: An Empirical Study

Minal Uprety, Sonam Mathur and Sarfaraz Ansari.

In today’s ever increasing competitive scenario, as all the sectors are focusing more on service

quality, health care sector is among one of them. In the proposed research paper, an attempt is

made to identify the service quality factors and analyze patients’ perceptions and expectations

towards these identified service quality factors. The paper has targeted 3 major hospitals of

Indore city; the total sample size is 150 which comprised 50 patients from each hospital, who

visited these hospitals during the period February 2016 to April 2016. Till date, duly filled

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questionnaires were collected from 96 respondents. SERVQUAL instrument will be used to

measure the service quality. The SERVQUAL questionnaire included an expectations and

perceptions section, each consisting of 34 statements. In addition, the questionnaire contained

an extra section relating to demographics of the respondents and an overall question on the

impression of quality of the service provided by the hospitals. It is expected that the service

quality of the hospital is affected by the availability of advance equipment and specialized

doctors, infrastructure, prompt response, hygiene, cost of services, behavior of the hospital

staff etc.

19. Reverse logistics network design and re manufacturing using new module

supplier

Rohit Titiyal.

Purpose: To provide a literature review on reverse logistic and understanding the reverse

logistics barriers in India. Conceptual and mathematical modeling of a reverse logistic network

with consideration of new module supplier for remanufacturing of end of life (EOL) product.

Methodology: This consist two part first is theoretical part and applied part. Theoretical part

gives extensive literature review on reverse logistics and study reverse logistics barriers in India.

Applied part gives the mathematical model formulation with linear programming method after

model formulation in ARENA simulation software. Model checking is done by the numerical

example.

Finding: Cost of reprocessing, remanufacturing, and the cost of new modules can be the driving

factor for the choice of a reverse logistics network. Throughout simulation with different

quantities of returned product, the cost of the new module is seen as an important factor in

network cost Therefore, it might be beneficial for the decision makers to locate reprocessing

center at a location where resources (like labor, energy, and land) are cheaper and to locate

remanufacturing centers at places where new modules of the remanufactured products can be

obtained at a cheaper rate.

Practical Implication: Model can be used for the firm to locate their remanufacturing center,

disposal site and recycling center by which they can minimize their overall transportation cost.

Originality: Consideration of the new module supplier for remanufacturing the end of life

product.

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20. A taboo search heuristic with discrete‐event simulation for scheduling

staff in call centers

Ajith Kumar.

Purpose: this study pertains to staff scheduling in a call center. This extended abstract describes

an ongoing work‐in‐progress.

Voice‐response call centers have been used for long to support business operations in large as

well as small organizations. A call center essentially consists of a team of service agents (SA)

trained to respond to customers. Typically, the arrival of calls to the call center is non‐

stationary: the number of arrivals per unit time changes with time of the day and day of the

week and can at best be described stochastically. Such an arrival phenomenon generates, to

the call center, what is termed as flexible demand by Ernst et al. (2004).

Callers interact with the SAs in the call center in real‐time. If a customer is made to wait too

long, she may abandon the call and may or may not call again. Thus, customer time spent

waiting in the queue is an important performance parameter for a call center in its effort to

satisfy customers. Typically, a company’s contracts with its client result in service level

constraints (SLA) that dictate the time the company can take to process a call and give a

satisfactory response to the customer. The SLAs are crucial among the call center’s

performance criteria. Robbins and Harrison (2010) noted that there are multiple types of SLAs,

but the most common one specifies a minimum proportion of calls that must be answered

within a specified time. For example, an 80/120 SLA specifies that at least 80% of the calls must

be answered within 120 seconds. The challenge, then, is to staff the team with as many SAs as

possible that can ensure meeting all SLAs. Having more staff than this, would lower staff

utilization and unnecessarily increase employment expenditure, while having less would

increase the risk of violating one or more SLAs. Further, direct labor costs often account for 60–

80% of the total operating budget of a call center (Aksin et al., 2007; Gans et al., 2003). Thus,

hiring the correct number of staff and scheduling them optimally is of paramount importance

to the success of a call center.

The roots of call center scheduling research can be traced back to an era when call centers did

not exist in their current form, but firms offered telephone‐based services. Examples of this

work include Molina (1927), Clos and Wilkinson (1952), Church (1973) and Segal (1974). Early

traces of research that is more directly related to the current study are evident in Agnihotri and

Taylor (1991), Brigandi et al. (1994) and Andrews and Cunningham (1995).

Design/methodology/approach: The traditional approach to formulating and solving the call

center scheduling problem has two separate stages that are carried out one after the other

(Mehrotra, 1997). The first stage involves dividing the scheduling horizon that could be a day or

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week, into small time periods of 15 to 30 minutes each, then computing (or forecasting from

past data) the average call arrival rate in each period, and finally determining the minimum

staffing level in each period to ensure that specified service levels are met. The problem

addressed in this stage is also called the ‘staffing problem’. The staffing levels in different

periods obtained as the solution to the staffing problem is the input to the second stage, which

addresses what is called the ‘scheduling problem’. There, an integer program is formulated with

the staffing levels as right hand sides of constraints, and solved to minimize an objective cost

function. The solution to the scheduling problem yields both the minimum total staff size and

the number of employees that must be assigned to each roster line. Taken together, the

staffing problem and the scheduling problem constitute the complete call center scheduling

problem.

Research over the years has incorporated and addressed multiple considerations of real‐life call

center operations into the problem’s formulation. Four most commonly seen in the literature

are

a) breaks within shifts (Henderson and Mason, 1998; Atlason et al., 2004; Bhulai et al., 2008;

Avramidis et al., 2010),

b) differing priorities between calls (e.g. Sze, 1984; Harris et al., 1987; Chen and Henderson,

2001),

c) abandonment or reneging of calls by callers (e.g. Atlason et al., 2004; Avramidis et al., 2010),

and

d) multiple skill groups among service agents (e.g. Cezik and L’Ecuyer, 2008; Avramidis et al.,

2010).

Interestingly, no study could be found that has addressed all these four considerations in the

same formulation. The current study attempts to fill this gap. Further, while almost all studies

only consider the cost of staff wages, the current study also includes the costs of waiting and

abandonment in the model’s minimization objective. These latter two costs are intangible as

they arise out of customer frustration with the voice response service, but clearly, they are very

relevant as they play an important role in the customer’s satisfaction with the service. With the

exception of Nah and Kim (2013), no study could be found that has included both these costs.

Speaking of solution approaches, two distinct modeling methodologies are seen to the staffing

problem: simulation‐based (e.g. Mehrotra and Fama, 2003, Atlason et al., 2004; 2008) and

analytic queuing theory based (e.g. Koole and Mandelbaum, 2002). Analytic queuing models

confer greater computational efficiency and are preferred when it can be reasonably assumed

that the system reaches a steady state quickly, within each time period. However, the steady‐

state assumption may not hold in many real‐life situations. Further, owing to the copious

nature of arrivals, the optimal staffing in one period depends upon the staffing levels of other

periods (Green et al., 2003). Finally, the service level function, which is most commonly

specified as the proportion of customers that must be served with a given time, cannot be

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algebraically expressed. Here, simulation has also been viewed as a useful methodology that

can provide both the flexibility to accommodate the dependencies between staffing in different

periods and an ability to assess a service level function that cannot be algebraically expressed.

The current study explores a solution approach that aims to combine the strengths evident in

the approaches of earlier researchers. It is developing and accessing variations of a Tabu search

heuristic that invokes discrete‐event simulation as a sub‐procedure to assess the satisfaction of

SLAs in the problem. Analyses currently being conducted explore various designs.

Originality/value: The intended contributions of the study are a) the formulation of an integer

non‐linear program to represent the call center staff optimization problem and b) the

development of a Tabu Search heuristic that uses discrete‐event simulation as a sub‐procedure

to solve the problem.

21. ISM Based modeling of supply chain management enablers

Dr. Vivek Agrawal, Professor Anand Mohan Agrawal and Sucheta Agarwal.

Purpose: In this increasing competitive and dynamic environment, supply chain management is

helping the organizations to meet the challenges (Sharma and Bhat, 2014; Sundram et al.,

2011). Supply chain management includes all those facilities and functions, which are

necessarily required during the transformation phase of goods and services from its initial stage

to end‐user stage (Chopra and Meindl, 2007). It aims to amalgamate the different processes

and structures of supply chain, flow of information to customers, and flow of services and

goods. The organization has taken the initiatives for implementing the supply chain

management and its related functions and practices to survive in this competitive era (Varma et

al., 2006). In future, competition among the organizations will revolve around the supply chain

development. It can be developed by strengthen the supply chain network or by adding other

values.

For this, the purpose of the paper is to identify the enablers of supply chain management and

establish the relationship among these enablers by using interpretive structural modeling. In

addition to this MICMAC analysis is used to find out the driving and dependence power of the

enablers.

Design/ Methodology: For examining the enablers, an extensive literature review was carried

out and prepared the list of enablers of supply chain. This list was circulated to the 12 experts

from the industry to identify the important supply chain enablers. By this exercise 11 important

enablers of supply chain management was identified: operational performance (1), employee

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empowerment and motivation (2), employee education and training (3), trust among supply

chain partners (4), supply chain collaboration (5), support by top management (6), financial

resources (7), strategic association (8) just in time (9), green supply chain management (10),

and customer satisfaction (11).

Interpretive Structural Modeling (ISM) is used for establishing the relationship among the

supply chain management. In ISM, a set of interrelated elements are structured into a

comprehensive systematic model (Warfield, 1974; Sage, 1977). It helps in identifying the

interrelationship among the variables. In the present research ISM was used to develop a

framework for the variables affecting supply chain management enablers to show the

interrelationship of the different enablers. Various steps involved in ISM are as follows:

• Identification of relevant variables of supply chain management enablers

• Establishing the contextual relationship among the identified variables

• Develop and prepare a structural self‐interaction matrix (SSIM)

• Preparation of Reachability matrix

• Level identification from reachability matrix

• Constructing the ISM model

Self structural interaction matrix was developed by taking the experts views, based on based on

brain storming and nominal group technique etc. In the present research experts from the

academia and industry were approached for identifying the contextual relationships among the

variables of enablers of supply chain management. Four symbols were asked to show the

direction of relationships between the variables (i, j).

V = variable i will help to achieve variable j

A = variable j will be achieved by variable i

X = variables will help achieve each other and

O = variables are unrelated

If the (i, j) entry in the SSIM is V, then the (i, j) entry in the reachability matrix becomes 1 and

the (j, i) entry becomes 0.

If the (i, j) entry in the SSIM is A, then the (i, j) entry in the reachability matrix becomes 0 and


If the (i, j) entry in the SSIM is X, then the (i, j) entry in the reachability matrix becomes 1 and


If the (i, j) entry in the SSIM is O, then the (i, j) entry in the reachability matrix becomes 0 and


The reachability and antecedents set for each variables are obtained from the final reachability

matrix. The antecedents and reachability variables consists of the variables itself and the other

variable which it will help to achieve. With the help of reachability sets and antecedent sets,

intersection set were identified and hence level of variables were identified in different

iteration.

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Findings: The present study has finally investigated the 11 important supply chain management

enablers and integrated model was prepared using interpretive structural modeling. Further

MICMAC analysis is used to identify the driving and dependence power of supply chain

management enablers.

Research implications/ limitations: Expert opinion was taken to identify the key enablers of

supply chain management and to build relationship among them using interpretive structural

modeling. It is totally based on subjective decision/opinion of experts, so biasness might be

possible by the experts in giving their opinions which affect the result. So, validity of the model

obtained by using interpretive structural modeling is required. This can be tested by using

empirical methods like structural equation modeling.

Practical implications: This study is important for academicians as well as practitioners also. The

practitioners need to focus on all these enablers during implementing the supply chain

management to increase the performance of organization and customer satisfaction. The

future scholars need to emphasize on the combination of qualitative and quantitative studies in

this context to validate the data.

Originality/value: This study has theoretically and practically contributes by identification of

important enablers of supply chain management and develop relational model using

interpretive structural modeling followed by MICMAC analysis to identify the driving and

dependence powers to identify and classify the supply chain enablers.

22. Price and credit period sensitive competitive supply chain model

Brojeswar Pal.

This study considers a two echelon competitive supply chain consisting two rivaling retailers

and one common supplier with trade credit policy. The retailers hope that they can enhance

their market demand by offering credit period to the customers and the supplier also offers

credit period to the retailers. We assume that the market demand of the products of the one

retailer not only depends on its own market price and offering credit period to the customers,

but also on the market price and offering credit period of the other retailer. The supplier

supplies the product with the common wholesale price and offers the same credit period to the

retailers. We study the model under centralize (integrated) case and decentralize (Vertical

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Nash) case and compare them numerically. Finally, we investigate the model by the collective

numerical data.

23. Ergonomics Enhancing Agricultural Systems Productivity

Ashok Matani.

Agriculture plays an important role in developing countries which are mainly located in tropical

regions. Agriculture is an industry with tremendous opportunities for the application of

ergonomics principles. Working conditions are extremely difficult due to severe environmental

conditions, long working hours, strenuous work and the use of mobile equipment. The

ignorance of the majority of ergonomics principles in the design of agricultural equipment

makes the conditions more difficult.

A vast majority of the world's workers are employed in agricultural activities and are exposed to

a wide variety of hazards. Since agriculture is primarily decentralized activity, it is often difficult

to set and implement work safety norms and standards. While standards can be set for

equipment manufactured in large factories, it is not easy to monitor its condition in use. For

equipment fabricated in small workshops or by the farmers themselves, it becomes very

difficult to ensure that design standards are adhered to especially when the users of equipment

are hired laborers on daily wages.

This paper discusses impact of effective ergonomics in enhancing productivity of agricultural

systems in various parts of the world.

24. Application of TQM in Resolving E‐Commerce Challenges in Rural

Markets

Vandana Sonwaney and Sunny Oswal.

Background/Objectives: E‐Commerce industry is going through a plethora of issues today that

includes logistics challenges, rural penetration and many others. This paper addresses these

issues.

Methods/Statistical analysis: Literature Review has been identified as the strategy that

summarizes existing research and helps collate various bodies of knowledge into a meaningful

theory. This theory has been embedded together to form the theoretical model. Also expert

opinion has been used to come up with recommendations.

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Findings: The expert opinion has been instrumental to come up with the solutions. The

solutions based on the lines of TQM are imperative to address the issues faced by the e‐

commerce in rural markets. The paper talks about how these findings will help in generalizing

the solution for the e‐commerce industry.

Applications/Improvements: This paper will be especially useful to online marketers, e‐

commerce companies and logistics outsourcing firms operating in rural markets.

25. Mobile Computing, Cloud & Internet of Things in SCM

Nischay Shetiya and Omkar Chandragiri.

INTERNET OF THINGS IN SCM

With the recent developments in technology like ‘Internet of Things’ (IOT) all physical objects

can be made a virtual computer, which can transmit data real‐time. In a way, every object that

you can think about can be connected to the internet and used in unimaginable ways. Let us

take examples of simple day‐to‐day objects.

Shoes ‐ designed to cushion the foot while walking or running.

Street Lights ‐ designed to throw light and illuminate the streets.

Forklifts ‐ designed to move heavy loads from one place to another.

Not so long ago, these items were just used as per their definition. But recent advances in

technology have made manufactures think about the wide variety of options that can be

explored just by inserting a sensor in these objects. Vast amount of information emerge when

these physical objects transform into a computer. This information gives new insights and

business value to the manufacturers along with added value to the consumer.

When connected:

Shoes ‐ can give details about footfalls, distance covered, speed, force of foot with which it

strikes the ground etc.

Street Lights ‐ can give details of cars travelled in the day, traffic, route planning etc.

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Forklifts ‐ can give details of efficiency, maintenance due‐date, fuel consumption etc.

Even though the amount of information that these objects can provide is enormous, we are still

only at the beginning of the revolution that IOT can bring about. Less than 1 percent of the

physical objects are connected to the Internet so far. To provide a number, less than 15 billion

physical items (including computers, smart phones, electronics etc.) are connected to the

Internet till today and there are roughly more than 1.5 Trillion items on earth!

IOT in Supply Chains

IOT promises to provide far‐reaching benefits to logistics companies and their customers

through connecting physical objects as described above. The benefits extend across the value

chain of logistics, which includes fleet management, warehousing, safety, customer experience,

last mile delivery etc. Through IOT, the seemingly difficult operational problems can be solved

with new ways and ideas.

But the question is whether IOT has been used before in Supply Chain?

Many technologies have been used by logistics companies since many years and IOT is not an

exception. Logistics Industries have been pioneer adopters of IOT technologies from

introduction of bar‐code scanners for inventory management to sensors that monitor shipment

integrity. The following are some examples of IOT being used in SCM.

Traffic and Fleet Management

Sensors placed in the fleet help logistics companies monitor the efficiencies of their vehicles

and also help their customers track their shipments. IOT can also be used for preventive

maintenance of vehicles, alerts in case of any unusual activities while transportation etc.

Production and Manufacturing Shop Floor

Applications that are sensor based have been used in manufacturing companies for a very long

time. These sensors enable the engineers and managers to assess the performance of the

machines along with ambient conditions, wastages, energy consumption, status of production,

flow of materials etc. Along with these KPIs, the sensors also provide information on machine

health which can be used for preventive maintenance and avoid downtime. The Overall

Equipment Efficiency thus is improved through the use of technology.

Warehousing Operations

Warehouses, which were primarily used as a hub for flow of goods through supply chains, are

increasingly becoming more important in today’s business scenario mainly because they serve

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as a key feature for any company to gain competitive advantage by serving their customers in a

fast, cost‐effective and flexible way. This is an extremely challenging task considering thousands

of different types and forms of goods being stored in an average warehouse. Every inch of the

warehouse should be optimally utilized and it should be ensured that the desired goods are

retrieved, processed and delivered as soon as possible with zero error. This is where technology

comes into picture. From storage to delivery, warehouses today contain these ‘objects’ that are

connected to the internet which facilitate error free operations. Low‐cost and miniscule

identification tags like RFID are used in the modern warehouses for better management.

Sensors combined with radars and cameras allow forklifts in modern warehouses to

communicate with each other and scan for goods throughout the warehouse. Automatic

Guided Vehicles are used for picking goods as well. Some sensors are also used to effectively

use lights in the warehouse to save on energy consumption whereas some sensors detect

unusual activities and alarm against thefts and accidents.

Last‐mile Delivery

recent technologies have enabled logistics companies to help with their last mile deliveries. This

is done through use of boxes outside pickup points which signals only when there are goods to

be picked up. If the boxes are empty, there is no signal and hence route optimizations can be

done for the deliveries and pick‐ups.

Mobility in SCM

The objective of using a mobile handheld device is to facilitate tracking, communication, and

process execution. This would enhance productivity.

Mobile applications allow companies to improve customer service activities, manage

compliance requirements, assess inventory levels and provide information to other managers in

real time. In addition, the mobile apps update in real time, facilitating quick decisions to adjust

supply chain operations to meet industry and client demands

Supply chain and logistics professionals rely on smart phones to access the enterprise

applications such as enterprise resource planning, transportation management systems and

warehouse management systems to track shipments and assets and access reports that are

stored on the cloud to mine useful information to make better business decisions.

Mobile devices can provide supply chain professionals and field sales personnel’s with the same

outside office access.

• Order and Shipment status visibility

• On board computers in the Transport vehicle to capture proof of delivery, calculating driver

hours and keeping track of the vehicles.

• Real‐time automated vehicle locating

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• Capture real‐time traffic information and suggest alternate routes to avoid delays

• Projecting Actual arrival time of the shipment to the end customer

• Stock‐out validation and point of sale (POS) visibility via Android, Windows Mobile 7 and

Apple iPhone and iPad devices.

• Voice recognition software that can enable forklift operators and warehouse professionals to

‘voice‐pick’ has helped the workers operating in high‐volume; high‐repetition environments

carry out their tasks in an efficient manner.

Mobile RFID devices and bar‐code scanners are gaining importance to keep a tab on the

transportation assets and high‐value equipment.

26. An Examination of Supply Chain Performance Factors based on the

Quality of Relationships

Rajeev Sharma and Gaurav Tripathi.

Purpose

With the growing importance of focus on relationships in business the days for transactional

style of doing business are numbered. This is not only true for situations when the offerings are

transferred to the final consumer through a retail channel but also equally important for

business‐to‐business dealings. In fact the importance of relationship is at the top for all the

actors (or members) of supply chain (SC) who are interested in serious business. In the context

of relationships among the actors of SC the quality of relationship model has gain a lot of

attention among the researchers. The importance of RQ is due to its ability to assess the

relationship strength which adds to competitive advantage (Hennig‐Thurau et al., 2002; Wong

et al., 2007). In fact RQ describes depth and climate of relationship (Johnson, 1999) while

Crosby et al (1990) and Bejou et al (1996) affirmed that it is a prerequisite for building

relationships for long term.

Therefore, the present research work aims at examining the relationship among the key entities

in a supply chain setup. The entities in a supply chain system are medium or large sized

businesses among themselves which work in cohesion to achieve a common goal. A well‐tuned

relationship among at all the levels will help in achieving customer satisfaction. However, the

supply chain management system is full of inefficiencies due to lack of integration among the

entities. The present research work investigates how the intangible relationships work among

the various supply chain players with a focus on the elusive factors contributing towards the

quality of relationships. The quality of relationship embedded in these factors have an impact

on the business performance which is worthy of investigation.

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Review of Literature

Relationships in business are of utmost importance especially in Indian context. The quality of

relationship is an indicator of the strength of its relationship. It is discussed widely in context of

relationship in case of business to customer and business to business however the consensus

pertaining to the dimensions of quality of relationship has not been achieved. However, it is

interesting to note many researchers have pondered on a conventional definition of quality of

relationship pondering on its constructs (Athanasopoulou, 2009; Qin et al., 2009). This has also

led to difference in conceptualizing the overall quality model in various cases. The lack of

consensus is also dedicated to the insufficiency quality research works which encompass critical

discussion of the model including its dimensions (Hennig‐Thurau, 2000). Hennig‐Thurau (2000)

also pointed out that most of these quality dimensions have been defined on the basis of

intuition and hence causes lack of consensus about the dimensions of the model.

Various studies have focused on exploring the dimensions of quality of relationship in the

context of business to business settings which are definitely in line with the relationships

pertaining to the various entities in the supply chain systems. In other words, due to business to

business context of supply chain management systems these dimensions can be referred for

each other.

Since, there is no agreement on the dimensions of the quality of relationship in the context of

supply chain systems and business to business setting an exploration of literature suggests

three key dimensions. These are trust (Kumar et al, 1995; Dorsch et al., 1998; Walter et al.,

2003; Fynes et al., 2005; Rauyruen and Miller., 2007; Kühne et al., 2013; Razavi et al., 2016),

commitment (Kumar et al., 1995; Dorsch et al., 1998; Walter et al., 2003, Fynes et al., 2005;

Rauyruen and Miller., 2007; Razavi et al., 2016) and satisfaction (Dorsch et al., 1998; Walter et

al., 2003; Rauyruen and Miller., 2007; Kühne et al. 2013). There are other factors but have

found relatively limited attention in the research works. The three factors are explained in the

following paragraphs.

Trust

According to Hosmer (1995), trust is all about relying upon any accepted responsibility in order

to protect interests of all parties engaged in the process of economic exchange. For supply

chain it is a key element for relationship (Svensson, 2004; Gounaris, 2005). It is understood that

building trust among the partners is important for mitigating the risk involved (Spekman and

Davis, 2004). Trust has been of huge importance in studies involving intra‐firm relationships

(Kingshott and Pecotich, 2007; Morgan and Hunt, 1994)

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Commitment

Commitment encompasses the belief of the players in the supply chain, in the current

relationship, wherein they make their best of the efforts to maintain the terms with other

parties (Morgan and Hunt, 1994). It also includes their willingness to maintain the relationship

(Monczka et al., 1998 and Spekman et al., 1998). This dimension of the quality of relationship is

essential for long term gains. It is noteworthy that the partners are showing willingness towards

focusing on the long term goals at the cost of short term goals (Mentzer et al., 2000). The result

of building long‐term relationships is towards perceived mutual benefits (Morgan and Hunt,

1994). Commitment is an indicator of the level of existence of a relationship in terms of

continuation and break‐down (Wilson and Vlosky, 1998). In addition, Anton et al (2007) said

that reduction in commitment from the supplier influences the relationship between different

parties have a negative impact on the willingness. Any business relationship between two

supply chain entities, which is in continuum needs high degree of commitment to ensure the

achievement of objectives of the supply chain system (Kwon and Suh, 2005). Commitment is

positively and directly related to performance of partnering entities and the whole supply chain

system (Prahinski and Benton, 2004).

Satisfaction

Satisfaction is another key factor which is essential for a strong relationship (Wilson and

Jantrania, 1994). It is strongly connected with the fulfillment of needs and even analogous at

times. (Naude´ and Buttle, 2000). It has strongly linkages with the overall supply chain

performance. Satisfaction can be both economic as well as social which are both involved in

business transactions. Satisfaction from the economic angle is all about the reaction towards

economic benefits of the other players in the chain while satisfaction arising about of social

aspects is mainly about gratification and issues pertaining to the exchange of information (Batt,

2004).

Overall Supply Chain Performance

The overall objective of the supply chain system is to make the system efficient thereby leading

to improved performance. This is strongly present in the literature where in various aspects are

discussed. The supply chain activities when linked with sourcing decisions and manufacturing

goals reflect key supply chain performance indicators viz., cost, quality, dependability and

flexibility (Narasimhan and Jayaram, 1998). These fours aspects are key to supply chain

performance and they can be highly impacted by the strength of the relationship exhibited by

the supply chain players. However, much of the literature on the quality of relationship has

focused on the marketing aspects (Morgan and Hunt, 1994). The impact of quality of

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relationship (in supply chain settings) on the overall supply chain performance has found

limited attention in the extant literature especially in the Indian context. The study closest to

the present work is that of Fynes et al (2005) who have attempted to the test this relationship

however they have composition of quality of relationship is differently envisaged by them.

Hence, research on examining the impact of quality of relationship on supply chain

performance in supply chain settings in India is a gap which strongly needs to be addressed.

Methodology

The present study involves data collection using structured questionnaires through personal

interaction from the supply chain entities. The key objective is to test the impact of quality of

relationship via trust, commitment and satisfaction on the supply chain performance factors.

The scale items are taken from the various studies related to supply chain in different contexts.

The scale items are refined based on the recommendations from the practitioners and

researchers in the field of supply chain and operations. Data collected will be put to advanced

techniques of multivariate analysis. The impact of quality factors (independent constructs) on

supply chain performance (dependent constructs) will be evaluated.

Findings and Implications

The results of analysis will help in understanding the influence of the quality factors.

Specifically, the impact of possible influence of each factor on the supply chain performance

factors will be the resultant. This means that relationship between trust, commitment and

satisfaction (independent constructs) and overall supply chain performance factors viz., quality,

delivery, cost and flexibility (dependent constructs) will be analyzed. The results will have useful

implications for the supply chain managers and the parties involved to focus specific factors of

quality of relationship based on their predefined performance objectives related to supply

chain performance.

Originality Value

The present study provides useful insights into the linkage between quality of relationships and

supply chin performance which have together received limited attention in the extant

literature. The study will be useful for academia and industry based on its ability to highlight a

key area which is deeply rooted in the Indian culture which is based on building and

maintaining lasting relationships.

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27. Moderating the effects of Lean manufacturing: A contextual framework

with respect to process industry

Anand Sasikumar and Padmanav Acharya.

The Lean implementation issues in different production systems are due to the complexities of

the process flow structures. Each production system is unique in comparison with other

systems. The uniqueness in terms of volume and variety are major obstacles in implementing

lean manufacturing concepts. The purpose of this paper is to address the issues in

implementing lean manufacturing principles in process industry. The analysis involved the

studying the research articles published from 2006 to 2016 in selected operations management

journals. The articles are categorized by time distribution of articles, methodology of research,

authorship patterns and implementation status in companies. The present paper tries to

explore how the tools and techniques of lean manufacturing developed for assembly line

production system can be adapted to continuous production system. The findings include the

need for intensification in empirical research, the challenges of adapting and implementing lean

principles in continuous process industry.

28. Logistics Management: Opportunities and Challenges with Reference to

Selected Organizations

Parikshit Kala.

Logistics management has become an integral part of business organizations that are keen to

sell their product worldwide. Even the developing countries are not far behind the race. As far

as Indian Logistics Organizations are concerned they are very curious to pick up and deliver the

Services via using effective modes of Transportation to dispatch the cargo shipments. Trend of

logistics management is very popular in metro cities among Supply chain service providers like

Blue Dart, Gati, Dtdc, Pafex, Concor, etc. Researcher took 150 Sample size from three metro

cities from North India. Intention of this research is to find out the motivating factors of logistics

management. In this study researcher asked several questions relating to logistics products and

efficiency in services. This study would be beneficial for logistics organizations to make

potential strategies regarding logistics management.”

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29. Does magnitude of penalties matter? An empirical investigation in the

healthcare context

Gopalakrishnan Narayanamurthy and Rachna Shah.

Purpose: In general, facilities are inspected by regulatory agencies to check the compliance

status on certain specific pre‐defined standards. On non‐compliance, inspectors decide to

penalize the facility. Based on the scope and severity of the non‐compliance observed,

inspectors impose penalties to threaten and push the facility towards compliance. In this study,

an attempt is made to disentangle the impact of having a penalty and that of the magnitude of

penalty on the future quality of care delivered. Through this attempt, we will be able to

understand the role played by the magnitude of penalty imposed.

Design/methodology/approach: To answer the research question, penalty data of U.S. nursing

homes from 2011‐2014 were empirically analyzed using fixed effects model. Penalties were

binary coded into ‘0’ for those not penalized and ‘1’ for those penalized. Model with these

binary coded variables were run to test the impact of having or not having the penalty on

nursing home’s quality of care. Subsequently, we ran the model only on those nursing homes

which were penalized to capture the impact of the magnitude of penalty. Several other control

variables at state level, zip code level, and nursing home level were included in the model.

Sample, measure and method robustness checks were also performed to reconfirm the results

obtained.

Findings: Results revealed that future quality of care improves on having a penalty, irrespective

of the amount of penalty imposed. Future quality of care was also observed to improve with

increase in magnitude of penalties. But, it was observed that the impact of having a penalty on

future quality of care was much higher than the impact of magnitude of penalty. Analysis also

showed that the magnitude of penalties have an inverted N‐shaped relationship with quality of

care. Different post‐hoc analysis were conducted to draw research and practical implications of

this study.

Originality/value: Based on the literature review conducted, we believe this to be the first

study to understand the impact of a post‐inspection outcome, namely the monetary fines on

future quality of care. This paper is also adding to the minimal literature on inspections in the

context of healthcare. Current study questions the practice of penalization – Is it sufficient to

blacklist the facility as a non‐conforming penalized one with zero penalties or is it essential to

impose them with heavy amount of penalties?

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30. Category Management: Enriching Customers private label purchase

Vilas Nair and Susan Abraham.

The change is driven by much more educated shoppers (thanks to the Internet), which affects

their path to purchase, and increased data complexity as big data continues to evolve the

accelerating trends within the retail and consumer packaged goods have increased the

importance of category‐based thinking and approach, and a requirement for more

collaboration between Retailers and Supplier / Manufacturer partners. Category Management

is a collaborative continuous process between manufacturers and retailers to manage a

shopper need state which we refer to as a ‘category’. The purpose of this process is to optimize

shopper satisfaction and fulfill the role chosen by the retailer for that category within the

overall portfolio of categories in the retail format. The end state of the category management

process is that combination of assortment, price, shelf presentation and promotion which

optimizes the category role over time. Category management is data intensive and analytical in

character. Category management is about understanding data. By contrast, shopper marketing

is more about understanding emotions or motivations. The retail industry is changing, and

retailers are vying for market share in an increasingly competitive environment. Shoppers are

becoming more complex and demanding. Data and technology options are increasing in

complexity with more and more big data. This research studies that category management

practices finds the optimal solution and provides both assortment, customer service, promotion

an important role. The process of category management consists of three phases namely

analysis, implementation and forecasting (KotzaB & Bjerre (2005). Analysis refers to analyze the

collected information regarding to customers, category development, and the retailers

performance in the category. Implementation means to carry out the analysis above in order to

enhance customer satisfaction, increase sales decrease costs. Forecasting represent the

expectation of how categories can be developed and a how customers’ needs can be

determined in the future.

PRIVATE LABEL BRANDS IN INDIA

Organized retailing is spreading and making its presence felt in different parts of the country.

With the entry of very large corporate houses like Reliance Fresh, Vishal, AV Birla group, Bharati

Walmart joint venture and the existing Biz Bazar, Spencer, Food Mart are also in large scale

expansions across the country, the spread of the organized retail is going to reach soon the

small populations towns of 1 lac to 5 lacs after covering all big, medium and small cities.

The trend in grocery retailing, however, has stated with a growth concentration in the South.

Though there were traditional family owned retail chains in South India such as Nilgiri's as early

as 1904, the retail revolution happened with various major business houses foraying into the

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starting of chains of food retail outlets in South India with focus on Chennai, Hyderabad and

Bangalore markets, preliminarily. In the Indian context, a countrywide chain in food retailing

has been pioneered by Big Bazar and Reliance fresh only. A large degree of private label growth

is due to the consolidation and expansion of the retail food industry. Over time, as retail chains

have expanded, they have moved from being price takers to price setters, thereby shifting

power from manufacturers to retailers. The increase in private label products among formats

and across countries has allowed retailers to focus on differing consumer demands around the

world.

It is increasingly evident that private label retailers are constantly expanding product selection

to appeal to the greatest consumer segments. For example, private labels stock keeping units

(SKUs) have increased eleven‐fold globally from 2004 to 2008, finally reaching 9,500 during

2008 to 2009. The expansion of retailers across countries and the increase of private label

products across different store formats are not only increasing sales and volume of private label

products, but are creating new opportunities to launch innovative, healthy and conveniently

packaged products to suit different consumer’s needs. Range in India is narrow across

categories compared with developed markets. A leading hypermarket would have 8,000 to

10,000 SKUs. Consumer companies have traditionally focused on fewer SKUs due to lower

affordability and fragmented retail. In future shoppers will increasingly demand more range of

products and retailers will use this as a source of differentiation. Private labels or store brands

can reduce entry prices and raise margin: high value private‐label manufacturing contract

increase retailers‟ bargaining power with vendors and attract more shoppers owing to lower

prices.

The study demonstrates that sales due to category management practices can be significant.

Finally, we propose adoption of private label as a category. With private label brands retailers

attempt to utilize this measure of exclusivity to differentiate them from the competition. The

results of this study suggest that category management enhance customer satisfaction by

focusing more on product availability, presentation, and customer service rather than price.

Key words Category management, private label, product availability, presentation, SKU, Stock

keeping units and customer service.

31. Assessing Risk by the High Net worth Investors of India in Financial

Decision

Shiba Parhi, Mohammad Khalid Azam and M Venkateshawrlu.

Introduction: Financial Management has been guiding the investors in assessing risk, but study

says there are several anomalies in actual measurement of risk. People of different background

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assess risk differently in different situation. The economist Daniel Kahneman and Tversky

published several papers on the above topic. But looking investors of Indian, a parallel study is

essential explore the variables. High Net worth Individuals are the measure investors in Indian

Business market, so to study their approach and behavior is essential

Objective:

1: To understand the importance of psychology and sentiment while taking financial decision by

the investors in Indian.

2: How do they assess the risk?

Methodology:

To carryout conceptual study to understand the behavior of Indian HNI Investors.

To apply Survey method to explore underneath variables.

Future Scope of the study: The study will help us in understanding the behavior of influential

investor and will guide financial institutions in formulating better financial policies.

32. Application of Behavioral Finance and econometrics to understand the

High Net worth Individuals investors during Uncertainties and Risk in

India

Shiba Parhi.

Introduction: Day by day uncertainties and suddenness are increasing because of political

turmoil and economic uncertainties. Predicting future on the basis of past data on such

situation is challenging. Basically when we are trying to map the behavior of investors in such

situation through econometrics, it is even more challenging, though there are number of

multivariate time series analysis, but need proper analysis.

Objective of study: To forecast the behaviors of HNI investors during economic uncertainties

and risk. Under Behavioral Finance and Econometrics to find out the path to study the HNI

behavior because of the constraint of availability of data.

Research Methodology: To do a conceptual study of the challenges faced by the forecaster in

above situations and to cross verify through econometrics analysis, if possible.

The problem to study HNI is the data, as such because of various rules and regulation and

privacy constraints getting data regarding stock investors and specifically HNI become difficult,

in such situation what a researcher should is a big question mark. Researcher faces problems in

getting basic data relating to pat investments.

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Through different econometrics analysis the data to be forecasted before the stock market

turmoil and to match with the actual data. Here through various study to understand the

limitations of econometrics in predicting future and to find out the corrective measures to be

taken. The evolving state of economic and political situation is to be understood for such

process. Along with the conceptual and econometrics analysis, in depth interviews to be

conducted among the professionals, econometrics expert and statisticians to understand the

perception among the technical forecaster regarding such mathematical tools.

Future Application: Day by day political turmoil are increasing as well as the terrorism, because

of political situations economic conditions are getting affected in term of pricing, consumption

and export and import condition. How HNI investors behaves in such situations in future.

33. Application of Optimizing Techniques in Indian Auto Ancillary Industries

for SCM.

Karan Venkatesh.

Organizations face many challenges in their battle to survive in the current economic climate. A

major challenge facing an organization is the need to change and change rapidly to remain

competitive. This imperative to change can be categorized as a key to survival. A major change

agent in the current economic climate is the optimization of resources and business processes.

Consequently, optimization has become an essential part in the strategy for survival. An

important prerequisite in achieving optimization is the elimination of waste and as a result

adding value to business processes, products and services companywide. Recent research

postulates that to be successful, organizations must implement strategies to boost process

optimization objectives that achieve customer satisfaction and competitiveness. It particularly

focuses on the impact of lean application in terms of speed, flexibility, reliability, quality and

cost in an attempt to create value to survive and attain customer satisfaction.

Manufacturing firms have a huge number of problems and in order to tackle them involves lot

of man power, time and energy. Thus selecting most influencing factor is the biggest hurdle

faced by the industry; which varies from industries to industry, product to product. In this

highly fluctuating market one requires numerous Research methods which are accurate and

dynamic in nature. Also with increasing competitions in industries adds to the complexity of

selection of parameter. The purpose of the project is to identify the most influencing problem

area and optimize the same in Indian Automotive Industry with respect to Supply Chain

Manufacturing (SCM) using Survey method, weighted average, Factor Analysis (Exploratory

type) technique and Kanban Systems. The basic steps of methodology are Survey instrument

development with the help of questionnaire, data collection, data analysis and validation. The

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data analysis approached is by weighted average, and validation through Factor Analysis. Also

use of Kanban systems for Optimizing the Inventory. This research is expected to help

government and private industry in selecting the most influencing problem area and its

optimization. It will also help in establishing the relation between various problem areas to cost

reduction. This increase the prediction accuracy in supply chain thus helping organizations to

draft there strategic plans and policy up gradation.

34. Building the foundation for Supply Chain Costing by identifying and

prioritizing the elements involved using TOPSIS.

Shilpa Parkhi and Gary Cokins.

Purpose:

Supply chain managers recognize that the next frontier in supply chain cost management lies in

portions of supply chain beyond their direct control. These executives have long back

understood that many of their costs and business processes are driven by behavior and

practices of their trading partners. Executives require a much broader view of costs than is

provided by their firm’s cost management systems. Supply chain managers’ needs to improve

their internal cost information and extend their “line of sight” to include their trading partners’

costs, both upstream and downstream. Without this information, supply chain costs cannot be

effectively managed. Many of these costs are driven by business practices of trading partners.

Cost visibility and inter‐firm cost management can reveal new potentially greater opportunities

for cost reduction than can be achieved by a single firm.

Despite the importance of supply chain costs, few executives possess the ability to effectively

manage these costs. They frequently lack cost information regarding the firms’ internal

processes, the activities comprising these processes, or the costs to serve different customers,

marketing channels or supply partners. Executives have less visibility over trading partners’

costs or factors influencing their external costs. Above all, supply chain professionals operate in

a dynamic business environment. The requirements of end user demands and the way

organizations function and interact with trading partners are altered by factors such as

globalization, product / service variety expansion etc. Hence measuring and managing both the

existing and prospective supply chain costs is required to meet the sustaining profitability and

remaining competitive in the increasingly complex environment. Firms still continue to rely on

their traditional inward looking costs systems; some firms have begun to extend their cost

visibility to include the major segments of their external supply chain. These firms have adopted

approaches to encounter similar problems in supply chain. But the techniques and strategies

involved differ based on firms’ position and level of cost knowledge of partners. The framework

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essentially consists of a series of steps recognizing to the costing requirement and challenges

posed by the supply chain.

Design:

Those firms already on their supply chain costing journey have attempted to capture expense

information and calculate costs from end user to the ultimate source of supply. The resulting

cost knowledge allows these professionals to report the magnitude of supply chain costs and

focus on key cost drivers across supply chain. The journey of implementing supply chain costing

consists of five steps. The steps are iterative within the firm and the supply chain.

The process of implementing supply chain costing is shown below:

Step 1: Identifying the elements of cost in Supply Chain

Supply chain costing needs to capture costs in a manner that enables managers to view and

portray costs in many different ways. This step gives careful classification and assignment of

costs. Alternative cost classification permits isolation of costs by product, customer or supply

chain. This step comprises of creating supply chain costs to performance and value creation

through the economic value added or balanced score card model.

Step 2: Prioritization of elements of cost of Supply Chain:

Firm uses a variety of costing method and tools to increase cost visibility and manage internal

and external costs. Hence supply chain encompasses a wide variety of tools and technology.

Most appropriate costing method depends on the management position or the position of firm.

Some costing technique works better than the others in different circumstances. Some work

well in mass production whereas some work well in lean. Hence choosing them is pivotal.

Step 3: Develop a foundation for effective supply chain costing:

First, executives need to have an appropriate foundation in place to support supply chain

costing. Essential elements include a shared vision of SCM and what costing information is

needed to support management decisions. The structure of the cost system should be based on

firm’s strategy, production methods and operating environment. Understanding the factors

affecting the supply chain costs should also be a mechanism in the costing system. The firm’s

position in the supply chain directly influences the supply chain cost and can be managed with

and without sharing the costs with the value chain.

Methodology:

Technique for Order Preference by Similarity to Ideal Solution or TOPSIS was originally

proposed by Hwang and Yoon in 1981. The elements are prioritized on the basis of their

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similarity to ideal solution. The solution that captures cost related information most efficiently

and can establish the strongest link between the cost and supply chain processes is considered

to be the ideal solution. While the solution that that is least efficient in capturing cost related

information and establishes weakest link between cost and supply chain processes is

considered to be the negative or anti‐ideal solution.

Considering the distance of elements from the ideal and anti‐ideal solution, the cost elements

are prioritized. The high priority elements are those that near to the ideal solution and far from

the anti‐ideal solution. The elements near to anti‐ideal solution and far from ideal solution get

low priority. In this way the high priority cost elements are most crucial for the foundation of

supply chain costing. This high priority elements act as building blocks for any model developed

for simulating supply chain cost and its impact on supply chain processes.

Procedure for TOPSIS:‐

1) Develop the multi‐criteria decision matrix.

2) Derive the normalized matrix.

3) Assign weights and formulate the weighted normalized decision matrix.

4) Find the ideal and anti‐ideal solutions.

5) Find the proximity of cost elements to ideal and anti‐ideal solution.

6) Establish the relative distance to ideal and anti‐ideal solution and prioritize the cost

elements.

Findings:

Even though most of the companies have not been able to implement an efficient supply chain

costing process that can provide enhanced, transparent and visible information regarding the

costs incurred throughout the supply chain. Yet, all the companies that participated in the

research felt the need to obtain the cost information regarding all their trading partners

throughout the entire supply chain. The realization of having an effective supply chain costing

system can be attributed to the shifting focus of the supply chain management processes which

calls for analyzing the costs not only from a single firm but also the costs incurred by all trading

partners in delivering the final product or service to the customer. This shift in center of interest

requires an altogether different cost management perspective than what currently exists in

most organizations.

Firms which focused on supply chain costing considered cost knowledge as a competitive

advantage. Thus, cost information has become an integral part of their culture and has been

aiding these firms in managing their operations by providing a cost driven link between their

decision making processes and its impact on firm’s performance. To establish this cost link

throughout the supply chain, cost estimation models can be developed that can capture the

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costing information and establish a relationship between the process changes and total cost of

supply chain. Therefore supply chain costing provides a holistic view of costs incurred

throughout the supply chain.

Originality and Value:

Based on the review of the literature of the elements of the cost of supply chain are identified.

Further to establish the significance and influence of these factors on cost of supply chain

Topsis methodology is used. The prioritized elements can be used as a foundation to develop a

supply chain costing model that can establish cost link throughout the entire supply chain and

simulate the impact these elements of cost and supply chain processes.

35. Military Aircraft LRUs with MRO Supply chain improvement: Self Reliance

in Aircraft MRO business and Sustainability for future

Krishana Kant Shukla, Ravindra Kumar Chauhan, Umashankar Aland and Prakash Joshi.

Hindustan Aeronautics Limited (HAL) Nasik has geared up with MRO business for Airframe & all

system LRUs especially Mechanical LRUs at Nasik base & Electrical, avionics LRUs at its sister

divisions within India. Organization has acquired necessary skill sets & better global practices

for its entire operations & spare management. During execution of SU‐30 MRO establishment

for ROH of Airframe & mechanical LRUs, HAL Nasik has managed global practices for its

Qualitative aerospace operations & spares related issues since inception. The risk involved for

execution of MRO of Su30 MKI aircraft that this activity was not being carried out at OEM base

and HAL is the 1st organization in India as well in the world which is engaged in MRO of

SU30MKI aircraft in‐coordination with its global experts. The entire material planning & supply

chain made sustainable for MRO of Mechanical LRUs for MiG‐21, MiG‐27, Mirage‐2000 & other

variants of military aircrafts. HAL’s business operations management has achieved not only

complete management of spares from different OEMs spread globally but were made

sustainable and supporting to Indian Air force from more than five decades. Now it is necessary

to be self‐reliant in spares management to sustain with MRO business of LRUs & Airframe for

cost effectiveness as private players have entered in this business. Also it’s a need of time to

achieve required pace of production / services at par with customer’s requirements. This paper

shares the best global practices implemented by Hindustan Aeronautics Limited Nasik to make

their MRO business sustainable and competitive in spares supply chain management. Also it

explores the opportunity to acquire the business in similar services for civil airline OEMs.

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36. Redesign of Supply Chain Network of Footwear Manufacturing Company

and impact of GST using Sensitivity Analysis tool

Shilpa Parkhi and Udgar Antani.

Purpose:

The purpose of this paper is to identify the Supply Chain network area of a footwear

manufacturing firm where optimization can be made keeping in mind two Key Performance

Indicators (KPIs): Savings & Service Levels and two Scenarios: Pre GST & Post GST using Dynamic

Sensitivity Analysis method.

Design/Methodology/Approach:

The reader is given analysis of how an optimum network design post Goods & Services Tax

(GST) would vary from an optimum network design in today’s taxation scenario. Post GST

optimal Supply chain network design will be based on logistical benefits and demand

management rather than tax costs. Facility location techniques like Centre of Gravity technique

and Load Distance technique can be used to determine approximate coordinates of the

consolidated Warehouses/RDCs/Depots. Dynamic Sensitivity Analysis method validates the

coordinates of each given location using simulation methods. For propriety reasons, some

information has been disguised and some data have been sanitized.

Findings:

The re‐organized network will in fact be significantly different for footwear manufacturing firm

which can take advantage of Economies of scale in the following manner:

1.Rationalization of Warehouses/ Regional Distribution Centers (RDCs)/ Depots:

o The move towards fewer Warehouses/ RDCs/ Depots would require them to combine, close

and re‐locate.

o The choice of Warehouse/RDC Locations, Depot Locations with respect to the Plants and the

Demand Markets.

o Required capacity of many Warehouses/ RDCs/ Depots will undergo changes and with fewer

numbers, the average sizes will go up.

o Fewer & larger Warehouses/ RDCs/ Depots may make it feasible to route plant production

directly to them rather than through hubs, due to larger throughputs. Thus, the size and

number of hubs could get affected.

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o The linkages between factories‐hubs‐ warehouses/ RDCs/depots ‐customers for various

products will get re‐aligned.

o Consolidation of warehouses/RDCs/Depots would mean a straight saving on warehousing

costs. The inverse root law states that: ‐

Safety Inventory = 1/sqrt (Number of Stocking Points). This means that the safety stock

requirement would also go down.

o Prima‐facie, some of these savings would be offset by the increased cost of freight especially

Secondary Freight.

2. Rationalization in Distribution and Transportation costs:

o State boundaries will no longer be the parameter for deciding routes since the tax rates

across states are envisaged to be uniform. At the same time, with larger

warehouses/RDCs/Depots, transportation lot sizes will automatically increase, making way for

more efficient bigger trucks i.e. use of FTL (Full Truck Load).

o Re‐designing supply chain networks would decrease cost of primary freight since

warehousing/depot locations are likely to be placed closer to manufacturing/import/export

locations. In contrast, this would increase secondary freight due to fewer

warehouses/RDCs/Depots.

o Downtime of vehicles due to trade barriers such as check‐post inspection, filing of entry

permits, compliances under Entry Tax laws and local levies will be eliminated.

The optimization and rationalization that above options can bring about in the supply chains of

a firm on account of GST will provide a competitive advantage to the business through low‐cost

better service and faster turnaround times.

Thus GST offers a great opportunity to revisit your Supply Chain & Distribution strategy, and

identify what is required to become GST ready. Early movers are likely to gain an advantage on

cost and service levels over their competitors and deliver a better value proposition to the

customer.

Research limitations/implications:

Our approach is focused on a footwear manufacturing firm in the Indian context and thereby

limits the ability to generalize the findings. Nevertheless, this study may serve as a significant

starting point for future research.

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Practical limitations/implications:

This paper focuses on Pre GST and Post GST scenarios and the implications of the latter will be:

o The Supply Chain network would be Tax neutral as far as Post GST scenario is evaluated.

o Distribution networks would shift towards the interstate sale model, eliminating the need for

C&FAs (Carrying & Forwarding Agents) and warehouses/RDCs/Depots in each state.

o The efficiency of Supply Chain would fundamentally depend on the minimization of Supply

Chain cost such as Primary Freight, Secondary Freight, CFA charges, Warehouse/RDC Fixed and

Variable Cost, Depot Fixed and Variable Cost etc. while maintaining service levels.

o Design of the Supply Chain such as Hub and Spoke vs. Meshed Design vs. combinations

thereof.

o Choice of Mode of transportation such as Road (9 tonner vs. 15 tonner vs. 20 tonner) and Rail

(Half Rake, Full Rake, 2 Point Rake) for the different linkages of Supply Chain.

o Choice of Inventory and Transportation strategies such as Safety Stock, Reorder cycle, Milk

Runs etc.

o Efficient handling of larger volumes per warehouse would command increased reliance on

automation/ technology applications such as Enterprise Resource Planning (ERP) and

Warehouse Management System (WMS).

o The redesigned network will come with the need for technically qualified and optimally skilled

workforce across the supply chain.

Originality/value:

Our work is perhaps the first on impact of GST on facility relocation and service levels in

emerging economies like India covering actual findings and experiences. It gives new insights to

a streamlined supply chain and distribution network reflecting both theoretical imperatives and

practitioner requirements.

Keywords‐ GST, Redesign of Supply Chain, Footwear Manufacturing, Sensitivity Analysis, Facility

location

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37. Energy efficient reconfigurable architecture for motion estimation in

video coding

Savitha Swaminathan.

Reconfigurable architecture has the ability to dynamically allocate the resources of a

computing device during runtime. This system incorporates some form of hardware

programmability and customizes the hardware periodically in order to execute different

applications using the same hardware. Reconfigurable architecture can be effectively used in

computationally intensive application like media processing. In media processing, video coding

is the computationally intensive part. In video coding, motion estimation is the critical

component as it consumes large amount of computational resources. To overcome this

problem motion estimation is mapped into reconfigurable architecture to effectively manage

the power utilization by dynamic reconfiguration. Determining the motion of objects between

the frames is called Motion Estimation. Dynamically reconfigurable hardware is configured,

based on the input parameters such as battery level of the device, output quality level and the

level of motion in frames of input video. The different configurations are used to reduce the

power dissipation and computational complexity.

Materials used: Altera Quartus v9.0 to design reconfigurable fabric

Methods used: Full search algorithm is used to calculate motion estimation between the

frames. For motion estimation, sum of absolute difference is evaluated by each modules in

reconfigurable fabric. Different sizes of search window is used during motion estimation, to

analyze the power dissipation.

Conclusion: The chrominance subsampling process is considered to study the different

subsampling patterns in YUV video format. Based on that, the YUV 4:2:0 formats is taken as the

input video. The individual frames of the input video are extracted. This is verified using the Hex

Editor tool. The level of motion between the frames for the input video is determined. The

resource utilization for different search window size is analyzed using Altera Quartus 9.0. The

power dissipation is verified by analysing the selecting number of processing elements. The

results concludes that the proper configuration for motion estimation selected during runtime

gives the optimization in terms of power and resource utilization.

38. Lot‐Sizing for Forecasted Demand at Metal Finishing Industry

Pranav Dange, Pranay Daharwal and Pravin Tambe.

Purpose ‐ This paper considers problem associated in lot‐sizing for the procurement of bars for

forecasted demand in metal finishing industry. With the help of the practical case study,

conducted in March‐April 2016 this paper intends to evaluate different lot‐sizing techniques

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and it’s applicability for the forecasted demand to provide a proactive decision making

approach for procurement managers.

Procurement management is the systematic approach used for buying all the goods and

services needed for a company to stay sustainable. Managing your procurement well adds

value to all business practices and save both time and money. Managing procurement in this

world of liberalisation, globalisation and privatization is one of the challenging problems for the

researchers and practitioners. With the help of these techniques the managers will be able to

understand the trend and plan for the resources needed for meeting the demand which will

have substantial effect on the industry performance in its operation and its supply chain.

Design Methodology/ Approach ‐ This paper try to put forward application of following lot‐

sizing techniques 1. Economic Order Quantity (EOQ) 2. Least Unit Cost (LUC) 3. Minimum Cost

Period (MCP) 4.Part Period Balancing (PPB) 5. Period Order Quantity (POQ) in determination of

total inventory cost.

These techniques are used because lot‐sizing has its far reaching effects on productivity of the

industry and cost associated with procurement. Lot‐sizing concerns with quantity to be

procured and time of procurement. Proper lot‐sizing helps in reducing cost of procurement

while meeting the demand on time. It results in optimization of procurement cost which

includes ordering cost and carrying or holding cost of raw materials. It helps in improving

productivity by optimizing input resources and reducing capital investments. Lot‐sizing is a

technique in the area of operations management which is concerned with determination of

quantity and timing of procurement in a firm to have optimum (minimum) total cost (ordering

and carrying cost) of procurement to satisfy forecasted demand.

Practical implications ‐ The industry had established its operations in the year 1997 which

consists of the range comprising the finest Carbon Steel Product and Bright Bars which has a

high demand in the market. Finishing of this product is done in compliance with the set of

industry norms and guidelines, utilizing the finest raw materials and modern machines. It has to

first pass through the Centre‐less grinding machine in which its diameter is reduced by 0.5 mm

which is followed by dipping bars in acid treatment tanks for improving the electrical

conductivity and load bearing capacity. While procuring the material the industry have been

facing high inventory and procurement cost which is leading to vague decision making of

material requirements planning. This paper investigates the problems by forecasting demand

using quantitative method of forecasting and applications of different lot‐sizing techniques for

meeting the forecasted demand for optimizing total ordering and inventory carrying cost also, it

can be useful for capacity planning of the industry.

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Findings ‐ The industry has order round the year and to meet this order, they have to procure

raw materials round the year. Currently, they have lot for lot type of lot‐sizing system which

involves very high ordering and carrying cost with huge capital investment. In this lot for lot

type of lot sizing a separate planned order release is placed for each periods projected

requirements by taking the lead time into consideration. This kind of practice leads to excessive

ordering cost if the cost per order is highly significant when compared to the carrying cost per

tonne per month. If the product is finished within the industry then the associated cost for

setting up the finishing system facilities is called as setup cost. But in this case it is brought from

the vendor then it is called as ordering cost. Hence, at the time of making planned order

release, it is made by considering the relative difference between the ordering cost per order,

and carrying cost per tonne per month, it may result in minimum total inventory cost thus this

paper uses this approach to be followed for minimizing the total inventory cost from the

available alternative methods to determine the lot size (order size) in the optimum (minimum)

cost using the best available resources. Demonstration of each lot sizing method is meticulously

calculated and for each method MRP (Material Requirement Planning) is done for determining

the planned order release and stock on hand for the forecasted demand (Projected

Requirement).

The outputs from individual calculations of each method for total inventory cost are shown in

the table given below:

Technique Total Ordering cost Total Carrying cost Total cost

Economic Ordering Quantity 135000 101700 236700

Period Order Quantity 180000 0 180000

Part Period Balancing 120000 49000 169650

Minimum Cost per Period 120000 49000 169650

Least Unit Cost 105000 93750 198750

From the calculations it is clearly manifested that the optimum method of Lot Sizing (Part

Period Balancing or Minimum Cost per Period) should be selected for the procurement of the

raw materials for which the total inventory cost involved is minimum. So in a nutshell this

papers finds the optimum total cost for the appropriate order quantity by implementing

different techniques of lot sizing and also when the planned order to be released. Thus, for an

industry having huge difference in inventory carrying and ordering cost Part Period Balancing or

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Minimum Cost per Period Method of lot‐sizing should be used for calculating Lot‐Size which can

be further used for Capacity Planning.

39. Vendor Rating & Inventory Management in an Indian Start‐up: A

combined AHP‐TOPSIS approach

Nishant D. Singh, Rohit Singh, Chetan Saxena and Naman Singh.

Fracktal Works is a Bangalore based start‐up which is unique in its own way; Fracktal Works

though known for its 3‐D printers specializes in product development. And during 3 years of its

existence has worked on product development for firms like L’Oreal Cisco, Toshiba, L&T, etc.

Designing an inventory management model for Fracktal was an interesting experience for SIOM

as they are in a growing phase and are constantly adding products to their catalogue. The

growth is not only limited to the volume of the existing products but also to the product mix

itself. SIOM had to be extremely careful that any system designed should be robust enough that

it can withstand the future growth that the firm is aiming.

Rating the suppliers/vendors using Analytical Hierarchical Process involved enabled us to have a

closer understanding of the factors that are essential for effective purchasing. Vendor rating is a

result of a formal vendor evaluation process, while the purchase department at Fracktal Works

does evaluates its vendors, a more formal system was needed which incorporates the

company’s evaluation and rating criterions, ranging from quality, delivery to the scalability

Developing a Vendor Rating system is a complex problem right from the selection of the criteria

to be considered to the method used to analyze various suppliers on the basis of the selected

criteria. Many researchers have focused on the vendor selection problem and have come up

with various criteria on which a vendor can be evaluated.

G. W. Dickson in 1966 studied supplier selection system and decision, and came up with twenty

three supplier criteria that should be considered in vendor evaluation, like quality, delivery,

price, performance history and others. Research compared the works of Weber, Current and

Benton (1991) and the 23 criteria of Dickson (1966) and concluded that price, quality, and

delivery are the most important vendor selection criteria. Ellram (2002) came up with the idea

of including management opinion as the criteria in supplier selection.

The Vendor Rating includes various intangibles like customer service along with different

tangibles like Quality and Delivery. There are various quantitative and qualitative criteria

involved in order to make multi‐objective decisions for vendor evaluation. To address this

problem statement, Thomas L. Saaty’s (1980) AHP can be used as it uses both qualitative and

quantitative criteria in order to make decisions. Analytical Hierarchical Process is a decision

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making method that assigns priorities to alternatives when multiple criteria are to be

considered and thus allows the decision maker to create hierarchical structure for complex

problems.

As the criteria were impacting the vendor rating both positively and negatively so TOPSIS is

used along with AHP. There have been a lot of researchers who have used AHP along with

TOPSIS for solving Multi criteria decision making problem.

Jadidi et al. (2010) used a TOPSIS based model for multi criteria decision making supplier

selection problem. Vimal et al. (2012) also used TOPSIS method in order to develop an

approach for a manufacturing company for selecting a competent supplier.

Need or justification of the paper

Although the purchase department of the company purchases goods, raw materials,

equipment’s, spares, intermediary products, office items etc. for all its divisions and

departments. The operations department is responsible in determining what to buy, how much

to buy and where to buy from. But the company had no rating system in order to evaluate and

rate its vendors based on their performance.

The objective of this paper is to develop a vendor evaluation and rating system that

incorporates the opinions of the company experts in determining the evaluation and rating

criterions, and then to rate their present vendors on the basis of these criteria.

The vendor rating is needed in order to improve the quality and reliability of the suppliers. It

helps the purchase department to cultivate the good sources that help it to meet its current

and future needs. It helps the company to identify the suppliers who offer best value for the

money spent.

A good vendor rating system protects the purchase department from the charge of bias from

their colleagues and other suppliers, as the department is able to rate the performance of each

supplier based on their entire performance.

It acts as a feedback to suppliers to improve performance and helps the purchase department

to recognize and reward outstanding performers, and can be used to allocate business share

among number of suppliers.

Also objective decisions can be made to disqualify and black list poorly performing suppliers

based on their rating. Also the ratings obtained by the top performers can be used as a

benchmark for others.

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Apart from the vendor rating system the paper will also mention the inventory management

system that was created in order to track the flow and status of inventory. As a part of this

project we devised a nomenclature system for all the inventory items and created an excel

workbook which keeps a record of all the inventory present, daily purchases and issues,

pending orders and helps the purchase department to identify the shortages and address them

in a timely fashion.

Research Methodology

Vendor rating

The main objectives of this paper are to identify all the supplier evaluation criteria that are

considered as of importance by the experts. Based on the literature review of the supplier

selection criteria ten criteria were identified for vendor evaluation and a questionnaire was

prepared.

This form was then distributed to seven experts and they were asked to score the ten criteria,

based on the score three out the ten criteria were eliminated and we were left with seven

criteria in order to rate the vendors.

Further process can be divided into two sections, first section involve carrying out AHP in order

to assign weights to the seven criteria while the second section will involve assigning ranks to

the vendors using TOPSIS.

Inventory management

As a part of this project, an inventory management system was created in order to track the

flow and status of inventory. We devised a nomenclature system for all the inventory items and

created an excel workbook which keeps a record of all the inventory present, daily purchases

and issues, pending orders and helps the purchase department to identify the shortages and

address them in a timely fashion.

For the purpose of nomenclature, the final product was divided into sub‐assemblies and codes

were given to different sub‐assemblies.

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40. Demand forecasting, Economic Order Quantity and Reorder point

calculation of a hypothetical company producing solar panels

Rishabh Dua, Tanusha Sharma, Kartik Gupta and Puneet Bhatia.

Correct forecasting has become a need for survival in today’s business world. Not only

production unit but correct forecasting is required at every stage of product development. It is

a foundation upon which the all company plan and objectives are built in terms of market and

revenue. Thus forecasting is method to use past experience and estimate the future. It can be

used for sales forecasting, demand forecasting and technology forecasting. Demand forecasting

is a principal tool for production planning. It is an initial phase of production planning in which

quantity of product required in the future is estimated and accordingly the production schedule

and is prepared. There are different methods of demand forecasting namely qualitative and

quantitative methods. To forecast for products for which there is no historical data or products

that are to be newly launched in the market, qualitative technique is used. It uses judgment of

sales and marketing experts, distributors, executives etc who are knowledgeable in this field.

Various methods for qualitative forecasting are Delphi method, survey of sales force and expert

evaluation. While, qualitative techniques give a narrow range of forecasts, quantitative

techniques such as naïve method, moving average method, exponential smoothening method,

linear regression method etc give a single forecast. Moving average method uses the average

value of the actual weights to calculate the forecasts. Although these methods are famous for

their simplicity, they can forecast up to only one period in the future. Thus, exponential

smoothening and regression methods are most common used since they are the most cost

effective statistical tools. In our paper we would be working on these methods to calculate the

forecast for future. Correct forecasting helps save wastage in materials, man hours, machine

idle time etc. which leads to increased efficiency and productivity.

The dataset selected is that of Solar Panel which under general consensus states the rising

demand of solar panels signifies the rising acceptance of using solar energy as a viable

alternative energy source. Solar Panel refers to a panel designed to absorb the sun's rays which

is an ultimate source of energy for generating electricity or heat. The factor that has hampered

the production of solar panels is the high installation and starting cost but as the acceptance of

solar panels rises the cost of setting up solar panels has been seen to be decreasing. From the

past demand curves, as stated by Swanson's law which states that with every doubling of

production of panels, there has been a 20 percent reduction in the cost of panels.

This project aims analyze a data set of demand of solar panels using the language R and carry

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out exponential smoothing, moving averages and linear regression model to forecast the

demand for solar panels in the subsequent years.

In order to compare the forecasting techniques the errors generated would be studied

signifying the more suited model to predict for that specific dataset.

The sales data set will be derived from the annual report of Trina Solar. Trina Solar’s PV

modules are sold in over 30 countries, bringing clean, reliable solar energy to residential,

commercial, industrial, and utility applications, on‐grid or off‐grid, around the world.

The sales data of a hypothetical company will be calculated assuming the production takes

place in a single plant in each country and capacity of a single PV module (Solar Panel) is 220W.

Using this actual demand, demand forecasts of PV modules will be calculated using moving

average, linear regression and exponential smoothening methods and respective errors will be

calculated. A suitable forecasting method will be selected and the forecasted demand will be

used to calculate Economic Order Quantity of Inventory and reorder point.

The demand forecasts form a key input to the economic appraisal. As such any errors present

within the demand forecasts will undermine the reliability of the economic appraisal.

Moreover, incorrect forecasts could create several problems such as over or under production,

wastage etc, in the organization as forecasting forms a key input to the planning function. While

forecasts are never perfect, they are necessary to prepare for actual demand. In order to

maintain an optimized inventory and effective supply chain, accurate demand forecasts are

imperative. Therefore, in order to select suitable forecasting techniques, error calculation can

be used as an effective method to select the most suitable technique to forecast demand for a

particular sector. The accuracy of the forecast could be measured by comparing the values of

error produced in the following error values, namely, forecast error (FE), Mean Absolute

Deviation (MAD), Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE) and

Tracking Signal (TS).

Post the demand forecasting phase, the estimated optimal quantity to inventory would be

calculated with a trade‐off between cost of ordering and cost of inventory and finding out the

order quantity such that the total cost of ordering and inventory is minimal. Since the lead time

between the time of ordering and arrival of order would be non‐zero, a lead time would have to

considered, which would dictate the reorder point which would be equal to the product of the

quantity consumed per unit time and the time required by the supplier to supply the quantity.

Also, since the lead times may vary significantly due to irregularities in supply and demand as

well as to make the possibility of stock out minimal, a minimum quantity, called a safety stock,

may be maintained for smooth operation of business operation. The safety stock acts as a

buffer in case where sales are greater than expected.

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41. Research on Procurement Management of MSE using system dynamics

methodology

Shubham Kakde, Manas Agrawal and Lakshman Suthar.

Purpose:

Purpose of this paper will be to develop of a system dynamics methodology which will result in

knowing of causal relation of all the elements of a company with its procurement system by

understanding the system w.r.t system dynamic methodology. Since the functions of

procurement like requirement planning, tendering, market study, supplier selection, asset

management will have dependency upon each other to some extent, system dynamics study

and model will help us to configure the dependency of each of these element over one other

and also the extent to which one gets affected by change in other. The desired outcome of the

study is to study various procurement cycles which will help in understanding the system

completely resulting in better policy development and implementation.

Methodology:

System Dynamics has been applied from the very beginning, as Forrester’s early publications

show (Forrester 1958, 1961). System dynamic is an approach to understanding the non‐linear

behavior of complex system over time using stocks, flows, internal feedback loops, auxiliary

variable and Time delay. It was develop in 1950’s to help corporate managers to improve their

understanding of industrial process. System dynamic is a method to study the world around us

looking as think as a whole. The objects and people in the system interact through feedback

loop where a change in one variable affects other variables over time which in turn affect the

original variable and so on.

Due to growing demand in market and the cut throat competition, it is very important to

provide the product in market on right time. Now to deliver the product on right time we need

to focus on the process of manufacturing, the breath of manufacturing is the inventory.

Inventory can be of many type like raw material, semi‐finished goods, tools‐equipment and

finished goods. Now to have this all at right time, at right place, of right quality and with right

quantity, Procurement Management play an important role. System dynamic method can be a

powerful tool for developing a general understanding for the underlying problem structures

within procurement management. In this paper we will focus our study in 3 sector of

procurement management as General Procurement, Procurement of Hazardous materials and

Procurement of Food material. Procurement management in general, pointing out relationship

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among the manufacturers, suppliers, distributors, and other relevant factors of procurement

system through system dynamics theory and method, confirming the causal relationship chart

and the system flowchart of the procurement system and deriving the causes tree of the

procurement system by VensimPLE which is a kind of software for system dynamics simulation.

Relationship management is a systematic project, including not only the enterprises which

contact with purchaser directly, but also other factors such as inventory levels, market

conditions and environment situation. However, the current theoretical results describing

systematically the interaction among the various elements of relationship management are

very few. Therefore, clarifying all kinds of influence factors to relationship management of

manufacturers in procurement activities and the feedback relationship of those influence

factors is necessary to improve procurement performance of manufacturing‐sector companies.

If system dynamics theory is to be used, the boundaries and scope of the system to be

inspected must be determined firstly. The core concept to be discussed of the paper is the

procurement, specifically the procurement to raw materials which are used by manufacturers

for their productions. Its decision also depends upon the market demand, manufacturing

capacity, inventory cost and climatic condition which will be set.

According to the system dynamics theory, the causal relationship among the factors should be

determined after determining the boundary of the system. The reason for manufacturers to

conduct procurement of raw materials is to maintain smooth production flow. This implies that

a system should be self‐adjusting as per the change caused by the factors in the system which

will give a better understanding and effective decisions. Basic factors which are responsible for

procurement management are purchasing, order processing, material handling, market

demand, inventory and capacity. For example for production it required procurement of raw

material through purchasing department and their dependencies on order processing of that

product

After determining the causal relationship chart among the factors of the procurement system,

system Stock and Flow‐chart can be determined according the system causal relationship and

by entering the equation for various variable according to their interdependency. Which will

result in forecasting of various factor which will be interdepended and help us to formulate

better policy by considering effect on whole system

Purchasing Policy applies to and binds all directors, managers and employees of the

organization in any situation where they are involved in a purchasing process, whether as

requisiteness or specifiers, purchasers or negotiators, or those who validate or authorize

payment. ‘Purchasing’ includes all procurement activities including leasing and hiring, and may

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where appropriate include other activities accompanying the life cycle of goods (or service

contracts) and the end‐of‐life disposal of goods which have been procured (whether or not they

remain in our ownership). It also include consideration of all legality, accountability and

auditability and mainly economic effectiveness, exploitation of development, risk management

and performance target.

Practical Implementation:

Procurement of Hazardous Materials. For this type of procurement purchase orders (PO),

maintain accurate inventory. There should be a responsible company employees as the person

to whom the material is to be shipped. The originator of the purchase order shall ensure that

the responsible person's name is noted on the PO. The procuring department shall enter the

purchase order information to system and print a barcode label for that material to be used

when it is received. When the hazardous material is received, the container, bottle, etc., shall

have the bar code label affixed to the container by the department ordering the hazardous

material. The bar code label must include the expiration date of the material. The material shall

be stored, if not used immediately, in accordance with the manufacturer's MSDS or label

warnings. Another sector of procurement management is procurement of food items.

Companies must ensure that all purchased food items meet the purchased food standards.

These items must then fit in to all meals or snacks served such that these meals and snacks

meet the nutrient requirements. The purchased food standards ensure that agencies are

making healthier choices like low‐fat dairy products a regular part of people’s diets and

ensuring that people who eat a few items of each meal will have healthy options. The meal and

snack standards ensure that people eating whole meals and snacks are eating a healthy,

balanced diet it also ensure the packing is airtight and food is stored in proper condition as

required. Understanding this system using SD methodology will give us better understanding

which will result making good policies and in taking optimal decision according to the policies.

Value:

The paper is unique in the sense that it develops an in‐depth model, which will help the

managers and procurement departments to better understand and predict the future steps at

the time of any change in the system. Also this paper will to plan the procurement process and

the factors associated with it as in time of process, further requirements with help of market

survey and the system.

42. Approaches for combining operational decisions for maintenance and

quality control: A review

Pravin Tambe and Makarand Kulkarni.

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Purpose – The purpose of this paper is to review the literature on combined decision for

maintenance and quality control. For these integrated models critical observations from the

literature are presented.

Design/methodology/approach – The paper systematically classifies the published literature

using different techniques, and also identifies the considerations in the author approaches

about the integrated modeling and the outcomes from the research. A variety of mathematical

tools and techniques used in the literature are mapped to the main issues considered.

Findings – The paper finds the important issues in the integrated modeling between

maintenance and quality control over a period from 1988 to 2016. The literature is segregated

year wise and author wise. There is an emerging trend towards interest for developing the

combined approaches for these functions. For developing the integrated models, either a

periodic or age based maintenance is combined with quality control using x ̅‐control chart

based on the economic design principle. The objective was to determine the optimal values of

the decision variables (n, h, k, and TPM) that minimize the expected total cost per unit time of

the system. Apart from this, a condition based maintenance is also considered in the recent

years. The integrated approaches have shown significant cost saving as compared to traditional

approach.

Practical implications – A limited literature is available on the classification of integrated

approaches between maintenance and quality control. The paper systematically classifies the

literature on the combined approaches for maintenance optimization along with quality control

parameters. This will give a holistic view of the different considerations for maintenance and

quality control in the integrated modeling. It also outlines the directions for future research in

the area of integrating these functions with other shop floor aspects.

Originality/value – The paper contains a comprehensive listing of publications on the combined

approaches and their classification according to various attributes. The paper will be useful to

researchers, maintenance professionals and others concerned with maintenance and quality

control to understand the importance of maintenance management in combination with the

quality control function.

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43. Multicommodity Network Design under Congestion

Navneet Vidyarthi, Sachin Jayaswal and Sagnik Das.

Multicommodity Network Design (MND) problems arise in various applications ranging from

telecommunications, transportation, and logistics to production planning. In this paper, we

consider a class of multicommodity capacitated xed‐charge network design (MCFND) problems

under congestion. The model captures four important features of network design applications:

the interplay between investment and operational costs, the multicommodity aspect, the

presence of capacity constraints, and accounts for congestion

on the arcs while routing flows from the source to the destination. The problem seeks to

simultaneously establish capacitated arcs that connect various nodes on the network and route

flows from the origin node to the destination node so as to minimize the sum of the fixed cost

of establishing the capacitated arcs, the transportation cost for every origin‐destination pair as

well as the congestion associated with waiting and service delay on the arcs. Congestion on arcs

is modeled as the ratio of total flow to surplus capacity by viewing the arcs as a single‐server

queuing system with Poisson inter‐arrival rates and exponential service times where congestion

refers to the queuing delays as a result of variability in the arrival times and service delays on

the capacitated arcs. We present a nonlinear integer programming formulation of the model.

Using simple transformation of the nonlinear objective function and piecewise linear

approximation, we present a linear

reformulation of the model. An outer‐approximation algorithm based exact solution approach

is proposed and computational results are presented.

44. Stepping on the Scale: SOLAS’ Container Weight Amendment

Saroj Koul.

Purpose: The rationale of this study is to examine if the 2016 SOLAS amendment will provide a

net benefit for affected parties such as exporters, importers, and national governments. This

report will allow affected parties to familiarize themselves with the standards before they

become legally binding. Since its announcement in 2014, the amendment has been met with

resistance by various groups such as the U.S. Congress, U.S. Coast Guard, and members of the

Russian government; our research also serves to determine whether this resistance is justified

or not.

Approach: This report will begin by explaining the complicated amendment in simple terms;

specifically, the two methodologies to weigh shipped goods and the consequences for those

who do not comply will be discussed in detail. Thereafter, a meta‐analysis of the issue will be

performed; in other words, legal interpretations, scholarly articles and newspaper articles in

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the public domain will be explored. The meta‐analysis will serve to determine whether the new

standards will be beneficial for three main stakeholders: shippers, port authorities, and national

governing authorities.

Findings: It was determined that all three stakeholders receive an overall benefit from the

implementation of the amendment. This is based on financial, logistical, and safety

considerations.

Practical Applicability: The container weight amendment by SOLAS is a current issue facing the

supply chain industry; parties who ship or receive goods via ocean transport need to be

exceptionally familiar with the new standards. This study will provide stakeholders with a

simplified explanation of exactly what needs to be done to comply with SOLAS’ amendment

and consequences for non‐compliers. Furthermore, the amendment has been met with

opposition by various stakeholders in the United States and Russia; it is hoped that the findings

of this investigation can assist in convincing them that compulsory container weight verification

will be an overall benefit for the shipping industry.

Originality/Value: While articles which discuss the implications of the SOLAS amendment exist,

very few research papers have been published. Consequently, a meta‐analysis of qualitative

research topics will provide substantiating evidence to those affected by the amendment.

45. Benefits & Scope of GPS in Logistics and in Different Works of Life

Arijit Poddar.

The issue of time management is an integral part of today’s life. So most of the thing we do,

we think of doing or is happening in an around us is associated with the factor 'Time'. So real

time data will put us in a better position to be able to assess the optimal time related to the

execution of the concerned work, so that we are in a better position to manage our daily

schedule, work etc and plan the day ahead efficiently. Suppose A has purchased an article from

an e‐tailer say XYZ who will be delivering the item to the buyer’s address. But A lives alone and

has to go to work on the day of delivery. Now the item which is out for delivery can be tracked

through a GPS and real time data is being sent to A every 30 minutes, A would be in a better

position to arrange for someone to receive the item on this behalf and he doesn't have to wait

to receive the delivery nor does A has to miss his office to take the delivery. Suppose one has a

logistics business whose office is located in West Bengal and his trucks are moving in different

parts of India. Now the owner has a lot of questions in his mind such as the following ones.

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Has his vehicle yet reached the destination?

What is the present location of his vehicle?

The vehicle is delayed. Where is it?

Are the kilometers log accurate?

How to ensure transparency about the vehicles movement?

How to check & prevent unauthorized detours?

How to view the travel route?

Trip Sheets

What is movement pattern of the vehicle?

How to ensure the shortest delivery path?

Is the vehicle over speeding?

So a real time data about the vehicles from the tracking details obtained through GPS

connectivity will enable the owner of the business to have readily available details at any

given time. The GPS connectivity along with the use of different tracking software that are

available in the market, will provide solutions to the owner’s queries , provide him with better

data which would help him optimize business decisions and also will help him provide his

clients transparent details. The GPS facility also helps in knowing when and where the vehicle is

taking breaks and if the vehicle is following the correct and shortest route. The data obtained

through GPS attached in the vehicle will help improve the followings:

Operational Optimization

Curb unauthorized halts

Enforce safety norms

Real time and updated information’s to customers

Over speeding alerts

Android APP for anytime anywhere tracking

Route adherence

Schedule adherence

Temperature Report

Door opening

Accurate monitoring of hold period at point of delivery

Logging of kilometers for accurate billing

Improved vehicle utilization due to faster turn‐around

More trips per vehicle per year

Higher revenue

Reduced cost

Happier end customers which will result in loyal customers

Enhanced safety of Man & Materials

Immobilize vehicle remotely through sms in case of any emergency

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Similarly in another situation, suppose a Ready Mix Concrete vehicle is out for delivery with

Ready Mix Concrete, now the client waiting at the construction site has done the necessary

so that casting can be done once the concrete reaches the work site. At the last moment

some technical glitches arise which need to be addressed keeping in mind that the Ready

Mix Concrete can't be kept in the vehicle for long. If the operation manager at the work site

has access to the real time location of the Ready Mix Concrete vehicle he or she would be in

a better position to take decision such as how much manpower should be employed for the

rectification work without disturbing the other works which are in progress. There are many

other vehicles which might be in use in the construction on a rental basis, movement of such

vehicles can been monitored in real time which will help the company generate work hours

from the vehicles they have rented by utilizing the real data from the GPS connected in the

vehicle. Once technology like this is easily available in the market and more people are aware

of facilities like these it will help different types of industries such as the Hotel Industry to keep

a track o the Guest moving in the hotel cars for safety reasons, the local vendors can also get

the benefit of this technology as they can track the vehicles carrying their orders from the place

it has been dispatched and so, if proper data is provided in real time to the vendors they

can utilize their daily time in a much better way. Manufacturing industries can track their

goods which are being transported daily to their customers. This will help develop

customer relationships as they are always connected with shipments that are being transported

to them.

46. Interdependence among dimensions of Sustainable Supply Chain:

evidence from Indian leather industry

Sandeep Kumar Gupta and Uday S. Racherla

Purpose: The Indian Leather industry has been passing through turbulent time due to its environmental compliance requirements. To assist the industry in coping up these challenges, it is vital to understand the relationships among the three dimensions of sustainability i.e. economic, social and environmental performance in a leather value chain. Though, many researchers have tested and recognized the relationship with theoretical as well as empirical basis for various industry but not for leather industry. The results have been mixed, as such, there is no consensus among their findings. Therefore, to assess interdependence or influence of one on another i.e. among economic, social and environmental performance, this study focuses on leading states of Indian leather Industry.

Design/methodology/approach: This study followed exploratory research where Partial Least Square (PLS) based Structural Equation Modelling (SEM) has been used to explore the relationship among the dimensions of sustainability in leather supply chain. The states has been selected based on judgmental sampling. The study used unit level data for the leading states of

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Indian leather Industry namely, Tamil Nadu (TN), West Bengal (WB) and Uttar Pradesh (UP). The study has used Annual Survey of Industry (ASI) data from 2007‐08 to 2011‐12. The proposed hypotheses have been tested using WarpPLS 5.0 software. For performance assessment purpose, a framework has been developed based on theoretical constructs, namely ‐ economic, social and environmental performances – which were weighted averages of indicator values (Fig. 2). These indicators were in turn based on literature precedence, recommendations by industry experts, correlation analysis and available data.

Findings: The descriptive analysis revealed that UP has performed better in social and environmental performance, whereas, TN has shown leadership in economic performance. This could be attributed to higher export margin and superior technological advancement of TN. The worst performance of WB may be assigned to its less incentive and low motivation for pollution preventive measures, and strong hold of labour union.

The structural equation analysis of unit‐wise leather industry data supports significantly bi‐directional negative relationship between social performance and economic performance among all the selected states. In contrast, the relationship between economic performance and environmental performance, as expected and supported by many existing theories, has shown bidirectional positive relationship. However, the relationship between social and environmental performance has shown quite mysterious and mixed trends. TN has depicted significantly negative coefficients which could be attributed to higher pressure for environmental compliance which might have led to trade‐off between the two to gain cost competitiveness.

Research limitations: Unfortunately, due to unavailability of data, many critical indicators were dropped from the theoretical framework of sustainability measurement. These are – Percent Child Labor (PCL), Differences in Remuneration (DIR) between men and women, Percent Community Welfare Expense (PCWE), Effluent Treatment Index (ETI), Solid Waste Disposal Index (SWDI), and Emission Index (EmI).

Practical implications: The outcome of the study could be used to help policy makers and industry owners to map and to take appropriate preventive or corrective steps in terms of selecting and supporting various social and environmental interventions which are having positive influence on economic sustainability of leather industry.

Social implications: The leather industry in India, specifically in the selected states, has been extending employment opportunities to thousands of men and women. However, the industry is also found responsible for water pollution and various health hazards in the areas of close vicinity. Therefore, it is essential to understand the interdependence among sustainability dimensions and optimize the trade‐off.

Originality/value: the sustainability framework proposed in this work is an original contribution of authors to the existing literature. Moreover, this study on the Indian leather industry fills the gap and resolve the mystery of interdependence among the three dimensions of sustainability.

Keywords: Sustainability; Indian Leather Industry; Structural Equation Modelling.

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47. Integrating SME’s of Indian Switchgear and Transformer Industry using

Lean Supply Chain Management Practices

Mrunalini Dodkey

Purpose: The growth of any nation is primarily decided by available infrastructure and the

vision it has to move to the next level as a part of larger economy. The four pillar of

Infrastructure includes modes of communication, transportation, industrial setups and power

capability. This makes it very important to have strategic view of all these four areas at national

level. As per 12th plan released by Planning Commission of India, energy use in India will

increase by 10% till 2031 as compared to what it is today. The emphasis is on providing energy

to rural India with focus on increasing supply side potential by augmenting generation capacity,

expansion of transmission system and capacity, strengthening of distribution system, improving

access to energy, development of renewable energy. Purpose of the research is to study the

supply chain management of electrical industry especially switchgear and transformers and the

role of SME’s in strengthening the supply chain. Unlike the automotive industry and other

repetitive type of industry where most of the activities relates to procurement, manufacturing

and distribution, in electrical industry, engineering is time consuming activity which decides the

lead time of the product to the market. Joint ventures, technical collaboration, value chain

partnering, green channel vendors are some of the models that are adopted in electrical

industry. Many of the OEM’s have outsourced technology to SME’s in form of ancillary units

and have become lean in the process. The role of SME’s in this area is very important since

SME’s are technically very sound and have the niche in value chain.

Design/Methodology: Secondary data through literature review and primary data through

Questionnaire Survey will be used to explore the supply chain management practices in upward

supply chain and study SME’s constraints to move towards lean supply chain management.

Findings: PCA identified 6 factors namely: Industry Type, Demand Variability, Product

Segmentation, Use of Lean Tools, Information Integration, and Size of the Organization as

deciding factors for implementation of lean supply chain management practices.

Research Limitations/Implications: The SME’s from only Maharashtra region were contacted

for data collection purposes.

Practical Implications: Lean supply chain processes across the organization will speed up the

entire value chain. Information Integration throughout the supply chain shall improve overall

supply chain efficiency. Formation of switchgear and transformer cluster will enable the SME’s

to respond to dynamic changes in the demand variability.

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Social Implications: None

Originality value: Enabling of information integration through frugal solutions across the value

chain shall make product movement transparent right from source up to the customer and shall

help in better delivery commitments, reduced lead time, reduced inventory at different

decoupling points and hence reduced wastages.

Keywords: SME’s, Switchgear and Transformer, Lean Supply Chain Management

48. Supplier Selection Using Combined SWARA and WASPAS – A Case study

of Indian Cement Industry

Rohit Singh, Jitendra Vishnolia, Jigar Gajjar and Anand Singh.

The focus of this research is projected on the dynamic relationship of two closed entities buyer

and supplier who are backbone of supply chain management (SCM).Aim of the paper relate

implementation of supplier management practices which creates culture of benchmarking of

these absolute quality management practices. The aim is to recognize and establish

relationships between supplier’s management by buyer and its relation with buyer’s quality

management. As for any company design of supply chain has a motto of supply chain surplus,

an obvious approach is to explore within the box rather than thinking outside the box. Some

companies have already established as a practice, and this trend will increase with time. Supply

bases are full of deep pockets of knowledge within them which can be very fruitful. Generally

multi factor method should be considered in the decision making method of research. Hence, a

robust model should be considered for such study cases. Moreover, the forethought outlook is

necessary for the future competing of the project. “Stepwise Weight Assessment Ratio Analysis

(SWARA)” is used for decision making process in order to prioritize and calculate the relative

importance of the criteria. Further, Weighted Aggregated Sum Product Assessment (WASPAS)

methodology is applied to evaluate potential alternatives.

49. Extending Green Practices in Supply Chain Management

Sonal Surabhi, Suman Sowrabh, Aditya Dubey, Yashomandira Kharde, Rohit Singh.

The aim of the paper is to understand green supply chain, and with the help of that, to

understand problematic areas and methodologies adopted to develop an understanding of

alignment of processes towards a greener environment. We have proceeded with our research

with certain key parameters like supply chain’s incoming logistics, production, outbound

logistics and reverse logistics. The supply chain metrics that we have measured include order to

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delivery lead time and supply chain response time. We have initiated our research with the help

of descriptive analysis of the data by floating a questionnaire for capturing data from various

Manufacturing companies in and around Nasik.

The questionnaire has helped us gain real time information of the factors and its effect on

supply chain. The sample has been taken from top and middle level managers of supply chain

industry. After data collection, Hypothesis generation has been done in line with dependence of

the factors on the supply chain metrics. Further, the methodology used is Reliability Test, Factor

analysis of data which has helped us to find impact and relationship of the factors with the

supply chain measures: lead time and response time.

50. Lean Production Supply Chain Management as Driver towards Enhancing

Product Quality and Business Performance

Sunil Das, Arun Koonammave, Prasanjit Biswal.

The main purpose of this study is to see how lean production, a key component of an efficient

supply chain management aims for continuous elimination of waste in all production process

thus achieving lower production costs, reducing the lead time and increase in output thereby

acting as a driver towards enhancing product quality and business performance. Lean

production thus, enables companies to attain good process management and better

documentation as it focuses on improving the operational efficiency, improving efficiency of

material flow, better supplier bond, simplified scheduling, increasing manufacturing flexibility

and hence increasing the overall product quality. Lean production strategy has found its

application in many sectors like electronics and automobile manufacturing industries whose

foremost priority is to reduce the production cycle time. One more aspect of lean management

is to reduce the uncertainties regarding demand, manufacturing and supplier. Manufacturing

uncertainties include product quality characteristic, downtime, worker’s absenteeism and

operator skill levels. Lean Supply Chain Management aims to reduce the various variations by

establishing standard work procedures.

The authors have taken the case of a company ABC Ltd. where there was either an inventory of

finished goods/ raw material piled up in the plant and or at times a shortage of raw materials

because of variable nature of demand from client. The authors have then tried to find out how

to go for effective production planning so that the inventory of finished goods/ raw materials

can be managed? The objective is to reduce the lead time across supply chain.

There are different methods of lean transformation. In this paper an enhanced Feld model has

been proposed by addition of a new phase “FUTURE STATE VERIFICATION AND VALIDATION”

after the “FUTURE STATE DESIGN” phase in order to ensure that it correctly addresses current

state gap. Measures have been proposed about to reduce lead time for parts procured from

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abroad and also from local suppliers. Finally it has been proposed to adopt a combination of

Lean and Agile (Leagile) supply chain strategy with additional recommendations of Enterprise

resource planning (ERP) and Collaborative Planning Forecasting & Replenishment (CPFR)

method to improve overall operations and customer services.

51. Lean Supply Chain in Manufacturing Unit using Value Stream Mapping.

Ashish Yadav, Ashwini Awale, Md. Zoheb Mehraj

Lean a series of activities or solutions to eliminate waste, reduce non‐value added (NVA)

operations, and improve the value added (VA). This VA and NVA concept were derived mainly

from Toyota Production System. Lean is a combination of 5S, SMED, Kanban, and JIT. There are

basically eight type of waste highlighted in TPS like: overproduction, waiting, conveyance, over

processing, excess inventory, movement, defects, unused employee creativity and Over‐

production (biggest failure).

Value Stream Mapping (VSM): It is a tool/ lean method to analyze the Current State and design

a Future State for the series of events that take a service or product from its beginning to finally

to the customer. Imagining Value Stream as a Waterfall will help to understand the concept

with clarity. In Value Stream, “all the steps, both value adding and non‐value adding required to

take a product or service from raw material to the waiting arms of the customer”. Value Stream

Mapping is mainly about reducing the Muda. Muda consumes enormous amount of time. On

the contrary, the value added time or the time the customers want to pay for is very small.

Often the company focus on the VA portion of the lead time. For instance, they want to make

VA twice as fast. They work to save a few seconds or minutes of machine or operate cycle time

in order to reduce the overall‐lead time. VSM Most important lean tool as it is, it behaves like a

visual tool which helps in documenting all the activities required to receive and fulfill a request

from our customer. It helps people see what is actually happening in a process through direct

observations. One has to closely monitor the process and collect actual data. Through this study

we try to find out the different aspect of VSM and how it can be useful in decreasing the

Manufacturing lead time

52. Supply chain performance measurement framework for small and

medium scale enterprises

Akansha Rammaiya.

An effective supply chain system is required for lowering of distribution and inventory costs

and increase operational efficiency by providing better medium for information sharing

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between all the links involved in the supply chain, improving process integration, providing

efficient manufacturing strategy along with improving financial aspects like cash flow to

collaboratively result in value addition to the customer culminating in higher profit margins. To

connection for those processing industry, the worth propositions from claiming supply chain

administration incorporate network differentiation also market division where the focus is to

distinguish as a chain to meet those progressive what's more particular requests of customers,

integrated quality where the target includes meeting the expanding requests from clients and

network optimization a process where the target is to minimize those expenses through a

streamlined chain hosting coherent information supply.

The extent of realization of above mentioned objectives and benefits can be measured by using

output of the Supply chain. This is because the performance measurement of supply chain

provides important feedback information which enables decision makers to monitor

performance, reveal progress, enhance communication and motivation and diagnose problems.

It is also used to reveal effectiveness of strategies and identification of potential opportunities.

Specific key performance indicators are used depending upon the objectives of the supply

chain. It is very critical to choose the right kind of performance measures and performance

measurement system in the supply chain. Some of the difficulties in determining a performance

measurement system include lack of connection with the strategy, an unbalanced approach,

low focus on competition as wells as customers, localized optimization due to lack of systematic

approach etc. Literature shows seven different types of supply chain performance management

systems exist. These are Function based measurement system, Dimension based measurement

system, Supply chain operations, reference model, Supply chain balanced scorecard,

Hierarchical based measurement system, Interface based measurement system and Perspective

based measurement system.

Performance measurement systems succeed when the organization’s strategy and performance

measures are in alignment and when senior managers convey the organization’s mission,

vision, values and strategic direction to employees and external stakeholders. The performance

measures helps to contribute to the success of the company and its stakeholders’ measurable

expectations. Both Balance Scorecard approach (BSC) and Supply Chain Operation Reference

(SCOR) model have been considered.

Execution estimation frameworks succeed when the association's methodology and execution

measures are in arrangement and when senior managers pass on the association's main goal,

vision, values and vital heading to workers and outside partners. The performance measures

adds to the achievement of the organization and its partners' quantifiable expectations. Both

Balance Scorecard approach (BSC) and Supply Chain Operation Reference (SCOR) model have

been considered.

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53. Lean assessment parameters and roadblocks in implementation of Lean

Management in Indian Auto component Industry: A combined AHP &

MICMAC approach

Akshay Kumar, Rohit Singh, Tanmay Borulkar and Partha Paramanik.

Purpose ‐ The aim of this paper is the prioritization of roadblocks in the implementation of lean

management in Indian Auto component industry based on the industry inputs and the

development of an interpretative structural model to establish the relationship between these

variables. The MICMAC analysis is carried out and the driving as well as the driven power of the

roadblocks are established further. The cause – effect relationships between the popular 7

wastes associated with Lean management and the roadblocks is investigated and the

relationship between ISM hierarchical levels and the Lean wastes found out. Finally, the impact

of the domino effect created by tackling the bottom – up ISM hierarchical structure of

roadblocks is seen upon Leanness assessment parameters with respect to various wastes.

Methodology – 14 Roadblocks in implementation of Lean management in Indian Auto

component industry have been identified via industry visits and by interacting with the industry

experts combined with extensive review of the literature available on Lean Management.

Further, a questionnaire based study has been carried out and the responses of the candidates.

The identification of the variables affecting the smooth execution of lean set ‐ up in the vehicle

sector in India is followed by prioritizing them with a powerful pair wise comparison analysis

using the AHP technique along with the calculation of Consistency Ratios. The statistical Mode

has been calculated for registering a response of a question answered by several respondents

from the concerned industry. ISM methodology is further used to identify interrelationships

among specific roadblocks, which are prevalent in the Indian automobile industry. MICMAC

analysis of developed ISM model is subsequently carried out in order to understand the driving

power and dependence of the roadblocks. A cause – effect analysis is used to establish the

relationship between the popular 7 wastes associated with Lean management and the

roadblocks arranged into hierarchical levels using the ISM methodology. Finally, the impact of

the domino effect thus created by tackling the roadblocks in the hierarchical order of the ISM

model is seen on Leanness assessment parameters with respect to various wastes.

Findings – This paper contains an argument to prioritize using AHP technique the Roadblocks in

implementation of Lean management in Indian Auto component industry identified via industry

inputs and literature review. A description of interrelationships developed using the ISM

approach has been described. The same has been cross – verified by using the MICMAC

approach that also surfaces out some of the latent variables, which can possibly be misjudged

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by the ISM model. The relationship investigated between the roadblocks and popular wastes in

Lean implementation is used to measure the impact of dealing with the roadblocks in bottom –

up hierarchy of ISM model upon the Leanness assessment parameters with respect to various

wastes.

Practical Implications – The identification and prioritization of the various occurring roadblocks

in the Indian Auto component Industry and identification of the various interrelationships

among specific roadblocks along with understanding the driving power and dependence of the

roadblocks will enable managers to use this intel for waste reduction along with the use of a

powerful pair wise comparison analysis using the AHP technique to focus on areas of

improvement. Consistency ratio values are obtained and used to accept or revise the subjective

judgment of the industry experts who answered the questionnaire used in data collection. The

managers will also have knowledge of interrelationships among the popular 7 wastes of Lean

management they are familiar with and the latent roadblocks that govern them in the industrial

scenario along with the impact of tackling the roadblocks in the ISM hierarchical domino

structure on the Leanness assessment parameters (with respect to the various wastes). This is

necessary especially for the Indian market considering the importance of resource constraints,

time and cost effectiveness to survive in this highly competitive scenario.

54. Benefits, Challenges and Bridges to Effective Supply Chain Management.

Pooja Shah

Purpose – Purpose of this paper is to analyze and come up with the benefits, barriers and

bridges to effective supply chain management and study the innovative methods used by two

of the leading organizations on how to counter the challenges faced by their supply chain.

Design/Methodology/Approach – The paper uses a pragmatic approach where previous

research is used to identify the major barriers for the supply chain and two cases of leading

firms are discussed to realize what the barriers in those firms are.

Findings – Major barriers to supply chain of the two firms were high demand fluctuations

because of varied product profiles and the lack of proper integration amongst the supply chain

elements. Customer satisfaction and on time delivery is being ensured by organizations by

overcoming various supply chain barriers such as coordination between various supply chain

partners by incorporating a flexible supply chain design and by use of improved technology and

communication systems to achieve the benefits of reduced cost and sustainability.

Research Limitations/Implications – The findings and analysis are based on firms in the specific

sector. There might be other possible benefits, barriers and bridges while considering other

sectors that have not been discussed in this paper.

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Practical implications – This study provides deep insights into the various problems faced by

the firms to effectively manage supply chain related challenges. Successful implementation of

right supply chain model proves to have provided the desired benefits in terms of cost,

sustainability and improved efficiency.

55. Prioritization of Antecedents for the Adoption and Execution of Supply

Chain Management using TOPSIS

Shreyash Bansal, Paras Bharel, Prahar Dongre

Purpose: The supply chain that we presently see has come a long way from what it used to be

traditionally. This evolution in the field of supply chain management can be attributed to

various antecedents that have shaped its development in past few decades. We have seen

many concepts like lean supply chain, JIT, agile supply chain, etc. and the latest being supply

chain flexibility, which have added new dimensions to the traditional supply chain. Thus, the

purpose of this study is to prioritize the Antecedents for the Adoption and Execution of Supply

Chain Management (extracted from literature) using TOPSIS Methodology in Indian FMCG

industry.

Approach: Authors have visited case firm to have an idea of issues related to their supply chain.

To carry out this study authors have done extensive literature review and extracted

antecedents most suited for Indian FMCG firm, accordingly designed the self‐administered

questionnaire and floated it among executives of case industry. The feedback authors received

in terms of filled up questionnaire become the input of data analytics using TOPSIS, and finally

designed the structured hierarchy of supply chain antecedents.

56. Digital Retail: A Sustainable Opportunity Yashomandira Kharde, Prasad Madan, Sonal Surabhi, Pravin Kharde

Purpose‐ The purpose of this paper is to understand that giving consumers what they want is

an easy win, but it is afflicted with sustainability challenges. Actual achievement lies in

motivating consumers to want what best not only for them; but for all of us‐ profit craving

people and planet.

Methodology‐ In this study the authors have extracted information from systematic literature

review (SLR) identify the variables or factors from extant literature and have used confirmatory

factor analysis approach to derive the conclusion.

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Findings‐ The findings mainly indicate that today time is equivalent to money. SLR output

suggests that we will see not just more online shopping, but a blurring of the physical and

online experience, with shoppers at home able to visit virtual outlets and in‐store shoppers able

to access a cloud of information about products and at the same time the consumer experience

will be more tailored, more continuous and more omnipresent.

Research limitations/ implications‐ Like any study, this study has its own limitations. In this

study, the authors have developed a model based on expert opinion. Though the number may

not be enough to validate the model statistically, nevertheless, it can be considered as a

platform for further research study.

Keywords‐ Digital, Retail, Sustainability

57. A Comparative Study on Automation Feasibility across Two Tools and

Report Benefit Assessment

Ayona Chakraborty

Infrastructure services offers a comprehensive portfolio of services to the clients that

completely maps the entire landscape of IT infrastructure advisory, design, implementation and

ongoing management to serve as true end to end capability partner focused entirely focused on

business outcomes. The result is an infrastructure solution which is efficient, scalable and

secure, that strikes a balance between flexibility and cost while facilitating innovation and

future business planning. The main objective is to help ensure that an IT service provider

company’s infrastructure operations runs as smoothly and reliably as possible. Robust

integrated operations are going to be built to the best practices of the IT infrastructure library

(ITIL), incorporating proven technology solutions and are augmented by specialist technical

expertise. The IT company of the study is known to provide its world class infrastructure

services by managing and optimizing its IT infrastructure to deliver true value by reducing

capital expenditure, reducing operational expenditure, integrating quality services, embedding

environmental considerations, the end results of which is higher productivity and end user

satisfaction. The company of study has achieved remarkable progress in streamlining IT

operations and providing support to customers across the globe. For ex‐ They successfully

helped reduce operational costs for manufacturing company Hochtief by increasing IT process

efficiency and providing value through economies of scale. Aided with a global team of 10,000

technical experts in all aspects of infrastructure, the company is now capable of implementing

multi source service integration to facilitate the standardization of infrastructure processes and

to maximize the value of services delivered by IT suppliers. It is also capable of providing

effective outsourcing services and service management capabilities across all infrastructure

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disciplines and legacy systems. Infrastructure services are now integrating the benefits of cloud

to business through the incorporation of a dedicated or multi‐tenant cloud services sourced

from public and private providers, including other associated cost effective infrastructure

services.

Whether or not businesses are outsourcing IT functions, it is vital for infrastructure and

application IT platforms are properly managed. The company’s service management team

ensures that the IT services provided are effective, efficient and aligned to the business

objectives. Today’s multi source environment evolved to be complex and global in bid to

improve the service delivery, cost effectiveness and efficiency but for achieving those grounds,

effectively managed services are essential. Service management in its current capacity holds

some of the most important projects associated to its services. In current situation

mutualisation and automation in the company are the two current projects of centre bed in the

SMG functions. Service management’s commitment towards cost benefit is not only associated

to the resources and processes it streamlines but also the placement of resources, technical

experts across the functional and technical domains. Service management endeavors to

streamline all processes associated to the IT services provided. With this thought in mind. The

Servicer management has been looking to automate the process of report making for faster and

efficient report making process.

Before we go deeper into the concept of automation, an understanding of the entire

automation initiative driven within the IT Company is important. The automation landscape

basically encompasses three streams Report, Process and Smart Utilities. Report automation is

the current drive within SMG today, where they are looking to automate 64 accounts into the

automation drive. Process automation mainly deals with streamlining the value process based

on its maturity by making an effectiveness and efficiency matrix and smart utilities help to

automate basic functions within excel like auto collate, for speeding up basic processes.

For developing an understanding of the process followed in reporting automation i.e. the first

stream of automation. We must first develop an understanding of the reporting process

followed by the reporting team. Essentially when there is a disruption on the flow of the

services provided by the service provider, the user/client raises an incident or a ticket. This

ticket is first reported as an incident and in response to this ticket a change process is initiated

after which an implementation ends the life cycle of the ticket. Repeated incidents are termed

as a problem and require a separate course of actions. So these four pillars of the ITIL

framework: incidents, problem, change and implementation information is picked up from the

remedy data base which is the ITSM platform used by the concerned IT company. This

information is also called the ITSM ROD data. This information is picked up from the ITSM

database and then collated into a report using various excel tools like Pivot tables, charts etc.

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Based on this various reports are made Service level agreement reports, breach reports and Key

Performance Indicator reports which are populated into a common dashboard and is available

for view for all the direct t stakeholders. Here the direct stakeholders are the clients, Senior

Management and Domain level managers.

Report automation is primarily done by two tools centrally in service management purview.

These are ITBM and Qlikview. ITBM as a tool has the ability to induct 33 of the 64 accounts bulk

of the accounts under the service management purview. The process followed by ITBM starts

with picking up information from ITSM ROD and then with constant dialoguing with the SMG

team, the ITBM dashboard is built using the reports data and the business logic behind

identifying the Key Performance Indicators are applied.

The main aim of this study is to streamline the processes to increase the efforts saving and this

objective can be met by identifying which tool in current capacity can meet the operational

requirements of the service management. Also since the ulterior motive is to induct as many

accounts of the IT Company in question into the automation program, the main aim of study is

to find a way to accommodate the two tools into the automation program. This project will

have tremendous cost benefits associated to faster and effective functions in the organization.

Now the end goal of this study is to satisfy the customers and maintain the quality of the

services provided.

58. New product development through quality function deployment

Preeti Shri Agrahari, Takshil Nagar

The aim of this paper is to explore the application of Quality Function Deployment in the mobile

phone industry. In today's world, the whole society is going tech savvy and what is more

technological in common man's life other than mobile phones. As a result the whole mobile

industry is growing rapidly and with more growth comes more challenges. Challenges to

compete, grow and sustain in the market.

As a research product, we have taken to upgrade outdated software and design of a smart

phone as per customer expectations to improve product life cycle and market share. Internal

processes and practices were not enough for the business so we decided to work on product

development through QFD as it helps in continuous improvement.

To achieve the mentioned goal we have used Quality function deployment methodology in

which we tried to map the voice of customers to voice of engineers. It works on triage

technique, therefore focuses on the higher priority requirements which saves time and effort.

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QFD is used for understanding the customer's needs and it also helps business to stay ahead in

the game.

It is strongly believed that mobile service design cost and design time will be significantly

reduced while mobile service quality will be greatly improved by using QFD approach due to its

systematic linking of customer requirements into and throughout the entire design,

development, and implementation process.

According to Dr. Yoji Akao who actually developed QFD in 1966, Quality function deployment

(QFD) is a “Method to transform user demands into design quality, to deploy the functions

forming quality, and to deploy methods for achieving the design quality into subsystems and

component parts, and ultimately to specific elements of the manufacturing process.”

“A process of determining the customer needs (the whats) and transforming them into target

attributes (the hows) thus converting the ‘whats’ into hows’.”

59. Interpretive Structural Modeling of Supply Chain Risks in a

Manufacturing Firm

M. Parthasarathi, Ravina Gautam, Kunal Pawar

Purpose: Manufacturing sector is an ever growing sector with a wide range of suppliers. The

supply chain of a manufacturing company is one its most critical part. The supply chain has a

huge role in many aspects of a manufacturing firm such as price of the product, lead time,

profits, quality etc. The supply chain has become a very complex structure due to a large

number of suppliers, service providers and customers. This complexity also has several types of

risks associated to it. Understanding and analyzing these risks has become an important aspect

in the manufacturing sector. Identification of supply chain risks is the first step towards

managing the risk. But the most important part is to devise an appropriate method that would

identify the most critical risk among all the risks and take the necessary action to avoid any

severe impact caused due to that risk. This will save a lot of time and money for any

manufacturing company.

One such method is the Interpretive Structural Modeling which is used for identifying

relationships among specific items. There may be many issues related to a complex problem.

But to understand these issues more accurately, it is important to clearly understand the

relationship between them. This helps in simplifying the problem to some extent.

Methodology: The approach starts with identifying many supply chain risks associated to a

manufacturing sector. The risks are identified and are placed in two categories – Internal Risks

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and External Risks. Internal Risks are the risks that exist within the organization and external

risks are the risks that arise from the events taking place out of the organization. Once the risks

are identified, a relevant relation will be chosen between all the risks.

A Structural Self Interaction Matrix (SSIM) is developed based on pairwise comparison of risks.

The matrix is then checked for transitivity. The SSIM is then converted into a Reachability

Matrix. The obtained matrix is then partitioned into different levels. The reachability matrix is

then converted into conical form. A digraph is drawn based on the relationship given in the

reachability matrix. The resultant digraph is then converted into an ISM model by replacing

nodes with statements.

Findings: This paper will help in analyzing the different supply chain risks associated with the

manufacturing sector and will also help in rating them based on their severity. This way the

most severe risk can be identified and can be avoided by taking some necessary actions.

Research Limitations: This paper does not include all the supply chain risks associated with the

manufacturing sector but only some important risks. The impact of other risks that are not

included in this paper will remain unexplored.

Keywords: Interpretive Structural Modeling, supply chain, structural self‐interaction matrix,

reachability matrix, transitivity matrix.

60. Evaluation of Supplier(s) for an Automobile Firm.

Moumita Saha, Vivek Alamadi, Aditya Bapat and Sudhanshu Pandey.

This paper is intended to put fixate on identifying critical parameters required to evaluate the

performance of the Automobile Industry. In this paper we will quantify the different

performance parameters on the substructure of which congruous evaluation of suppliers would

be done.

Methodology ‐ Performance quantification parameters of Automobile Industry have been

identified via plant visits and by interacting with the subsisting suppliers cumulated with the

extensive review of the literature available on Supplier Evaluation Parameters. TOPSIS analysis

is rigorously used to strengthen the relative judgment of the Automobile Industry stalwarts

whose responses have been collected with the help of questionnaire.

Finding‐ This paper contains an argument of using confirmatory TOPSIS analysis to reinforce the

subjective judgment of industry experts who answered the questionnaire regarding Evaluation

of Suppliers that was used for data collection.

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Practical Implications ‐ The identification of measures of performance of the evaluation of

suppliers is of extreme consequentiality for the present Automobile industry in India

considering the limitations of resource constraints, time and cost efficacy to survive in this

highly competitive scenario.

Limitations – The results thus obtained are strictly applicable to the Speedosteer Company.

However, these findings may or may not be applicable for some another industry. As every

company has different area of operations and respective supplier evaluation criterion is a

subjective matter to study.

61. A case on Business Process management.

Shrikant Shinde

ABC Ltd is one of the leading stock exchange in the India. ABC Ltd became the first exchange in

the country to provide a modern, fully automated screen‐based electronic trading system

which offered easy trading facility to the investors across all over the globe.

Key products offered by the ABC Ltd are Equities, Indices, Mutual funds, Equity Derivatives,

Currency Derivatives, Corporate bonds.

There are over 1000+ processes in the ABC Ltd across various departments. There is no

structured process classification in the organization. The processes for individual departments

are there at the local repository but not at the central repository. Also the levels defined by

each department are different. So there is no common language across organization for the

process classification. These impacts on the understanding of processes at organization level

and also the inter‐departmental linkage are difficult to understand. Also the knowledge transfer

to the new employees is difficult. Because going through each process without having the Life

cycle view of the process makes it difficult to understand.

The major problems across organization can be classified as below:

Content Management: The content management includes collection, management and

publishing of the information in any form or medium. ABC Ltd observed that due to

inconsistent internal language to describe the work done within the organization makes the

content management difficult. Also the organization of enterprise content, process flows and

models is difficult.

Benchmarking: The lack of structured process classification makes it difficult to compare the

tasks. Developing a common language takes a large portion of organizations time. Also the lack

of process framework makes it difficult to study the internal and external processes and

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practices of the organization. This makes the benchmarking difficult not only within the

organization but also between organizations. The performance management and process

measurement between organizations is difficult to implement.

Business process definition: The cross functional processes are missing. There is no way to

identify and create the missing cross functional processes.

ABC Ltd needs to improve its corporate performance by managing and optimizing its business

processes. It needs to map its processes in a Framework which will help in classifying the

processes according to global standards which will further enable Benchmarking, Content

Management and Business Process definition. But mapping all the processes of the organization

in a framework is a time consuming and complicated task. Hence ABC Ltd is looking for a

framework which is already existing and accepted across the industry and will offer easy

process mapping and classification.

62. Overall Equipment Effectiveness (OEE) to increase productivity of work

centre.

Shiladitya Adhikary, Arijit Roy, Bir Pratap Singh, Sourav Ghosh

Purpose: Overall equipment effectiveness (OEE) is a highly effective business performance

management tool, which critically evaluates how effectively a manufacturing operation is

utilized? It provides a quantitative approach on parameters such as availability, performance

and quality for measuring the efficiency of individual equipment or entire work centre. Besides

these parameters, there are certain performance factors such as the efficient use of raw

materials and the production conditions e.g. production system, logistics, skilled labour, etc. in

which the equipment or the process is exposed has a significant role to play in the overall

process performance. The purpose of this paper is to present an alternative solution to

implement OEE in work centre to increase productivity.

Design/methodology/approach: This paper reviews the scope of OEE to be implemented on an

individual machine or entire work centre to increase the productivity and yield. In a seamless

tube plant, overall equipment effectiveness (OEE) is being monitored on the mother machine

(hot rolling mill) which produces the seamless tubes. The total operations of the mill are being

recorded minute by minute. The data generated is being analyzed for productive time and

unproductive time, breakdown time, utilization%, productivity% and availability.

The crane productivity report generated has parameters such as available hours, working

hours, idle hours, Breakdown hours. Total no. of lifts, holding hours and utilization. After

implementation of OEE, the efficiency of the cranes will be heightened.

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Originality/value: This paper presents a novel and alterative approach to measure the

performance of manufacturing and construction equipment and processes. The OEE is to be

implemented to decrease breakdown time and streamline TPM.

Findings: Before implementation of OEE, there was a substantial gap between equipment

capacity & actual output. Workers & managers were not able to come to a reason for low

outputs & quality issues, hence increased production cost, high downtime & breakdowns,

defects in products. The focus area was not clear & that’s why these problems couldn’t be

attacked. Management was not able to take decisions regarding the future course of actions

due to low output & increased production cost. The per second value of running the mill was Rs

100 as per management.

As the first step of OEE implementation, we came up with a plan to monitor each minute’s

performance of the machine with help of a software & a spreadsheet (format attached). Every

minute was accounted for in a shift & reasons for problems were noted down so as to take the

necessary actions to avoid such problems in future. Furthermore, the responsibility of problems

were divided into 5 sections involved in running the machine.

At the end of the shift, there were brain Storming Sessions in which key people from Quality

Assurance, Mechanical Maintenance, Electrical Maintenance, Operations, & Tooling sit down

together & discuss together on CAPA for last day's stoppages, breakdowns & come up with

action plans to eradicate/ reduce this delay time

Standard time for each activity is set based on good practices & video clippings are made

This standard time is taken as reference for assessing the performance of a team in performing

the same activity in their shift.

After accumulation of lots of data, we could actually identify what are the most frequent

problems, which are the least frequent, which problem the most time was consuming.

Differentiating the problems helped a lot to managers to decide upon the action plan & takes

the necessary actions & make the necessary resources available on time for avoid such delays.

After 4 months, we could see that the efficiency of the machine increased from 82.4 % to 85.3

%. The utilization increased from 64.2% to 70.7%. (Report attached)

Keywords: Overall Equipment Effectiveness, Availability, Quality, Productivity, Total Productive

Maintenance.

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63. Risk Analysis in Global Supply Chain Management: Application of AHP

and DEMATEL

Pradeep Kumar Jain, Prasang Jain, Tarun Garg, Akshay Gupta

Purpose – The efforts put forward would be in finding out the critical parameters out of the set

of general parameters that will have an effect on the production systems in the organization,

first by identifying the influential parameters from the set of recognized general parameters by

using AHP (Analytical Hierarchy Process). Each of these influential parameters can then be

analyzed independently by DEMATEL (Decision Making Trial and Evaluation Laboratory)

technique to find out the most critical parameters among these that affect production system

the most and accordingly we can use our findings to improve those production systems.

Design/methodology/approach – we have identified and build a hypothetical case comprising

of general parameters which were the result of surveys, studies and research done in the past.

Based on this data and with the help of industry experts, we have assigned weightage to

individual factor according to its relevance to the production systems of organizations. Then,

we ranked these different recognized parameters according to their level of importance using

AHP. According to the ranks, we selected few influential parameters and further evaluated

those pair wise to find the cause and effect relationship between these using DEMATEL and

decide which parameters are most crucial to work upon for improvement in production system.

Research limitations/implications – Since this is a hypothetical case, the selection of the

parameters and their effect on each other is based on some individuals perceptions which

might not go with the perception of the rest. The structural model is based on the AHP and

DEMATEL methodology, which has its own limitations. For example; the model is highly

dependent on the judgments of the experts. Opinions of the experts may be biased. Besides

that, the effect of uncertainty and human bias in evaluating the parameters has not been

considered in this study.

Practical implications – The proposed DEMATEL based analysis model may also be extended to

the different industry sectors of Indian economy, in improving their production system.

However, the expert’s opinion regarding factor evaluation may 3 vary. The result obtained for a

particular sector might not comply with the findings of the other sector and hence the findings

would not be generalized.

Originality/value – This is the first kind of study which identified many parameters across

different domains of production systems in an organization. After this, a hierarchy among these

identified parameters is determined by using AHP approach. After this approach we came to

know the most influential parameters responsible for improvement in production systems. We

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further evaluated these influential parameters to understand the cause and effect relationship

among these using DEMATEL which are most critical for the production systems.

Keywords AHP, DEMATEL, Production System, Influential, Critical

64. Process development using ISM in Ecommerce business.

Basavaraj Koulapur, Sudipto Sinha, Eshwar Pasarge, Vivek Munshi

Electronic commerce, commonly known as e‐commerce or e‐commerce, is the trading or

facilitation of trading in products or services using computer networks, such as the Internet.

The Ecommerce business looks to promising at least in the near future. It is estimated by

Morgan Stanley Research that Ecommerce market size in India will be USD 119 BN by 2020. This

also comes as a challenge with growing competitors, improved customer satisfaction and

catering to wide range of customers. To retain profitable market share it is essential that

companies need innovation and improvements in the existing process.

The scope of the project is to identify the important factors that influence strategy and profit of

an Ecommerce business. This can be achieved by using Interpretative Structural Modelling

(ISM). This tool is used to identify how each of these factors affect remaining factors. Further

prioritizing these factors at various levels to strategize the plan of action in successful business.

65. Identification and evaluation of parameters affecting ERP System

Implementation in a manufacturing firm

Priya Daware, Videtha Ghai, Mayank Mehrotra, Saikat Chandra.

Purpose: Today business is not limited to local markets but has grown to global business

environment. Competition today is not limited between companies only, but it has extended to

be among their supply chains as well. Thus, companies are beginning to realize that in order to

survive in the global business environment they must improve their whole supply chain along

with the organizational efficiency. These reasons force many companies to make large

investments in developing and implementing better technologies and systems such as

enterprise resource planning (ERP) system (Davenport and Brooks, 2004).

The purpose of this paper is to examine the parameters for successful implementation of ERP in

manufacturing sector.

Design/methodology/approach:

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The regression ‐

It is a mathematical method of obtaining the reliability of the data by obtaining the line

of best fit between dependent variable, usually demand and some independent

variable. This method indicates the linear relation between X and Y by the value of co

relation co efficient.

This method is being used to calculate confirmatory factor analysis using coefficient of

determination.

Research limitations/implications: This research focuses only on implementation of ERP

system life cycle, where ERP system passes through three implementation stages of system life

cycle and that includes pre‐implantation stage, implementation stage, and finally post‐

implementation stage. Two or three stages of ERP system life cycle could be investigated

simultaneously.

Originality/value: The results of this study will enable the sector to achieve optimum usage of

ERP system after the implementation stage and help to avoid system failure and achieve better

SCM performance. The study contributes toward technology diffusion between companies

through reducing the likelihood of ERP systems failure, and therefore introduces ERP systems in

manufacturing sector.

Practical implications: The application of this integrated methodology would serve as a

systematic approach for measurement of the aggregate performance of ERP in manufacturing

sector so as to gain valuable academic and practical insights

66. Interpretive Structural modelling of Supply Chain Risk Management

Nirmal Shah, Nikhil Mohite, Ashish Nannaware, Vishesh Khandelwal.

Purpose: The purpose of this paper is to identify the possible risk in Supply Chain, assessment of

it and provide structural analysis of major risk which is interdependent. It will provide how

interpretive structural modeling (ISM) gives deep insight to managers in identifying and

understanding interdependencies among supply chain risks on different levels like Inbound, in

house and outbound. Interdependencies among risks will be derived and structured into a

hierarchy in order to derive which risk is major and affect other risk with corresponding driving

power and dependency.

Design/methodology/approach: Interpretive structural modeling is a well‐established

methodology for identifying relationships among specific items, which define a problem or an

issue. ISM was used to identify relationships among major supply

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Chain risks and to classify the risks according to their driving and dependence power.

Originality/Value: This model’s insight would help supply chain managers in the identifying the

risk which is destructive to the supply chain system which can be tackled by preventive and

reactive action. Also managers get a deep insight in effectively allocation of risk management

resources in the subsequent risk management action.

67. Kumbh Mela: Nasik City Logistics study of the state shuttle‐bus

transportation system using simulation approach

Jitendra Vishnolia and Rohit Singh.

Kumbh Mela is the largest peaceful and religious gathering in the world, in which Hindus

gather to bathe in a sacred river to cleanse one of all sins. The month‐long Kumbh Mela is a

Hindu festival that takes place once every three years rotating around four cities—Haridwar,

Allahabad, Nashik and Ujjain. Kumbh Mela 2015 is being held in Nashik. More than 10 million

pilgrims and Sadhus with a prayer on their lips and a desire to attain freedom from the cycle of

life, a sea of humanity are expected to dip in the holy water of river Godavari. Kumbh Melas are

being held in India since ancient times. They are older than history. Even in ancient times when

transport facilities were next to nothing, thousands of men, women and children used to

converge for a holy bath from all corners of the country. Risk management strategies to tackle

stampedes during previous Kumbh Mela have failed consistently in India because of the large

crowds and the widening spread of the venues. Lakhs of devotees are expected to attend the

Kumbh mela this year and take a holy dip at various 'ghats', constructed on Godavari river bank

in Panchavati locality. Seven ghats have been established at Nashik. Eight Routes paths have

been proposed for Nashik and four for Triambkeshvar. These seven ghats are Takali Sangam

Ram Ghat, Nandur Ram Ghat, Dasak Ram Ghat, Lakshmi Narayan Ram Ghat, Rokdoba maidan

Ramghat ‐ Gouri patangan ghat, Gandhi Talav Ram Ghat and Talkteshwar Ghat. The

government officials and authorities have done micro planning to manage the huge crowd

efficiently. The arrangements of seven outer‐parkings has been made, where devotees coming

from different places like Mumbai, Dhule, Pune, Trimbakeshwar, Aurangabad, Gujarat and

others will park their vehicles . The devotees will park their vehicles in the outer parking. They

will have to reach ghats by Maharashtra State Road Transport Corporation (MSRTC) buses

which would be kept ready at the outer parking. The distance between outer parking and inner

parking is expected to be covered by State Road Transport Buses running over defined specific

path assigned. This research looks into a queuing model to build the relationship between no of

pilgrims and frequency of state transport on the particular route to minimize the risk of

blocking. Queuing theory is the study of queue or waiting lines. Analysis has been carried out

using queuing model include the expected waiting time in the queue, the average time in the

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system, the expected queue length as well as the probability of the system to be in certain

states, such as empty or full. The devotees will come to the outer parking with their own

transport channel then they have to get down and utilize the facility of state road transport,

this will be done in batches to avoid the blockage/traffic issue. From the inner parking devotees

will travel to the respective “ghats” by walk in performing their rituals of bath. They will again

come back to the inner parking to avail the facility of State Road Transport which will lead them

to the outer parking. The complete transport channel is divided into three systems, System 1

will be the flow of devotees from outer parking to the inner parking availing the facility of State

Shuttle Bus Transport, and System 2 will be the flow of devotees from inner parking to the

respective “ghats” which will be travelled by foot where the devotees can utilize the service of

Kumbh Bath / Kumbh Snan and then return back to the inner parking and the System 3 will be

the flow of devotees from the inner parking to the outer parking where devotees will avail the

facility of State Shuttle Bus Transport. The methodology proposed in this paper focuses on the

constant flow of pilgrims throughout the above planned channel and avoid blockage at any

location. Queuing model is used in this practical phenomenon to determine the

frequency/number of the State Road transport required at individual respective routes.

Queuing model will be used to determine the waiting time of devotees per hour at each of the

systems. The queuing model is simulated through Monte‐Carlo simulation using Crystal Ball

software for better solutions. This research will help the authorities to determine the frequency

of state shuttle bus transport required at both the system 1 and system 3. Thus they will deploy

the State Bus as per the requirement and frequency predicted. As the arrival of devotees will be

random at the eight route paths proposed for Nashik and four for Triambkeshwar, the

calculation of waiting time per hour and frequency of State shuttle bus transport will be

calculated for each individual route path proposed for Kumbh Snan considering the distance

between outer and inner parking for each proposed path. The objective of this study is to

introduce a new model for optimizing the flow/transportation of pilgrims between the outer

and inner parking location through the deployment of existing techniques in a new application‐

domain. This research can bring out the effective model where concerns of crowd safety

management, entry and exit systems, steady flow of crowd is maintained so that all the pilgrims

can utilize the service of Kumbh Bath / Kumbh Snan without any misfortune.

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68. Customer Roll out ‐ Operationalization of Customer Contract

Anil Choudhary, Himanshu Thakur, Kavin M Purpose – Design the Large Item Distribution Process and Streamlining and standardizing the

3PL and client operations

Design/methodology/approach ‐ Analysis of existing process of LID system. , data collection , Data Analysis , Designing of zones and sub zones depending upon the existing pin code., determining the number of lanes/pallets/inventory for each zone depending on the customer orders for LID region., designing of dashboard for automatic put‐away strategies, designing of MIS for tracking and visibility of current inventory ,execution and conclusion of new LID process. Findings – LID was the Prime bottleneck area of the warehouse, no standard process for LID put

away and picking area, multiple region items were placed on the same SKU causing difficulty in

picking process, multiple piling and random placement of the material was resulting into more

picking time and travel time of the pickers. ,No tracking of item stored in LID area result into

Item lost / not found , High customer delivery time of pepper fry last mile delivery, customer

dissatisfaction because of late delivery ,low productivity of pickers because of random

placement of materials.

69. Supply Chain Management: Asset Control and its impact on the value of

firm

Elvin Clements, Pratik Gupta, Vimal Singh

Purpose: The purpose of this research paper is to examine the effect of Supply Chain

Implementation using Logistics performance as a focal construct since it has implications on

both marketing and financial performances which ultimately impact the value of a firm.

Design/Methodology: A survey with questionnaires related to the various aspects of supply

chain strategy, logistics performance, marketing and financial performance was shared across

various operations and logistics managers. The responses from the respondents was collected

and a confirmatory factor analysis was conducted in locating the factors that affect the system

and in turn proving the hypothesis made. A correlation analysis was conducted to identify the

interrelationship among the various factors identified.

Findings: It has been proved that the logistics performance impacts the supply chain

management and its successful implementation impacts the marketing and financial

performance which are direct measures of supply chain performance. Hypothesis have been

proved using statistical measures which substantiate the hypothesis quantitatively.

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Research limitations/ implications: Scope of the research is limited to analysing logistics

performance alone assuming that other drivers/elements like supplier integration, sourcing,

inventory management, capacity utilization, etc., of supply chain management are constant and

not affecting the firm’s value to a great extent.

Implementation of Supply Chain Management would involve designing a supply chain network,

Planning and Coordinating Demand and Supply In a Supply chain, Planning and Managing

Inventories in a Supply chain, Designing and Planning Transportation Networks right from the

suppliers, manufacturers, transporters, warehouses, retailers and the customers and thus help

in creating flexibility and robustness of a supply chain. Logistics plays an important part in

efficient performance of supply chain. The lead time reduction for raw material, finished goods,

in‐plant transient goods, distribution and delivery greatly affect the overall organization’s

performance.

Practical Implications: Transportation alone accounts for up to 50 percent of the total logistics

cost and thus needs to be contained in improving the performances of the supply chain.

Originality/Value: This research demonstrates the impact of logistics performance to support

and advocate implementation of supply chain management which improves the

competitiveness and value of the firm.

Keywords: Supply chain management, organizational performance, logistics, statistical

modelling

70. Sector analysis‐An automotive supply chain model for demand driven

environment

Subhro ghosh, Sandipan Show, Manish Ghosh.

Purpose: The main aim of this paper is to study the challenge of demand management and

formulate a model to increase the efficiency of supply chain model and optimize the process to

cater to increasing demand of the automobile goods.

Design/methodology/approach: The efficient supply chain model has been developed. It

mainly comprises of the structure, components, the physical flow, operational planning and

processes and strategies of the supply chain model. Suppliers are usually located at different

locations and time taken by the suppliers to deliver parts may vary. Local suppliers may take

one or two days where as overseas suppliers may take several weeks. This may result in

stocking of parts to manage lead time and ever changing demand. To maintain lead time this

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model make use of supplier parks to cut down on lead time and fluctuations in demand. A

supplier park is the concentration of dedicated production, assembly, sequencing or

warehousing facilities run by suppliers or a third party in close proximity. It increases the

reliability of supply because the delivery time from finished component to assembly will not be

more than a few minutes. It makes the supply more reliable as it reduces the delivery time from

hours to minutes. Entire assembly of vehicles depends on timely delivery of the components.

Synchronous delivery is obtained by employing a decoupling point upstream the chain.

Decoupling point shows how customer order enters in goods flow. This arrangement ensures

synchronous sequential deliveries between second and first tier suppliers and first tier and

OEMs.This results in increased efficiency in vehicle manufactured. In this type of arrangement,

first tier‐supplier is located close to OEM site. This delivery between them is synchronized

sequentially. The second tier is shifted within the supplier park. This improves the

communication between first tier, second tier, OEMs for executing synchronous deliveries of

the products and also increases the ability to provide demand and production information.

Findings: The proposed model consists of three processes namely physical flow, operational

and planning processes and strategies. The physical process mainly deals with movement of

goods or information in transit or storage. In operational and planning tasks are performed to

guarantee proper physical flow. Strategies are employed to increase the efficiency and

responsiveness to changing market. This supply chain model will provide an environment of

high product variety. The customer receives the exact product specification required, with

ensured sales finished goods inventory and discounts, as well a reduction in stock obsolescence

risk. There is also balance between MTO and MTS which will help in maintaining stock levels

matching the market requirements.

Practical Implications: Though the proposed model is perfect example of responsive supply

chain its applicability is a question. The model is yet to be tested. The researchers have made

propositions and additional enhanced the model to make it more impressive. It can be

enhanced by practices like as JIT manufacturing, quick response, flexible manufacturing

systems, and vendor‐managed inventory (VMI).Furthermore supplier parks ensure close

proximity between the tier suppliers and the manufacturers.

Originality/value: The Applications of this model will ensure that Indian automotive sector is

able to cater the changing demand cycles and stays competitive in terms of flexibility as well as

strategies.

Keywords: overall equipment manufacturer (OEM), Make to order (MTO), Make to Stock

(MTS), Leagile, Vendor manage Inventory (VMI), Just‐In‐time (JIT).

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71. Performance Issues in Supply Chain Management Using SAP‐LAP

Framework: A Case Study Evidence from Manufacturing Industry

Akshay Gathekar, Hemant Gavale, Salman Mohammad

Purpose: The purpose of this paper is to analyze the case of Tasty Bite, a biscuit manufacturing

firm in India, status of its supply chain performance, issue identification and help provide

solutions and various associated tangibles and intangibles to bridge the gap. A situations‐

actors‐processes (SAP) learning‐action‐performance (LAP) analysis has been applied to identify

the various issues that need attention, compare current performance with the desired

performance, propose development plans and hence making the supply chain efficient and

effective.

Design/methodology/approach: SAP‐LAP is a holistic framework that blends hard systems and

soft systems paradigms. There is a pressing need to evolve a management approach which is

holistic and flexible in the light of dramatic change in various external factors of the business

environment and the corresponding change in the internal factors of the organizations. The

SAP‐LAP framework consists of three entities in any context, viz. a situation to be dealt with, an

'actor' or group of actors who deal with it and a 'process' or processes that recreate the

situation. In this framework, freedom of choice lies with the actor. A synthesis of SAP leads to

LAP which deals with learning, action and performance. We often encounter situations in

managing organizations and conducting management research to carry out an in‐depth inquiry

of the problem/case at hand for effective action.

Findings: The proposed inclusive framework of SAP‐LAP model is presented to capture the

whole Scenario of coordination to exploring the performance level of supply chain in the

manufacturing industry. It is based on the three key entities, viz. situation, actor and process

and takes the learning synthesis in terms of learning, action and performance. The framework

helps in identifying different coordination issues based on the relative importance of using

internal supply chain in the manufacturing industry.

Practical Implications: Logistics, sales and distribution –They use both inbound and outbound

logistics. When researched, it was found that outbound logistics are more complicated than the

inbound logistics. The whole phenomenon is managed through a mix of spoke and hub, where

the raw materials were taken from various vendors of one area in a truck and then supplied to

the factory unit. Vendor development strategy‐Tasty Bite incurs about (50‐60) % of the total

cost towards the procurement of raw materials like wheat flour, sugar, vegetable fat, liquid

glucose, milk powder, yeast, color, flavours, coconut, fat and packaging material

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Originality/value: The paper mainly looks at the application and execution of “SAP‐LAP

framework” in an Indian FMCG company for the supply chain management.

Key words: Situation‐ Actor‐Process (SAP), Learning Action Performance (LAP), Performance

measurement.

72. Strategic Alignment of future supply chain with existing supply chain of

LNG distributing organization in India

Parth Gandhi, Mayukh Saha, Navaneeth Surendran

Ronald H. Ballou in “The evolution and future of logistics and supply chain” states that “Before

1950’s firms might have organized key activities at that time in terms of the responsibilities and

objectives for marketing, finance, and production. This fragmentation led to conflicts among

those responsible for logistics activities with the result that, from the firm’s perspective, costs

and customer service were sub‐optimized. The reasons for this fragmentation were said to be:

a lack of understanding of key cost trade‐offs, the inertia of traditions and conventions, areas

other than logistics were thought to be more important, and the organization may have been in

an evolutionary state.” He also states that the earlier distribution network also intended to

have a manageable flow of resources and materials from its source to end consumer. With

network of multiple suppliers, manufacturers and customers increasingly cause constraints in

smooth flow, with limited or no co‐ordination of activities. The concept of total cost is used to

serve as the basis for managing certain activities, which were associated with flow of material

across the supply chain. Activities such as transportation and inventory control were managed

together because they were in cost conflict. Moreover the physical distribution and logistics

were embraced by both marketing and production areas, but have very less responsiveness

towards the issues of product flow. As a result, physical distribution and logistics started to

emerge as separate entity within business and further resulting in high logistics cost and

unrealized opportunity to optimize them.

With the advent of globalization created an urge for cost optimization. The globalization gave

way for MNC’s to have their product available in local market. Now the SCM is concerned with

realizing the opportunities from integrated management of product flow processes across

functions. This led to logistics being seen as subset of SCM. Earlier, the scope of logistics was

very much limited within the boundaries of the function of a firm. Inter‐functional and inter‐

organizational management seem to be within the purview of SCM rather than logistics.

Logistics as an identifying name supersedes physical distribution. Currently, SCM is practiced as

logistics and not the broad, theoretical scope envisioned for it. Perhaps managers will begin to

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practice SCM when its benefits are better documented and measured, and the techniques and

tools needed to achieve the benefits are refined. As new MNC’s are moving towards emerging

markets to establish supply chains based on the cultural, administrative, geographic and

economic distance of the host market, a new holistic relationship between manufacturer,

supplier and distributor have started to developed. The conflicting interests between

marketing, production and finance plans, is now foregone to realize the need for saving overall

cost optimization.

Thus, to understand the current changes and challenges of strategic alignment which

organizations of LNG distributing industry faces, with this paper tried to identify such issues and

mitigating solutions for the same. For the same purpose, we have considered ABC Ltd. a LNG

distribution organization, which is moving towards integrating its supplier network and

customer networks by working with the supplier and distribution. Its supplies come from gulf

countries and random tramp ships. The supplies are fulfilled with existing contracts between

their suppliers and ad hoc contracts based on urgent need of the customers. On account of high

lead times and LNG price fluctuation based on crude variation, existing contracts is detrimental

in optimizing the costs incurred. With exploratory research based approach on the content

available, the dimensions were validated for measuring performance of SCM. After analysing

through the AHP model, parameter for the current supply chain suggests a holistic outlook for

viewing supply chain. The paper brings out the evolution of supply chain by setting an example

of LNG distribution plant. The evolution would be majorly in terms of collaboration using the

KPI’s listed in the SCOR model as a performance evaluation metric and further setting the

agenda to reduce setup time in VSM. The essential non value added domains in VSM could be

further sketched after implementing measures and suggestions. The paper is a guideline to

improve the existing process at the LNG distribution plant.

73. Transporter selection using AHP analysis & Central warehouse Planning

Saqibullah Choudhary, Rohit Kapoor, Viraj Raut

Business environment is getting complex day by day. Coping with the complexity of today’s

business environment is not about predicting the future or reducing risk. It’s about building the

capacity, in yourself, your people, and the organization to adapt continuously and learn

speedily, in order to maximize the chances of seizing fleeting opportunities. Today, companies

are building strategies to achieve competitive advantage. Among these, warehousing is still

unlooked as a medium to gain advantage in this competitive environment.

In FMCG industry, there is great outward of materials having variety in dimension, weight,

packaging designs etc. A small improvement in warehousing/logistics operations increases the

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turnover, increasing the profitability of company but the constraint lies in finding these

improvements and implementing it.

Transportation cost is one of the major components of the supply chain cost. To reduce the

supply chain cost of an organization it is important to focus on this area. Using Analytical

Hierarchy Process as a tool, we evaluate the transporters on a number of criteria and provide a

framework for future selection of transporters, which further helped us in assigning fleets to

the transporters based on their ranking.

The paper depicts the route towards warehouse operations improvement by suggesting various

improvement strategies. There are about 450 different SKUs in Finished Goods warehouse to

be dispatched. Each part is completely studied & brainstormed and finally improvements were

filtered out. These improvements ultimately provide cost savings for the company.

Central warehouse strategy is made for the company as the drawbacks of different warehouses

are causing various problems to the organization in terms of lead time, cost and lose of orders.

Tool used for planning for central warehouse location is Load‐distance analysis.

74. Strategic Initiative for Supply Chain Management in Different Sectors.

Sanuj Das, Vishvas Luhana, Aditya Bhagwat

Purpose: The aim of this paper is to research the case of departments of the sectors,

particularly of health care (Care Pharma) sector and manufacturing sector (A1 chocolate

manufacturing industry), standing of its provide chain performance, issue identification and

facilitate other solutions and varied associated tangibles and intangibles to bridge the gap.

Methodology: This paper research is done on the stated problems and also the situation

analyzed for developing and delivering optimized solution to the organization. A situations‐

actors‐processes (SAP) learning‐action‐performance (LAP) analysis has been applied to spot the

assorted problems that require attention. Compare current performance with the required

performance; propose development plans and create the value addition to the available supply

chain model by enhancing economical and effective operation.

Findings: Cross sectional matrix giving the interdependency of assorted drivers among state of

affairs, Actor and method will be designed that provides an additional elaborate approach

towards the implementation of LAP (Learning‐Action‐Performance) measures. The self‐

interaction matrices represent the interdependency of the varied drivers among one another.

The dependency will be understood and also the level to that it's answerable for the

organization’s offer chain performance. The projected inclusive framework of SAP‐LAP model is

conferred to capture the complete state of affairs of coordination to exploring the performance

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level of providing chain inside the manufacturing trade. It supported the three key entities, viz.

situation, actor and technique and takes the coaching synthesis in terms of learning, action and

performance. The framework helps in characteristic altogether totally different coordination

issues supported the relative importance of victimization internal give chain inside the

manufacturing trade.

Practical implications: Management case studies are generally action oriented. After having

diagnosed the problem an action needs to be suggested. If one compares SAP‐LAP with

management case analysis frameworks like SWOT, VRIO then one finds that SAP‐LAP helps

understanding in roles that actors (key decision makers) play. No other framework talks about

actors and learning. In SWOT and RIO managers generally do not explain the learning which

accrues to them. SAP‐LAP framework gives tremendous clarity on the roles key decision

makers’ play, recommended actions, expected performance and learning which can carry

forward. No other framework provides these features. SAP‐LAP is an interpretive framework

that we can use as a case method in a context of management teaching, research and practices.

It is holistic yet simple framework that can be applied in a variety of contexts. It takes situation

as the driving element and takes into consideration the freedom‐of‐choice of actors. The

synthesis is learning centric. It can be extended by using it in a dynamic manner and by

interrelating various elements via SAP‐LAP linkages, which can be categorized by Interpretive

Ranking Process (IRP).

Keywords: Supply Chain; Supply Chain Management; Order Management; Vehicle Breakdown;

Shipment visibility; Vendor development strategy; Vendor quality control; SAP‐LAP; SAP‐LAP

Analysis; Self – interaction matrix; Cross‐ Sectional matrix

75. Extending Green Practices across supply chain: an empirical study

Ajay kaushik.

Introduction: In initial environmental management frameworks, operations managers were

involved only at small length. Separate organizational units had the responsibility for ensuring

environmental excellence in the fields of operations, product development, process design,

marketing, logistics, waste management and regulatory compliance etc. Today, this has

developed from the quality revolution of the 1980’s to the 1990’s supply‐chain revolution, it

has become clearer that the best practices call upon for the integration of environmental

management with the on‐going operations.

Green supply chain management (GrSCM) is attracting more interest among practitioners and

researchers of operations and supply‐chain management. The growing importance of Green

Supply chain management is driven mainly by the increasing deterioration of the environment,

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e.g. reducing raw material resources, superfluous waste sites and ever increasing levels of

pollution in the environment. However, this isn’t just about being environment ‐ friendly; but it

is about higher profits returns and good business sense. In fact, it should be a business value

driver and not like a cost centre. Moreover, consumer pressures and the regulatory

requirements are driving GrSCM. Hence, the scope of GrSCM ranges not only from a reactive

monitoring of the general management programmes but to a more proactive practices

implemented through various Rs (Reduce, Re‐manufacture, Re‐use, Re‐work, Re‐furbish,

Reverse logistics, Reclaim, Re‐cycle, etc).

Purpose: Our main objective is to present a detailed integrated view of the published literature

on all the aspects and facets of GrSCM, taking a ‘reverse logistics view’ so as to facilitate deep

study, practice and research on it .To meet this objective, we define a few relevant term to

understand the topic well. Qualitative analysis was applied to classify the existing literature on

the basis of problem context and the approach taken into consideration. We map the tools via

the problem context classification. Green supply‐chain management has its roots in both

supply chain management and environment management literature. Adding the ‘green’

component to supply‐chain management involves addressing the relationship and influence

between supply chain management and natural environment. Similar to the concept of supply‐

chain management, the limits of GrSCM is based on the goal of the investigator. The meaning

and scope of GrSCM in the literature has varied from green purchasing to an integrated green

supply chains flowing from the supplier to the manufacturer to the customer, and even the RL

GrSCM is defined as ‘integrating environmental thinking into supply‐chain management,

including material sourcing ,product design and selection, manufacturing processes, delivery of

the final product to the consumers also the proper end‐of‐life management of the product after

its useful life is over’. We basically focus on RL and mathematical modelling aspects in order to

prepare for further study and research work. Green design has been used remarkably in the

literature to mark the designing products with some unavoidable environmental

considerations. It is the well‐developed systematic consideration of design issues related with

health and environmental safety over the full product life cycle during process development

and new production Its scope entails many disciplines, including product safety, environmental

risk management, occupational health and safety, resource conservation, pollution prevention

and waste management. A green operations takes into consideration of all aspects related to

usage, handling, product manufacture/remanufacture, logistics and waste management as and

once the design has been finalized. A green manufacturing aims to minimize the ecological

burden by using appropriate technologies and material, while remanufacturing mentions to an

industrial process, in which worn‐out products are being restored to new‐like condition.

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Few characterize RL as 'the procedure of arranging, executing, and controlling the proficient,

practical stream of crude materials, in‐procedure stock, completed products and related data

from the purpose of utilization to the point of root with the end goal of recovering quality or

legitimate transfer', while some characterizes waste minimization as 'the lessening ... of

dangerous waste which is created (amid production and operations) or in this manner treated,

put away or arranged ...'.

Methodology: We classify the existing GrSCM literature into three different categories based

on the problem context in supply chain design which are highlighting the importance of GrSCM;

literature on green supply design; and literature on green operations to be taken. Green design

may be looked into from the viewpoint of environment conscious design and assessment of the

product and/or process into account. Similarly, green operations involve all operational aspects

relating to RL and network design (collection; inspection/sorting; pre‐processing; network

design), green manufacturing and remanufacturing (reduce; recycle; production planning and

scheduling; inventory management; re‐use, product and material recovery) and waste

management (reduction; pollution prevention; disposal). We do not consider literature and

practices relating to green logistics, the issues are more operational than the strategic in nature

and are not be significant in the supply chain design. We do not focus in detail on empirical

studies on GrSCM and literature on green purchasing, industrial ecology and industrial

ecosystems, as it is limited by our research design. We focus more onto the RL as the

establishment of efficient and effective RL networks is the prerequisite for profitable recycling

and remanufacturing.

The classification is for the easier understanding of different problem contexts of GrSCM – their

interactions, integration and relationships – in order to present a well‐defined and clear vision

for in‐depth analysis and research. It is not rigid, and there could be many overlaps (for

example, reduce gets focused not only in green manufacturing and remanufacturing, but also

elsewhere as to reverse logistics and waste management; green design, emphasizes reduced

use of virgin material and other resources on the platform. Similarly, green design should be

taken into account for the whole product life‐cycle costs, including those during manufacturing

and re‐manufacturing, reverse logistics and disposal for the same.

The target of this paper is to distinguish significant deals with green production network

administration exploration incorporating ecological speculation into inventory network

administration, and from that point, to arrange them to recognize gaps, issues and open doors

for further study and research. A writing audit is by all accounts a legitimate methodology, as it

is a vital stride in organizing an examination field and structures a fundamental piece of any

exploration directed. This distinguishes the theoretical substance of the field and aides towards

hypothesis improvement. Our exploration is driven by hypothetical pre contemplations and

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takes after a reasonable procedure, as this permits conclusions to be drawn on the checked on

writing. It might be delegated an archival examination technique in the system for leading and

assessing exploration. Our procedure of investigation contains the accompanying steps:

Defining unit of analysis: The unit of investigation has been characterized as a solitary

exploration paper/book. We further delimit the material (examination paper/book) to be

gathered according to our degree.

Classification context: We select and characterize the order setting to be connected in the

writing audit to structure and arrange the material. There are two settings: the issue

connection and philosophy/approach setting.

Material evaluation: The material is broke down and sorted by arrangement setting. This

permits ID of important issues and understanding of the outcomes. Issue setting and related

philosophy/methodologies permit grouping of the checked on writing, which can be inferred

deductively or inductively.

Findings: A lot of literature exists about various facets and aspects of GrSCM. Detailed reviews

on green design, production planning, repairable inventories and control for re‐manufacturing,

issues in green manufacturing and product recovery, reverse logistics (RL) and logistics network

design have been published in many works. Earlier reviews and works had a very limited focus

and narrow perspective. They did not cover adequately all the facets and aspects of GrSCM that

was required. Much of the work was empirical and did not focus much on network design

related issues and modelling.

Practical Implications: Our writing audit centers upon books, altered volumes and diary articles

just. To set up a period compass, a beginning stage was set at 1990. This appears to be

legitimized, as the start of the level headed discussion on GrSCM can be followed to this period.

Library databases were utilized where a watchword hunt utilizing some vital catchphrases, for

example, 'green store network', 'remanufacturing', 'green buying', 'green configuration',

'modern biology', 'mechanical environments', 'RL', "remanufacturing" and 'squander

administration' were directed. To delimit the quantity of distributions, observational papers

fundamentally tending to firm‐level or particular operational issues were prohibited from the

survey. Likewise, exceedingly specialized work on points, for example, life‐cycle appraisal, stock,

contamination counteractive action and dismantling was additionally barred from the survey.

Research with an exceptionally natural instead of production network point of view (green

buying, mechanical environment and modern biological systems) was additionally avoided. This

is by all accounts supported while considering the goal laid out, which focuses on incorporating

ecological deduction into store network administration. We utilize the distributed writing from

1990 onwards to do a reversal to different papers by cross referencing. As the distributed

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writing is interlinked to an extensive degree, one paper (stem) prompts others (branches). In

this way, when we get one string, we can discover others. As references collected, we found

that some of them were more focal and helpful than others. We consider such references as

original papers. These were additionally observed to be for the most part referenced various

times in consequent writing. Therefore, inside of our characterized objective, this work

incorporates and takes forward the writing on GrSCM since its conceptualization. Around 1500

books, articles from diaries and altered volumes have been secured.

76. Performance Measurement of supply chain: A Balance Score Card (BSC)

approach

PRS Sagar

Purpose: The main aim of this paper is to study the importance of performance measurement of supply chain using Balanced score card framework in Indian FMCG Industry. Design/methodology/approach: Performance management has become an important requirement for all the industries in different sectors. Unfortunately, many tools don’t exist to measure and monitor performance measurement of supply chain delivery effectively. Managers need accurate information to ensure that their decisions not based on feelings and speculations, but that the information with regard to service delivery is precise and relevant. So Balanced Scorecard (BSC) methodology is used to translate the organization’s strategy into performance objectives, measures, goals and initiatives. A precise balanced scorecard framework can predict the effectiveness of an organization’s strategy through a series of performance measures based on four perspectives of the framework including: Finance, Internal processes, customers, Employee growth and learning. Findings: Gap analysis for financial and non‐financial parameters of supply chain is done by Balanced score card framework and the results are shown using Radar chart. Regression analysis has been done .The findings of the study will be showing the importance of different perspectives of BSC in an organization. The findings will also include the interdependence of the parameters that have been measured and analyzed using various statistical tools where we can compare multivariate data. Different organizations have quite different needs, market areas, people, products and services, and will end up with significantly different balanced scorecards. Practical Implications: The balanced scorecard framework is balanced not only in one dimension of balance of measures of important areas of business, but also a balance between goals versus accountability. The people of the organization are the key to the success of the balanced scorecard system. Each organization must adopt a more balanced perspective in its performance measurement and management. Originality/value: The paper mainly looks at the application and execution of “Balanced Score Card Performance” in an Indian FMCG company for the supply chain management. Keywords: Performance measurement, Balanced Scorecard (BSC), Radar chart, four perspectives.

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77. Modeling Supply Chain Network Design and Product Recovery Planning

Under Demand Uncertainty

Apoorv Jha, Sana Ibrahim, Sudarshan K, Rohan Sharma

The backbone of any industry whether it manufacturing, FMCG, services etc. is their supply

chain network. It plays a very important role in defining the Key Performance Indicators (KPIs)

of that particular industry or firm. Supply chain network comprises of the complete SIPOC

diagram starting from the supplier to the end customer. Organizations are banking heavily on

making their networks leaner and more efficient.

With the ever changing dynamics of the global market and cut‐throat competition, we need to

take into account the major aspect that is the product differentiation and the demand

uncertainty. Product differentiation is a very critical aspect as it helps to set our product apart

from the rest of the market whether it is in terms of additional features, quality standards or

pricing. This involves offering delight to the customers in terms of product standard.

While talking about the supply chain network, it is very crucial to consider the demand

uncertainties related to the product. Right from the supplier to the end‐customer,

understanding the demand patterns helps by efficiently managing the following parameters:

Reducing the Lead Time at all the levels of the SIPOC cycle

Optimizing the inventory levels according to the requirements

Maintaining the quality standards as per norms

Developing the Master Planning Schedule (MPS)

Planning the production cycles

Implementation of the Pull view of supply chain based on Just‐In‐Time philosophy

There has been several research articles published to understand how organizations should

react to demand uncertainty by bringing the necessary changes in their supply chain design. For

instance, we can look into the AAA supply chain model (Hau L. Lee, HBR, 2004) especially

designed for products belonging to niche markets where the production is relying heavily on

the demand from the market.

Agility

Adaptability

Alignment

It involves the organizational commitment to quickly adapt and align their current practices to

the market dynamics.

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Another major work by Hau L. Lee (HBR, 2002) involves the framework design depending on the

demand and supply uncertainty related to a specific product.

H

Responsive Agile

Efficient Risk Hedging

L L Supply Uncertainty H

We can see how the organizations have to quickly adapt and change their supply chain models

according to Low‐High demand and supply uncertainties.

Another important point to note is that under what category we are placing our product, i.e.

functional or innovative. While efficient supply chain model is best suited for functional

products, the Responsive mechanism pays off well for innovative products. (Marshall Fischer,

HBR, 1997).

PROBLEM IDENTIFICATION

The major area where we need to work is the integration of the uncertainties at all the levels

and hence coming up with an optimal solution so as to address the issues of cross functionality

in a supply chain model.

Also, we will look into the transformational fundamentals used by the organizations for

adapting to the market requirements and changing their supply chain models for efficient

operations.

DESIGN METHODOLOGY

As we saw earlier that how business environment and market dynamics are forcing the

organizations to bring in the necessary changes in their supply chain models and adapt to the

customer orientations by understanding the product requirements and demand uncertainties.

We in this paper would be extending our research methodology by using statistical tools and

cross linking the different components related to understanding the demand uncertainty in the

market. We will also try to define the different models according to product classification and

business environment.

Another problem we will address through this paper is the seasonality or variations which need

to be eliminated at the preliminary level as they are the induced errors in the model.

Dem

and uncertainty

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Different forecasting techniques which we will see to understand the demand changes include:

Average Forecasting Method

Weighted Average Method

Exponential Smoothing Method

Regression Method

Next Generation Regression Model

Different inventory models, deterministic or probabilistic will be further linked to the demand

scenarios and other parameters which are cross functional will be included.

We will also try and incorporate the much talked about Big Data Analysis for supply chain

design. It is one of the current trending topics in this field comprising of gathering and analyzing

data available in the following formats:

Unstructured Data (Through Twitter, LinkedIn, News etc. comprising 80‐90% of the data)

Semi‐Structured Data (Interview, discussion with reports etc.)

Structured Data (Reports published by research agencies, organizations etc.)

This is important to integrate the information in hand for predictive modeling and analyze the

different supply chain models. For this, there are different tools which can be used including

the Goal Programming, Mixed Integer Linear Programming and Multivariate Statistics.

Findings: The approach adopted here for supply chain modeling is a dynamic one which will

depend on the priorities assigned as per the industry experts. Also, the demand forecasting

tools involved are of the continuous nature and help the organization to develop preventive

benchmarks. This approach can be adopted by managers for Critical‐To‐Quality (CTQ) issues

and analyze the functional domain involving the activities.

Research Limitations: This method simulates the basic priorities assigned by the functional

heads in an organization. However, the process needs to accommodate more parameters for

understanding the root cause and take corrective actions for the same with the use of the three

stage process involving identification, analysis and corrective action. Other areas which can be

involved include Flexible manufacturing systems (FMS) and how it can be effectively managed

using demand forecasting and product development.

Practical Implication: The methods adopted have been explained by using the data sets

available from the Indian manufacturing industry which imply the actual problems faced by the

companies under quality control. The assigned scores for different parameters of demand

uncertainties and product development are included while taking the functional areas in

consideration.

125 Page

Keywords: Lead time, Quality planning, Master Planning Schedule, Production system, Pull view

of supply chain, Demand forecasting, Critical‐to‐quality (CTQ), Next generation regression

model, Key performance Indicators (KPI).

78. A Comparative Study between AHP and TOPSIS to Prioritize Supply Chain

Flexibility Dimensions: A Case Study of Indian FMCG Sector

Shreyash Bansal, Nupur Prajapati

This is a comparative study between AHP and TOPSIS methodologies to prioritize the supply

chain flexibility dimensions (extracted from literature) in Indian FMCG industry. Authors have

visited the case firm to have an idea of issues related to flexibility. Flexibility is the ease by

which an organization can adapt or change itself to the changing business environments and

customer needs. It is the ability of a system to respond to internal or external changes which

may affect its value delivery in cost effective and timely manner. Flexibility enables an

organization to swiftly respond to any uncertainty by sustaining its output and profitability.

These uncertainties may be in a form of a risk or an opportunity, in former case the primary

objective of flexibility becomes to sustain while in the latter case the primary objective is to

increase or enhance the value delivery system of the organization. Thus, being flexible has

helped many organizations to pass the test of the time with flying colors. The factors of

changing consumer behaviors, frequent innovations in technologies across various domains and

raging price wars have made flexibility the need of the hour. One such industry which is

constantly driven by these factors is the Fast Moving Consumer Goods or FMCG industry. To

thrive in the unpredictable, uncertain and turbulent modern business environment flexibility in

supply chain is must.

To carry out this study authors have done extensive literature review and extracted supply

chain flexibility dimensions, most suited for Indian FMCG firm, accordingly designed the self‐

administered questionnaire and floated it among executives of case industry. The feedback

authors received in terms of filled up questionnaire become the input of data analytics using

AHP and TOPSIS, and finally designed the structured hierarchy of supply chain flexibility

dimensions. This study will help firm to understand which area to focus upon the most to make

firm’s supply chain flexible enough to cope up with uncertainties present in external

environment.

Key words: Supply Chain Flexibility, FMCG, AHP, TOPSIS, Uncertainty.

126 Page

79. A combined AHP‐ANP approach to evaluate supply chain of electronic

business

Abhishek Tuli, Ankit Karir

Purpose: The purpose of this study is to solve the issues in supply chain network with the

integration of Operation Management models and E‐Business and to provide the real time

solution to Wrangler that witnessed the decline in sales and market share, which was once

highly successful and highly competitive in the denim jeans market. Wrangler identified that

product was not conveniently available to the customers.

Methodology: This problem includes both tangible and intangible criteria therefore analytic

hierarchy process (AHP) is accepted as the methodology and to identify the interdependency

between these criteria analytic network process (ANP) is used.

Findings: According to our observations by using different OM models, it was found out using

AHP that Future group emerged as the most important criteria followed by Westside and

Reliance retail for managing the distribution network of Wrangler products. Dependency

among the different criteria was identified using ANP.

Originality/Value: In this study we implemented various OM models to a real world supply chain

problem. The results that we obtained were considered acceptable and feasible by the decision

maker.

Practical Implications: This robust technique for the effective use of E‐business with OM models

as a backbone in supply chain network can be used in any sector for effective use of resources

and achieving customer satisfaction.

Keywords: AHP, ANP, Supply chain management, E‐Business.

80. Identifying dimensions of Student Support Systems in eLearning courses

and their causal relationship using AHP and DEMATEL

Prashant Barge

Today’s business environment is supported by e‐activities, up to the extent that no business is

possible to have maximum profitability without availing e services. Today “E” is everything: e‐

commerce, e‐business, e‐banking and e‐learning also (Richard N. Katz and Diana G. Oblinger

2000). The ocean of “E”, a world where the Internet, Internet of Things (IOT) and the Big Data

with Cloud technology is changing the ways people work and the ways businesses operate on

127 Page

all levels. We are talking of SMART World with SAMRT Cities, which is possible now using

Internet of Things (IOT).

Many universities across the world want to improve the performance of their e‐Learning

initiatives in this e‐era. The Student Support Services in e‐Learning has major role and is major

component as discussed and proved by many researchers (Alias 2005). As mentioned by Sener

and Humbert (2003); student satisfaction is vital element in successful e‐Learning program.

Students’ satisfaction ultimately leads to completion of the course. This in turn helps to reduce

the attrition rates in e‐Learning course.

The purpose of this paper is to identify the key variables of Student Support Services through

Systematic Literature Review (SLR). Further attempt has been made by authors to establish the

causal relationship among selected constructs of Student Support Services using Analytic

Hierarchy Process (AHP) and DEMATEL.

The study has employed AHP and DEMATEL to develop a Student Support Services framework

and formulated strategy to implement in Indian scenario.

Our key objectives of this research paper are:

• To identify key variables for Effective Student Support Systems (S3) in eLearning Courses,

• To explore conceivable linkage among these dimensions; and

• To propose new Student Support Systems (S3) framework to increase student satisfaction in

eLearning courses.

Research Methodology: Based on the AHP process; following phases are followed by the

researchers to prioritize strategic areas (Categories) and sub factors (Attributes) used for this

study. AHP provides a framework to cope with multiple criteria situations involving intuitive,

rational, quantitative and qualitative aspects for such study.

In the next section of research, authors have established a structure for identifying the

evaluation attributes and factors as well as their relationships. This study presents not only the

priority of attributes and factors within each attribute but also the cause and effect relationship

between them using DEMATEL. DEMATEL analytical technique was used to determine the

causal relations and to identify the significant attributes and factors which consists those

attributes.

Future Application of proposed research:

1: To reduce the attrition in the e‐learning courses

2: To increase the satisfaction of e‐learners

128 Page

3: To develop the better e‐learning courses considering personalization

81. The Role of Information Uncertainty on Cement Industry‐ (Using

Combined AHP‐DEMATEL Analysis)

Rohit Singh, Jitendra Vishnolia, Anand Singh, Jigar Gajjar, Udgar Antani

Implementation of Sustainable manufacturing into products and processes has become the

necessity of major cement manufacturing industries as Cement Manufacturing process

comprises of consumption of raw material, energy, and major source of pollutants. Thus in this

research the role of information uncertainty in the Key performance indicators of the

Sustainable Cement Manufacturing process is evaluated based on the triple bottom line of

sustainability.

Sustainable manufacturing should be integrated and evaluated with respect to the three

indicators of environmental, social, and economic, known as the triple bottom line of

sustainability.

The society’s infrastructure construction around the world uses the fundamental building

material Cement which is the most important ingredient of concrete. Generally, the cement

plants are characterized as an intensive consumer of natural raw materials and fossil fuels, and

hence are remarked as emitters of pollutants. According to United Nations Environment

Program report, due to an ever increasing demand for the building sector; the annual growth

rates of cement is about 6% for cement but at the same time these industries caused about 6%

of global greenhouse gas emissions. Therefore, evaluating sustainable manufacturing has

become a necessity for this industry. This reflects the crux of our case.

Generally, the cement plants are categorized as a concentrated consumer of natural raw

materials and fossil fuels, and has observed as emitters of pollutants. Therefore, assessing

sustainable manufacturing has turn out to be a requirement for this industry.

In this study, an attempt was carried out to rank and to establish relationship between

indicators commonly used in sustainable manufacturing evaluation. This paper proposes a set

of Key Performance Indicators (KPIs) for assessing the sustainable manufacturing assumed to be

suitable to the cement industry. The KPIs are then used to develop an assessment model of

sustainable manufacturing.

Multiple criteria decision making (MCDM) refers to making decisions in the presence of

multiple, typically conflicting, criteria. MCDM problems are common in everyday life.

129 Page

Issues related to MCDM are most common, MCDM as a discipline exclusively encompasses a

relatively short history of concerning thirty years.

This research helps in prioritizing the performance indicators and to analyze the relationship

between these indicators using “Analytic Hierarchy process” (AHP) and “Decision‐making Trial

and Evaluation Laboratory” (DEMATEL).

The Analytic Hierarchy Process (AHP) is a multi‐criteria decision‐making approach and was

introduced by Saaty (1977 and 1994).The analytic hierarchy process (AHP), as proposed by

Saaty is a later development and it has recently become popular. Recently modification to the

AHP is considered to be more consistent than the original approach.

Sustainable manufacturing is certainly one of the critical issues for the cement industry.

Cement, as the most important ingredient of concrete, is a fundamental building material for

society’s infrastructure construction around the world. The Analytical Hierarchy Process (AHP)

methodology is applied to weighting the KPIs and prioritize them. It is believed that the

proposed KPIs and the evaluation model enable and assist the cement industry in effort to

increase their sustainable manufacturing performance.

The prioritized KPIs are then checked for interdependency between the indicators by the help

of DEMATEL another approach of Multi criterion Decision‐Making (MCDM).

DEMATEL is functional to examine and build the relationship of cause and effect among

assessment criteria (Yang et al., 2008) or to develop interrelationship among indicators (Lin and

Tzeng, 2009).

The key performance indicators are identified and classified into three categories: Economic,

Environmental and Social factors. The DEMATEL method will be used to identify dependency of

the performance indicators and the AHP multi criteria decision making (MCDM) approach will

prioritize the indicators, which will support in project decision making and rank the alternatives

in a preferred order. This priority and relationship will help the cement industry to achieve

higher performance and better competitiveness.

The Key Performance Indicators classified on the basis of triple bottom line:

1. Economic Factors

Material Cost

Inventory Cost

Labour Cost

Product Delivery

Raw Material substitution

130 Page

2. Environmental Factors

Air Emission

Energy Consumption

Fuel Consumption

Material Consumption

Noise Pollution

Non‐product Output

Water Utilization

Land Utilization

3. Social Factors

Accident Rate

Employee Involvement

Labour Relationship

Gender Equity

Occupational Health and Safety

Training and Education

Out of the Triple Bottom line of sustainability one is the traditional measure of corporate

profit—the “bottom line” of the profit and loss account. The second is the bottom line of a

company's “people account”—a measure in some shape or form of how socially responsible an

organization has been throughout its operations. The third is the bottom line of the company's

“planet” account—a measure of how environmentally responsible it has been. The triple

bottom line (TBL) thus consists of three Ps: profit, people and planet. It aims to measure the

financial, social and environmental performance of the corporation over a period of time. Only

a company that produces a TBL is taking account of the full cost involved in doing business.

Thus, for sustainable cement manufacturing Process the key performance indicators are

classified on the basis of Triple Bottom line of sustainability.

Firstly the KPIs will be rated by managers of production and manufacturing unit of Cement Plant

for sustainable manufacturing assessment in the cement industry. The outcome of the

Response from ten managers of leading manufacturing Cement Industries will be evaluated for

prioritization through AHP method.

Once the priority is decided the DEMATEL method is applied to analyze and form the

relationship of cause and effect among evaluation criteria or to derive interrelationship among

factors. The DEMATEL method converts the relationship between the causes and effects of

criteria into an intelligible structural model of the system. The questionnaire will be developed

and sent to different managers or responsible persons to understand their opinion and

131 Page

relationships as per their point of view. Response of the concerned managers will be averaged

out and normalized to build the DEMATEL model.

The outcome of the AHP approach will prioritize the KPIs. The proposed KPIs and the evaluation

model will enable and assist the cement industry in effort to increase their sustainable

manufacturing performance. Whereas the DEMATEL approach will define the interdependency

of the KPIs on one another.

It has been reported that those companies adopting sustainable practices are able to achieve

better product quality, higher market share, and increased profits. Hence lower the information

uncertainty, better evaluation of above mentioned Key Performance Indicators (KPIs). This

priority and relationship will help the cement industry to achieve higher performance.

Keywords— Sustainable manufacturing, Key performance indicators (KPI), Analytic Hierarchy

process (AHP), Decision‐making Trial and Evaluation Laboratory (DEMATEL).

132 Page

Authors’ Index

Paper ID

Author Affiliation Paper Title

36 Mrunalini Dodkey

SIOM Nashik

Integrating SME’s of Indian Switchgear and Transformer Industry using Lean Supply Chain Management Practices

38 Arshiya Mahajan

self(student)

Green Evolution in Hospitality Management

39

Dr. Anil Kumar BML Munjal University

Deciding the vendor selection criteria for capital procurement

Dr. Manoj Kumar Dash

Indian Institute of Information Technology & Management

40

Ridhima Arora

BML Munjal University

Utilization of big data to enhance speed of idea generation

Dr. Anil Kumar


Dr. Shrawan Kumar Trivedi


41 Manish Verma

McMaster University, Canada

A framework for locating and equipping marine oil‐response facilities

42 Manish Verma

McMaster University, Canada

An analytical approach to rail‐truck intermodal transportation of hazardous materials with capacity selection & terminal congestion

43

Pankaj Sharma

IIT Delhi

Idea for a Lean‐Agile supply chain for the Armed Forces

Makarand Kulkarni

IIT Bombay

133 Page

44

Dr Ashok Matani

Government College of Engineering, AMRAVATI

Synchronizing Electrical Energy Generation and Distribution Supply Chains

45

Dr Ashok Matani


Greener Supply Chains Towards Environmental Protection in Food Processing Industries

46

Karuppanna Prasad N

TVSTS Ltd, India A review on the experimental usage of classical, Shanin and Taguchi design of experiment (DOE) with Data Mining approach using six sigma DMAIC.

Sekar K

NIT‐Calicut

Manohar M

ISRO, India

47 Anil Sathe

ACE SCM Solutions, India

Performance Measurement of supply chain: a changing paradigm

48

Haimanti Pal

JADAVPUR UNIVERSITY

Optimal replenishment policy and preservation technology investment for a non‐instantaneous deteriorating item with stock‐dependent demand

Sudarshan Bardhan

HALDIA INSTITUTE OF TECHNOLOGY

Bibhas Giri

JADAVPUR UNIVERSITY

49

Protik Basu

Army Institute of Management Role of HR in Lean Manufacturing

Implementation – a Comprehensive Study Pranab K Dan

Indian Institute of Technology Kharagpur

50

Sudarshan Bardhan

Jadavpur University

Coordinating a Three‐echelon Supply Chain with Uncertain Demand and Random Yield Bibhas Giri

Jadavpur University

134 Page

Tarun Maiti

Jadavpur University

51

Kalidas K

Hindusthan Institute Of Technology

Investigations on raw material supplier selection methodology using fuzzy logic K. Sundaraj

52

Naveen Jain

National Institute of Technology, Raipur

A Hybrid model based on SWARA and WASPAS MCDM methods for supplier selection

Amitraj Singh

National Institute of Technology, Raipur

Akhilesh Kumar Choudhary

IIITDM, Jabalpur, India

53

Vikas Thakur

IIT, Roorkee Questionnaire survey on various issues of

healthcare waste management in India

Ramesh Anbanandam

IIT, Roorkee

54

Yuvraj Gajpal

Asper School of Business, University of Manitoba, Canada

Routing Alternative Fuel‐powered Vehicles for Garbage Collection

Shuai Zhang

University of Manitoba, Canada

Mohamed Abdulkader

Department of Mechanical Engineering, University of Manitoba, Canada

S. S. Appadoo

Asper School of Business, University of Manitoba, Canada

55 Sneha Kumari

Symbiosis International University

Role of Big Data in Decision Making

135 Page

Shirish Jeble


Yogesh Patil


56

Minal Uprety

Prestige Institute of Management & Research, Indore

Service Quality in Selected Hospitals in Indore City: An Empirical Study

Sonam Mathur


Sarfaraz Ansari


57 Rohit Titiyal

IIT Kharagpur

Reverse logistics network design and re manufacturing using new module supplier

58 Ajith Kumar

XLRI Xavier School of Management

A tabu search heuristic with discrete‐event simulation for scheduling staff in call centers

59

Dr. Vivek Agrawal

GLA University, Mathura

ISM Based modeling of supply chain management enablers

Professor Anand Mohan Agrawal

GLA University, Mathura

Sucheta Agarwal

Indian Institute of Technology, Roorkee

60 Brojeswar Pal

The University of Burdwan

Price and credit period sensitive competitive supply chain model

136 Page

61

Dr Ashok Matani


Ergonomics enhancing agricultural systems productivity

63

Dr. Vandana Sonwaney

SIU Application of TQM in Resolving E‐Commerce

Challenges in Rural Markets Sunny Oswal

SIU

65

Rajeev Sharma

Birla Institute of Management Technology

An Examination of Supply Chain Performance Factors based on the Quality of Relationships

Gaurav Tripathi

Birla Institute of Management Technology

67

Anand Sasikumar

Research Scholar,NITIE(National Institute of Industrial Engineering)

Moderating the effects of Lean manufacturing: A contextual framework with respect to process industry

Dr. Padmanav Acharya

Associate Professor, NITIE(National Institute of Industrial Engineering)

68 Dr Parikshit Kala

COER SCHOOL OF MANAGEMENT

Logistics Management: Opportunities and Challenges with Reference to Selected Organizations

69

Mohit Agrawal

BITS Pilani A System Dynamics Modeling Framework for Sustainable Supply Chain Management

Abhijeet Digalwar

BITS Pilani

70 Gopalakrishnan Narayanamurthy

Indian Institute of Management Kozhikode

Does magnitude of penalties matter? An empirical investigation in the healthcare context

137 Page

Rachna Shah

Carlson School of Management, University of Minnesota, USA

71

Vilas Nair

SCMS COCHIN SCHOOL OF BUSINESS

Category Management: Enriching Customers private label purchase

Dr Susan Abraham

SCMS COCHIN SCHOOL OF BUSINESS

72

Shiba Parhi

SIOM Nashik

Assessing Risk by the High Net worth Investors of India in Financial Decision

Dr Mohammad Khalid Azam

Bett of Business Administration , AMU, Aligarh

Dr M Venkateshawrlu

NITIE, Mumbai

73

Shiba Parhi

SIOM Nashik

Application of Behavioral Finance and econometrics to understand the High Net worth Individuals investors during Uncertainties and Risk in India

75 Karan Venkatesh

KK wagh

Application of optimizing techniques in Indian auto ancillary industries for SCM

76

Dr. Shilpa Parkhi

SIOM

Building the foundation for Supply Chain Costing by identifying and prioritizing the elements involved using Topsis.

Gary Cokins

United States

77

Krishana Kant Shukla

HAL Nasik

Military Aircraft lrus with MRO Supply chain improvement: Self Reliance in Aircraft MRO business and Sustainability for future

Ravindra Kumar Chauhan

HAL Nasik

Umashankar Aland

HAL Nasik

Prakash Joshi

HAL Nasik

138 Page

78

Dr. Shilpa Parkhi

SIOM

Redesign of Supply Chain Network of Footwear Manufacturing Company and impact of GST using Sensitivity Analysis tool

Udgar Antani

SIOM

79 Savitha Swaminathan

SSN college of Engineering

Energy efficient reconfigurable architecture for motion estimation in video coding

80

Pranav Dange

RCOEM Nagpur

Lot‐Sizing for Forecasted Demand at Metal Finishing Industry

Pranay Daharwal

RCOEM Nagpur

Pravin Tambe

RCOEM

81

Nishant D. Singh

Fracktal Works Private Limited

Vendor Rating & Inventory Management in an Indian Start‐up: A combined AHP‐TOPSIS approach

Dr Rohit Singh

Symbiosis institute of Operations Management

Chetan Saxena

Symbiosis Institute of Operations Management

Naman Singh

Symbiosis Institute of Operations Management

82

Rishabh Dua

Delhi Technological University, Bawana, Delhi

Demand forecasting, Economic Order Quantity and Reorder point calculation of a hypothetical company producing solar panels

Tanusha Sharma


Kartik Gupta


139 Page

Puneet Bhatia


84

Shubham Kakde

Ramdeobaba College of Engg. and Management, Nagpur

Research on Procurement Management of MSE using system dynamics methodology

Manas Agrawal


Lakshman Suthar


85

Pravin Tambe

RCOEM, Nagpur

Approaches for combining operational decisions for maintenance and quality control: A review

Makarand Kulkarni

IIT Bombay

86

Navneet Vidyarthi

John Molson School of Business, Concordia University, Canada

Multicommodity Network Design under Congestion

Sachin Jayaswal

Indian Institute of Management, Ahmedabad

Sagnik Das

University of Illinois at Urbana‐Champaign, Urbana, IL, USA

87 Saroj Koul

Jindal Global Business School

Stepping on the Scale: SOLAS’ Container Weight Amendment

88 Arijit Poddar

IISWBM , Kolkata

Benefits & Scope of GPS in Logistics and in Different Works of Life

89 Jitendra Vishnolia

SIOM, Nashik

Kumbh Mela: Nasik City Logistics study of the state shuttle‐bus transportation system using

140 Page

Rohit Singh

SIOM, Nashik

simulation approach

90

Sandeep Kumar Gupta

IIT Kanpur

Interdependence among dimensions of Sustainable Supply Chain: evidence from Indian leather industry

Uday S. Racherla

IIT Kanpur

91

Dr. Rohit Singh Symbiosis Institute of Operations Management, Nashik

Supplier Selection Using Combined SWARA and WASPAS – A Case study of Indian Cement Industry

Jitendra Vishnolia

Jigar Gajjar

Anand Singh

92

Sonal Surabhi

Symbiosis Institute of Operations Management, Nashik

Extending Green Practices in Supply Chain Management

Suman Sowrabh

Aditya Dubey

Yashomandira Kharde

Dr. Rohit Singh

93

Sunil Das Symbiosis Institute of Operations Management, Nashik

Lean Production Supply Chain Management as Driver towards Enhancing Product Quality and Business Performance

Arun Koonammave

Prasanjit Biswal

94

Ashish Yadav Symbiosis Institute of Operations Management, Nashik

Lean Supply Chain in Manufacturing Unit using Value Stream Mapping

Ashwini Awale

Md. Zoheb Mehraj

95

Akansha Rammaiya


Supply chain performance measurement framework for small and medium scale enterprises.

96

Akshay KumarSymbiosis Institute of Operations Management, Nashik

Lean assessment parameters and roadblocks in implementation of Lean Management in Indian Auto component Industry: A combined AHP & MICMAC approach

Rohit Singh

Tanmay Borulkar

Partha Paramanik

97 Pooja Shah


Benefits, Challenges and Bridges to Effective Supply Chain Management

99 Yashomandira Kharde


Digital Retail: A Sustainable Opportunity

141 Page

Prasad Madan VSS College, Jalna

Sonal Surabhi


Pravin Kharde VSS College, Jalna

100 Ayona Chakraborty


A Comparative Study on Automation Feasibility across Two Tools and Report Benefit Assessment

101

Preeti Shri Agrahari Symbiosis Institute of Operations Management, Nashik

New product development through quality function deployment Takshil Nagar

102

M. Parthasarathi Symbiosis Institute of Operations Management, Nashik

Interpretive Structural Modeling of Supply Chain Risks in a Manufacturing Firm

Ravina Gautam

Kunal Pawar

103

Moumita Saha Symbiosis Institute of Operations Management, Nashik

Evaluation of Supplier(s) for an Automobile Firm Vivek Alamadi

Aditya Bapat

Sudhanshu Pandey

104 Shrikant Shinde


A case on Business Process management

105

Shiladitya Adhikary Symbiosis Institute of Operations Management, Nashik

Overall Equipment Effectiveness (OEE) to increase productivity of work centre

Arijit Roy

Bir Pratap Singh

Sourav Ghosh

106

Pradeep Kumar Jain


Risk Analysis in Global Supply Chain Management: Application of AHP and DEMATEL.

Prasang Jain

Tarun Garg

Akshay Gupta

107

Basavaraj Koulapur Symbiosis Institute of Operations Management, Nashik

Process development using ISM in Ecommerce business

Sudipto Sinha

Eshwar Pasarge

Vivek Munshi

108

Priya Daware Symbiosis Institute of Operations Management,

Identification and evaluation of parameters affecting ERP System Implementation in a manufacturing firm

Videtha Ghai

Mayank Mehrotra

142 Page

Saikat Chandra Nashik

109

Nirmal Shah Symbiosis Institute of Operations Management, Nashik

Interpretive Structural modelling of Supply Chain Risk Management

Nikhil Mohite

Ashish Nannaware

Vishesh Khandelwal

110

Jitendra Vishnolia Symbiosis Institute of Operations Management, Nashik

Kumbh Mela: Nasik City Logistics study of the state shuttle‐bus transportation system using simulation approach

Rohit Singh

111

Anil Choudhary Symbiosis Institute of Operations Management, Nashik

Customer Roll out ‐ Operationalization of Customer Contract

Himanshu Thakur

Kavin M

112

Elvin Clements Symbiosis Institute of Operations Management, Nashik

Supply chain management: Asset Control and its impact on the value of firm

Prateek Gupta

Vimal Singh

113

Subhro ghosh Symbiosis Institute of Operations Management, Nashik

Sector analysis‐An automotive supply chain model for demand driven environment

Sandipan Show

Manish Ghosh

114

Akshay Gathekar Symbiosis Institute of Operations Management, Nashik

Performance Issues in Supply Chain Management Using SAP‐LAP Framework: A Case Study Evidence from Manufacturing Industry

Hemant Gavale

Salman Mohammad

115

Parth Gandhi Symbiosis Institute of Operations Management, Nashik

Strategic Alignment of future supply chain with existing supply chain of LNG distributing organization in India

Mayukh Saha

Navaneeth Surendran

116

Saqibullah Choudhary


Transporter selection using AHP analysis & Central warehouse Planning

Rohit Kapoor

Viraj Raut

117

Sanuj Das Symbiosis Institute of Operations Management, Nashik

Strategic Initiative For Supply Chain Management In Different Sectors

Vishvas Luhana

Aditya Bhagwat

143 Page

118

Ajay kaushik


Extending Green Practices across supply chain: an empirical study

119 PRS Sagar


Performance Measurement of supply chain: A Balance Score Card (BSC) approach

120

Apoorv Jha Symbiosis Institute of Operations Management, Nashik

Modeling Supply Chain Network Design and Product Recovery Planning Under Demand Uncertainty

Sana Ibrahim

Sudarshan K

Rohan Sharma

121

Shreyash Bansal Symbiosis Institute of Operations Management, Nashik

A Comparative Study between AHP and TOPSIS to Prioritize Supply Chain Flexibility Dimensions: A Case Study of Indian FMCG Sector

Nupur Prajapati

122

Abhishek Tuli Symbiosis Institute of Operations Management, Nashik

A combined AHP‐ANP approach to evaluate supply chain of electronic business

Ankit Karir

123 Prashant Barge


Identifying dimensions of Student Support Systems in eLearning courses and their causal relationship using AHP and DEMATEL

124

Rohit Singh Symbiosis Institute of Operations Management, Nashik

The Role of Information Uncertainty on Cement Industry‐ (Using Combined AHP‐DEMATEL Analysis)

Jitendra Vishnolia

Anand Singh

Jigar Gajjar

Udgar Antani

144 Page

Leadership

HONORARY PATRON

(FOUNDER PRESIDENT – SYMBIOSIS SOCIETY,

CHANCELLOR – SIU): Prof. (Dr.) S. B. Mujumdar

HONORARY PATRON (PRINCIPAL DIRECTOR – SYMBIOSIS SOCIETY): Dr. Vidya Yeravdekar

CHIEF PATRON (VICE CHANCELLOR – SIU): Prof. Rajani Gupte

Organizing Team

PATRON (DIRECTOR – SIOM, NASHIK): Prof. Vandana Sonwaney

CONVENER (FACULTY, SIOM): Prof. Rohit Singh

CO‐CONVENER (FACULTY, SIOM): Prof. P.A Ratna

ORGANIZING SECRETARY (FACULTY, SIOM): Prof. Rohit Singh

Prof. Aditi Mishal

Prof. Rishabh Jain

ORGANIZING COMMITTEE MEMBERS (FACULTY, SIOM): Prof. Shiba Parhi

Prof. Surendra Kansara

Prof. Yashomandira Kharde

Prof. Prashant Barge

Prof. Mrunalini Dodkey

Prof. Aasha Sharma

Prof. Shilpa Parkhi

145 Page

STUDENT CONVENER (STUDENTS, SIOM): ‐ Jitendra Vishnolia

Sriparna Nandi

Arun Goyal

Sonal Surabhi

STUDENT SECRETARY (STUDENT, SIOM): Rohit Pande

VERTICAL HEADS (STUDENTS, SIOM): Himanshu Thakur

Avinash Karthik

Chetan Saxena

Jigar Gajjar

Aditya Bhagwat

Anand Singh

Rahul Mishra

Manish Puri

Abstract Proceedings ICOSCM 2016 - RCOSCM | … · 2016-08-19 · Moderating the effects of Lean...

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Transcript of Abstract Proceedings ICOSCM 2016 - RCOSCM | … · 2016-08-19 · Moderating the effects of Lean...