CRITICAL SUCCESS FACTORS FOR SIX SIGMA DESIGN AND ... · CRITICAL SUCCESS FACTORS FOR SIX SIGMA...
Transcript of CRITICAL SUCCESS FACTORS FOR SIX SIGMA DESIGN AND ... · CRITICAL SUCCESS FACTORS FOR SIX SIGMA...
CRITICAL SUCCESS FACTORS FOR SIX SIGMA DESIGN AND DEPLOYMENT TO COMPLIMENT
LEAN OPERATIONAL STRATEGY TOWARDS CAPABILITY MATURITY
A. Vermeulen
Post Graduate School Engineering Management
University Of Johannesburg, Auckland Park, Johannesburg, Gauteng, South Africa
JHC. Pretorius
Post Graduate School Engineering Management
University Of Johannesburg, Auckland Park, Johannesburg, Gauteng, South Africa
A J. Viljoen
Post Graduate School Engineering Management
University Of Johannesburg, Auckland Park, Johannesburg, Gauteng, South Africa
ABSTRACT
PURPOSE OF THE PAPER
To integrate Six-Sigma and Design For Six Sigma (DFSS) includes different strategies and are critical
success factors when implementing internal processes. The research objective is to (i) critically
analyse critical success factors (CSF’s) impacting on the integration of Lean Six Sigma (LSS) and DFSS
as they are frequently misunderstood and applied in industry and to (ii) develop a framework
guiding organisations towards operational excellence complemented by Lean operational strategy
(LOS) applications when utilising Six Sigma and DFSS.
The design of the “newly” develop framework links together “synergistically” key components
impacting on the successful implementation thereof supporting Capability Maturity Model
Integration (CMMI) in terms of a business strategy. The framework also integrated the Theory of
Constraints (TOC), Agile and Scrum, Lean Six Sigma (LSS), Design for Six Sigma (DFSS) in a multi-
framework capability maturity model.
RELATED WORK
Literature shows that original equipment manufacturers (OEM’s) in Europe, Japan and America has
been giving rise to fundamentally disseminate the core concepts and opportunities within Lean,
Six-Sigma and Design for Six Sigma (DFSS) to fundamentally drive operational excellence
throughout the product and process life cycle. Numerous examples exist over the past two
decades in the automotive manufacturing industry where it is observed that during the design
phase of products and processes that critical success factor (CSF’s) of DFSS does not fully unlock
the opportunity towards performance and operational excellence.
RESEARCH DESIGN
The nature of this research is primarily exploratory and descriptive (Cooper, D.R. Shindler. P.S.
(2011). The main elements of the research are formed by Phase 1 by means of thorough literature
reviews in terms of Industry4.0 technologies in Six-Sigma, DFSS, Lean Six-Sigma (LSS) and CMMI.
Phase 2- survey questionnaires and interviews with industry specialists. Phase 2 therefore,
targeted knowledgeable, LSS and DFSS industry participants across South Africa and
internationally. The questionnaires and interviews were designed with specific objectives to
determine:
i. Research objective 1: The most significant CSF’s required for LSS successful deployment in
an organisation.
ii. Research objective 2: The most significant CSF’s for successful DFSS deployment in an
organisation.
iii. Research objective 3: The design of a framework assisting organisations to achieve
successful integration of LSS, DFSS, within CMMI.
FINDINGS
The research results obtained assisted in the design and testing of a comprehensive integrated
LSS, CSF’s, DFSS and CMMI framework. The developed framework was tested at an international
auto manufacturer in South Africa assisting the organisation to optimise processes and product
quality coupled with product performance transcending into successful capability maturity
outcomes in the pursuit of increased customer loyalty.
PRACTICAL AND VALUE
Lastly the research identified possible shortcomings of existing continuous improvement
techniques used by manufacturers and as such provide critical success factors assisting
organisations utilising LSS, DFSS and Industry4.0 technology in order achieve overall business
excellence. The research also identified a significant contribution in terms of reduced project
effort when combining Agile and Scrum within CMMI. It is anticipated that the result of the
research will serve as a detailed customised implementation “framework” for both
manufacturing and service industries to become more competitive.
Keywords: Six-Sigma, Design For Six- Sigma, Lean Six- Sigma, Capability Maturity Model Integration,
Critical Success Factors, Industry4.0
INTRODUCTION
Lean Six Sigma (LSS) and Design for Six Sigma (DFSS) are operational strategic tools oriented toward
achieving the shortest possible cycle time by eliminating waste and reducing variation. According to
Bozdogan, K. (2010) the Lean Six Sigma (LSS), Total Quality Management (TQM), Design For Six Sigma
(DFSS), Theory of constraints (TOC), Agile manufacturing and Business Process Reengineering (BPR)
have been introduced as universally applicable best methods to improve the performance of
enterprise operations through continuous process improvement and systemic planned enterprise
change focusing on Lean.
Despite certain differences, Curtis, B. and Alden, J. (2007) suggest that the methodologies potentially
complement each other and established the foundation of the maturity capability model. The
methodologies, are closely interconnected as highly complementary approaches and can be brought
together to define a first-approximation “core” integrated management system, with Lean
enterprise system serving as the central organising framework. Specific elements of the other
approaches can be selectively incorporated into the “core” enterprise system to enrich its
effectiveness, (Corsi, P. and Neau, E. (2015).
To achieve the above, Albiwi. S (2014) observed that Capability Maturity Model Integration (CMMI)
and LSS are two of the best proven improvement-oriented initiatives, with many overlaps. When
comparing CMMI to LSS, CMMI is domain specific, whilst LSS is not. It is noted that here the basic
difference between CMMI and LSS pertains to the scope of application. CMMI therefore aims at
process improvement in specific disciplines or process areas whilst LSS, on the other hand aims at
solving specific product or process related issues within the context of overall organisational process
improvement. Thus, while CMMI is a domain specific improvement engine, LSS has a much wider
application, serving as both an enterprise governance model and a tactical improvement engine
cutting across domains.
In terms of CMMI and Six Sigma, - CMMI provides a framework for continual benchmarking and an
improvement strategy whereas performance is directly linked with the application Six Sigma. CMMI
delivers structure to organisational processes where these are often non-existent or poorly
designed.
To integrate CMMI and DFSS one can include different strategies whereas for such implementation
CMMI, Six Sigma and LSS are key choices in implementing internal processes. The implementation of
the “model” as such is best illustrated in Figure 1 where CMMI and LSS “mature over time” and can
therefore not provide a quick fix solution.
To review the contribution to Lean Continuous Improvement Strategy (CIS) and the contribution of
Critical Success factors when integrating Lean Six-Sigma (LSS) and Design for Six Sigma (DFSS) when
implementing internal processes. The research objective is to (i) critically analyse Critical Success
Factors (CSF’s) impacting on the integration and deployment of LSS and DFSS to maximise the (CIS)
with widespread deployment failures and successes (ii) develop an integrated framework guiding
organisations towards operational excellence complemented by CIS applications when deploying LSS
and DFSS selectively and (iii) constantly review and align Industry 4.0 technological advances to
compliment CIS within Capability Maturity Model Integration (CMMI). The design of the “newly”
develop framework links together “synergistically” key components impacting on the successful
implementation thereof supporting (CMMI) in terms of a business strategy. The framework also
integrated the Theory of Constraints (TOC), Agile and Scrum, Lean Six Sigma (LSS), Design for Six
Sigma (DFSS) in a multi-framework capability maturity model.
RELATED WORK
Literature shows that original equipment manufacturers (OEM’s) in Europe, Japan and America has
been giving rise to fundamentally disseminate the core concepts and opportunities within Lean, Six-
Sigma (LSS) and Design for Six Sigma (DFSS) to fundamentally drive operational excellence
throughout the product and process life cycle. Numerous examples exist over the past two decades
in various industries where it is observed that during the design phase of products and processes
that critical success factor (CSF’s) of DFSS does not fully unlock the opportunity towards
performance and operational excellence.
RESEARCH DESIGN
The nature of this research is primarily exploratory and descriptive. The main elements of the
research are formed by Phase 1 by means of thorough literature reviews in terms of emerging
Industry 4.0 technologies, LSS, DFSS and CMMI. Phase 2- survey questionnaires and interviews with
industry specialists. Phase 2 targeted knowledgeable LSS and DFSS industry participants across South
Africa and Internationally.
RESEARCH TECHNIQUES
The nature of this research will be primarily exploratory and descriptive. The main element of the
research is formed by thorough literature reviews, survey questionnaires and interviews with
industry specialists. The objective is to document relevant and essential current scientific literature.
The literature study is key for clarifying the problem statement and answering the research
questions. Therefore, the literature review and the data (knowledge) collection included studying
and analysing existing articles, papers and journals from scientific journals and from various
databases such as: ABI/Inform, ProQuest, JSTOR, ScienceDirect focusing on Six Sigma, Lean or LSS,
DFSS and Capability Maturity Model (CMM) or a combination of these databases.
The structure of both the survey and interview questionnaires developed and distributed to a total
target of 200 LSS and DFSS industry participants across industries and internationally, including
academics who have conducted research to further examine the CSF’s for LSS and DFSS
methodologies and the relationship within Maturity Capability Model evolution.
The survey and interview questionnaires included:
i. Background of the respondent and organisation.
ii. Requirements for successful deployment of LSS and DFSS.
iii. Critical success factors (CFS’s) for LSS and DFSS implementation.
iv. Respondent organisational maturity capability status.
v. What are the relationships for capability maturity model in relation to LSS and DFSS
implementation.
vi. Application of industry4.0
The research therefore targeted organisations, institutions, consultancies and academics,
(irrespective of industry sector) which have already implemented LSS and DFSS inclusive of
organisations with significant Continuous Improvement Programs (CIP) in both services and
manufacturing industries.
FINDINGS
The research results obtained assisted in the design and testing of a comprehensive integrated LSS,
CSF’s, DFSS and CMMI framework. The developed framework is undergoing testing at an
international auto manufacturer in South Africa assisting the organisation to optimise processes and
product quality coupled with product performance transcending into successful capability maturity
outcomes in the pursuit of increased customer loyalty.
Research objective 1: The most significant CSF’s required for LSS successful deployment in an
organisation.
The CSF’s contributing to effective LSS deployment was confirmed in comparing previous literature
reviews of 31 similar research documents. Research survey results obtained across multiple
industries (Financial, Insurance, Pharmaceutical, ICT, Aerospace, Automotive, etc.) and participant
responses from global geographical origins (Asia, USA, Canada, Europe, South Africa, etc.) and
industry specialist interviews to determine geographical and industry relevance. Table 1 summarises
CSF factors determination of LSS deployment according to Cronbach’s alpha.
Table 1. Survey results in Critical Success Factors determination for Lean Six Sigma Deployment.
Noted is that the results confirmed Management commitment as the single most important
CSF in achievement of successful LSS deployment and concurring previous survey results
(Laureani, A. and Antony,J. 2012). The significant changes in CSF ranking is observed in the
2016 survey results where the increased prominence in ranking position is found in CSF’s
number 4, 5, 6 and 8 compared to earlier research in Laureani, A. and Antony, J. (2012).
Interviews conducted also confirmed that the metrics should not be exclusively linked to
financial improvements but also customer LSS metrics in CSF number 4. LSS staff selection has
emerged as a significant CSF in personality testing on Black Belts and Master Black Belts.
Hoerl, R. (2001) confirmed that management commitment as the single most important CSF in
achievement of successful LSS deployment and concurring previous survey results (Laureani,
A. and Antony,J. 2012). The significant changes in CSF ranking is observed in the 2016 survey
results where the increased prominence in ranking position is found in CSF’s number 4, 5, 6
and 8 compared to earlier research in Laureani, A. and Antony, J. (2012). Interviews
conducted also confirmed that the metrics should not be exclusively linked to financial
improvements but also customer LSS metrics in CSF number 4. LSS staff selection has emerged
as a significant CSF in personality testing on Black Belts and Master
Noted form the from above authors rankings that Black Belts - LSS financial accountability
emerged as prominent CSF ranked in position number 6 where more than half of the
respondents in both survey and interviews confirmed the importance of linking LSS metrics
with financial metrics and typically this would include divisional and organisational annual
financial reports. Berry, O. - the vice president at Ford South Africa (2017) stated in an
interview on Industry 4.0 that although this may be the case for many organisations it is an
outcome of many other input processes rather than a metric for many others. Extending LSS
to the Supply Chain was also ranked in 8th position, however, this study showed that it is not
practical to target 4, 5 or even 6 Sigma Quality when your supply chain is not delivering similar
sigma metrics with their input processes as the single highest risk to the attainment of Six
Sigma quality and metric targets. Interviews conducted confirm Industry 4.0 as a significant
technological enabler of achievement of both Lean and Six Sigma objectives.
Research objective 2: The most significant CSF’s for successful DFSS deployment in an organisation.
The CSF’s determined for effective DFSS deployment was limited to the survey results and the
responses obtained from interviews conducted. Figure 1 reflects the level of organisation DFSS
maturity of the survey responses at 84, 7%.
Figure 1. DFSS Integration % of survey responses
CSF’s for DFSS is illustrated in Table 2 Critical Success Factors identified for DFSS deployment shows
the significance of VOC and Kano analysis tool usage ranked 1st according to Cronbach’s alpha result
of 0.8600 and a mean rating of 4.077.
Noted is that LSS organisation maturity is ranked 2nd with a mean rating of 4.295. Leadership and
management commitment rank in 7th position with a mean rating of 4.525. CSF’s 12, 13 and 15 each
relate to a different constituent within Innovation and the importance is also affirmed in Chemical
industry research participant who has developed a unique Capability Maturity approach with
McKinsey and Company distinguishing between DMAIC Black Belts and Innovation Master Black
Belts who exclusively focus on innovating improved and new product and process designs with
reported savings of $144m in 2015 and $564m in the period 2011-2015 which is more than 2% of
Sales.
Table 2. Critical Success Factors identified for DFSS deployment
The significance of Maturity of Agile and Scrum ranked in 8th position during product development
holds relevance in research conducted when Agile and Scrum was combined with both CMMI level 1
and level 5 maturity seen in Figure 2. In Johnson, R. (2010) and in Justice, J. (2015) three project
scenarios are presented when combining Agile methodology and CMMI maturity level 1 delivering
typical 50% work and 50% rework per project, this is then reduced to 10% rework from 50% when
reaching CMMI maturity level 5 and yielding a 9% process focus for a combined project effort
reduced to 69% from original 100%. The addition of Scrum during project development when
combined with CMMI maturity level 5 and yielding a 4% process focus, only 25% work effort and
only 6% rework levels for a combined project effort of only 35% from the original 100%. This
empirical result achieved does warrant further research to explore replication possibilities in other
project domains but should not be ignored as a significant catalyst within DFSS deployment when
combined with other DFSS CSF’s in Table 2.
Figure 2. Agile CMMI Performance Analysis when combined with Scrum and varying CMMI maturity
levels
Sutherland, J. (2015) also reflects that the breakthrough results achieved at Systematic is attributed
them being the only Scrum company in the world appraised at CMMI level 5 integrated with Lean.
The significance I the approach are including the customer during product testing and closing the
gap in VOC and QFD metrics. CMMI will improve the Sigma Quality but not the rate of production,
Scrum enables project delivery and speed increases. Industry 4.0 presents increasing levels of
Scrum
continuous and sustainable improvements being realised because of Cyber Physical Systems made
possible with quantum computing and Big Data and real-time predictive analytics.
Research objective 3: The design of a framework assisting organisations to achieve successful
integration of LSS, DFSS, within CMMI.
Industry 4.0 presents several supporting enablers to Capability Maturity Model and to LSS and DFSS
methodologies. Figure 3 depicts the 9 pillars of Industry 4.0 supports both LSS and DFSS
methodologies in using Big Data computing, Autonomous Robotics, Design Simulation, System
Integration, Internet of Things, Cybersecurity, Cloud Computing, Additive Manufacturing and
Augmented Reality enabling cost, reliability and speed parameters not possible previously.
Figure 3. Industry 4.0 and 9 technological pillars presented in Cyber Physical Systems (CPS).
Melanson, A. (2015): What Industry 4.0 Means for Manufacturers,http://www.aethon.com/industry-4-0-means-manufacturers/
INTEGRATED FRAMEWORK TO ACHIEVE CAPABILITY MATURITY
A Capability Maturity Model (CMM) addresses the capabilities of a business process and the entire
organisation, expressed as overall maturity, to deliver higher performance over time. These
capabilities are represented in models such as European Foundation for Quality Management
(EFQM), Malcolm Baldridge National Quality Award (MBNQA) and CMMI, which are systematically
assessed and improved. The study has elaborated on the theoretical model components to specify
what is being measured by a CMM. The proposes integrated framework titled CMMI 4.0 was
developed to consist of staged Continuous Improvement implementation using CMMI maturity and
Industry 4.0 technologies to facilitate the integration of improvement methodologies and best
practices available in the 9 pillars of Industry 4.0. In Table 3 - Industry 4.0 Primary Industry Benefits.
Table 3 therefore, illustrate a significant wider improvement over and above typical productivity
improvements enabled through Industry 4.0 technologies.
Table 3. Industry 4.0 Primary Industry Benefits.
Integrated capability maturity framework
The Integrated Capability Maturity Framework designed and developed is illustrated in Figure 4. The
framework harness the varying Continuous Improvement methodologies deployed in both hard and
software industries due to the need for improved speed and agility in design-end product to market
execution and the constant increased connectivity of CPS and consumer solutions where one
methodology could become the constraint as opposed to the needed improvement solution.
The Capability Maturity Model has been labelled (named) CMMI 4.0 due to the compositions and
the direct link to Industry 4.0 enabling technologies to achieve high yield sigma product quality, JIT
deliveries, Jidoka process management and ultimately maximising Return on Investment for
improvement projects.
The framework designed in Figure 4 support the basis of CMMI level 1 to 5 maturity whilst including
the and making provision for Theory of Constraints, Lean and Six Sigma to be utilised throughout all
maturity stages and the respective ISO standards developed to guide the user or organisation in
effective deployment. It should be noted that the maturity model and maturity level is not of key
importance although this is recommended to become and remain an Innovative and self-regulating
industry participant or organisation.
During the study, it emerged that limited successes are reported within organisations attempting
higher levels of Continuous Improvement Methodologies such as DFSS, QFD, Innovation, Agile and
Scrum before establishing LSS as a baseline continuous improvement methodology. Maturity level of
CMMI level 2 is a minimum standard although CMMI level 3 is the suggested maturity level for
sustained data driven decision making in reviewing existing and new process and product
development and often also an industry requirement for the supply chain. The increased
contribution in innovation possibilities within DFSS and CMMI maturity levels 4 and 5 warrants
further research, not included within the scope of this research document.
The constant review of Industry 4.0 as enablers to increased cost and customer satisfaction metrics
are pivotal in achieving CMMI level 4 and 5 but also economically. The CMMI 4.0 framework includes
a plethora of existing ISO standards and some in advance stages of review and development,
affording the user a navigation map in achieving increased levels of Continuous Improvement with a
linear increase in organisational maturity capability.
Impact research in Schlaepler, R.C. and Koch, M. (2015), Otto, H.P. (2016) and in Geissbauer, Vedso,
J. and Schrauf, S. (2016) underlines the significance and the necessity to comprehensively position
and also strategically adjust the organisations position to use Industry 4.0 technology to improve the
customer relationship, market penetration, operational efficiency such as cost and speed and
ultimately secure a sustainable and integrated organisational CI strategy inclusive of capability
maturity. The flexibility offered by the integrated CMMI 4.0 is practical and based on user maturity
and tool selection for improvement.
Figure 4. CMMI 4.0 - Integrated Capability Maturity Model developed to harness multiple Continuous
Improvement methodologies within CMMI.
CONCLUSION
The research identified possible shortcomings of existing continuous Improvement methodologies
used by industries and as such provide critical success factors assisting organisations utilising LSS,
DFSS and Industry 4.0 technology in order achieve overall business excellence. The research also
identified a significant contribution in terms of reduced project effort when combining Agile and
Scrum within CMMI. It is anticipated that the result of the research will serve as a detailed
customised implementation “framework” for both manufacturing and service industries to become
more competitive.
It is noted that strong leadership is central to Agile and Scrum as it will improve capability.
Innovation in a similar fashion is a result of sustained strong leadership and DFSS deployment. Scrum
in Sutherland, J. (2015) provides a platform for learning and a learning organisation is positioned
extremely favourably for Innovation when combined with DFSS and CMMI. Also of importance is
that the maturity of the organisation must be sustainable within the environment of big data
analytics as it is of significance in assimilating data for quality yields of 6 sigma and higher, which will
be a necessity to sustain Innovation of existing processes with the necessary organisational Agility to
respond to stakeholder’s expectations.
The vision of the integrated maturity framework CMMI 4.0 will be able assist with the migration to
excellence through zero defect repetitiveness at efficiencies previously not envisaged.
The integration of both LSS and DFSS as well as considering the CSF’s in the developed framework
will ensure the need to monitor capability maturity to maximise ROI during CI program. The CMMI
4.0 model therefore integrate LSS, DFSS, TOC, Scrum and Agile components. The innovation
opportunities that are realised within this model augmented reality simulations combined with
multiple DOE’s and regular Agile and Scrum testing iterations will save significant cost and increase
responsiveness to the market needs.
The increased value will be delivered in this all comprehensive framework ensuring supporting
Industry 4.0 to continuously driving cost, process and quality improvements, reducing waste and
continuously improving margins. This will furthermore accelerate the NPI process and afford the
clients make to order and highly customised products.
REFERENCES
Journal Antony, J. and Desai, D.A. (2009): Assessing the status of six sigma implementation in the Indian industry - Results from an exploratory empirical study, Management Research News, 32(5), 413-423. Barnes, C. and Walker, R. (2010): Improving corporate communications: Lean Six Sigma science has broad reach, Journal of Business Strategy, 31(1), 23-36. Geissbauer, Vedso, J. and Schrauf, S. (2016): Industry 4.0: Building the digital enterprise, PWC 2016 Global Industry Survey. www.pwc.com/industry40. Geissbauer, Vedso, J. and Schrauf, S. (2016): Industry 4.0: Building the digital enterprise, PWC 2016 Global Industry Survey. www.pwc.com/industry40. Hoerl, R. (2001): Six Sigma black belts: what should they know? Journal of Quality Technology, Vol. 33, No. 4, 391-406. Sutherland, J. (2015): Scrum – The art of doing twice the work in half the time, Business Books NY. Journal – Additional references
Anand, G., Ward, P.T. and Tatikonda, M.V. (2010): Role of explicit and tacit knowledge in Six Sigma projects: An empirical examination of differential project success. Journal of Operations Management, 24(6): 948-975.
Book Albiwi, S.A., Antony, J., and Arshed, N. (2014): Critical Literature Review on Maturity Models for Business Process Excellence, Heriot-Watt University, UK. Andersson, R., Eriksson, H., and Torstensson, H. (2006): Similarities and differences between TQM, six sigma and Lean, School of Engineering, University College of Bora, Sweden. Andersen, B. and Fagerhaug, T. (2000): Root cause analysis: Simplified tools and techniques. Milwaukee: ASQ Quality Press. Andersson, R., Eriksson, H., and Torstensson, H. (2006): Similarities and differences between TQM, six sigma and Lean, School of Engineering, University College of Bora, Sweden. Bozdogan, K. (2010): Towards an integration of the lean enterprise system, total quality management, six sigma and related enterprise process improvement methods centre for technology, policy and industrial development, Massachusetts Institute of Technology, Cambridge, MA USA 02139. Cooper, D.R. Shindler. P.S. (2011): Business Research Methods. New York MacGraw-Hill, 11th Edition. Corsi, P. and Neau, E. (2015): Innovation Capability Maturity Model, 1st edition, John Wiley and Sons Inc, London (UK) and Hoboken (USA). Curtis, B. and Alden, J. (2007): BPM and Organisational Maturity; The Business Process Maturity Model (BPMM): What, Why, and How.” A BPTrends Column. Proceedings Anbari, F.T. and Kwak, Y.H. (2004): Success Factors in Managing Six Sigma Projects, Project Management Institute Research Conference, London, UK, and July 11-14, 2004 Yan-jiang, C., Dan, W. and Lang, X. (2006): “Influencing Factors of Continuous Improvement and Tendency to Change”, IEEE International Conference on Management of Innovation and Technology, Vol. 1, 181-185, Singapore. Yan-jiang, C., Lang, X. and Xiao-na, W. (2006): “Empirical Study of Influencing Factors of Continuous Improvement”, International Conference on Management Science and Engineering, 577-581, Lille, France. On-Line Article Hammer, M. (2007): Process and Enterprise Maturity Model (PEMM), www.bptrends.com. Justice, J. (2015): Scrum for manufacturing, The Learning Consortium for the creative economy,https://www.scrumalliance.org/scrum/media/ScrumAllianceMedia/ Files %20and%20PDFs/Learning%20Consortium/Learning-Consortium-for-the-Creative-Economy-Report-2015.pdf
Laureani, A. and Antony, J. (2012); (2015): Leadership characteristics for Lean Six Sigma, Total Quality Management & Business Excellence, and DOI: 10.1080/14783363.2015.1090291
Melanson, A. (2015): What Industry 4.0 Means for Manufacturers,http://www.aethon.com/industry-4-0-means-manufacturers/ and or https://www.bcgperspectives.com/content/articles/engineered_products_project_business_industry_40_future_productivity_growth_manufacturing_industries/ McKinsey and Co. (2014) Big Data Analytics, Source:http://www.mckinsey.com/business-functions/operations/our-insights/how-big-data-can-improve-manufacturing. Ohno, T., (1978): The Toyota production system: beyond large-scale production. English Translation 1988, Productivity Press, 17-18 & 126-127.
Schlaepler, R.C. and Koch, M. (2015): Industry 4.0 – Challenges and solutions or the digital transformation and use of exponential technologies, Deloitte AG, The Creative Studio, Zurich, 45774A.
Geissbauer, R. Vedso, J. and Schrauf, S. (2016): Industry 4.0: Building the digital enterprise, PWC 2016 Global Industry Survey. www.pwc.com/industry40. Thesis Rathilall, R. (2014): A Lean Six Sigma Framework to enhance the competitiveness in selected automotive component manufacturing organisations. Doctoral Thesis, Durban University of Technology. Samson, D. and Terziovski, M. (1999): The relationship between total quality management practices and operational performance. Journal of Operations Management, 17:393-409. Schlaepfer, R.C. and Koch, M. (2015): Industry 4.0 – Challenges and solutions or the digital transformation and use of exponential technologies, Deloitte AG, The Creative Studio, Zurich, 45774A.