a study on inventory management with reff to kallishwari company

INTRODUCTION

INVENTORY MANAGEMENT

The investment in inventory is high in most of the undertakings engaged manufacturing,

whole-sale and retail trade. The amount of investment is sometimes more in inventory than in

other assets. About 90 per cent part of working capital invested in inventories. It is necessary for

every management to give proper attention to inventory management. A proper planning of

purchasing, handling, storing and accounting should form a part of inventory management. An

efficient system of inventory management will determine:

What to purchase.

How much to purchase.

From where to purchase.

Where to store etc.

Inventory management is primarily about specifying the size and placement of stocked goods.

Inventory management is required at different locations within a facility or within multiple

locations of a supply network to protect the regular and planned course of production against the

random disturbance of running out of materials or goods. The scope of inventory management

also concerns the fine lines between replenishment lead time, carrying costs of inventory, asset

management, inventory forecasting, inventory valuation, inventory visibility, future inventory

price forecasting, physical inventory, available physical space for inventory, quality

management, replenishment, returns and defective goods and demand forecasting.

Involves a retailer seeking to acquire and maintain a proper merchandise assortment

while ordering, shipping, handling, and related costs are kept in check.

1

Systems and processes that identify inventory requirements, set targets, provide

replenishment techniques and report actual and projected inventory status.

Handles all functions related to the tracking and management of material. This would

include the monitoring of material moved into and out of stockroom locations and the

reconciling of the inventory balances. Also may include ABC analysis, lot tracking, cycle

counting support etc.

Management of the inventories, with the primary objective of determining. Controlling

stock levels within the physical distribution function to balance the need for product

availability against the need for minimizing stock holding and handling costs.

In business management, inventory consists of a list of goods and materials held available

in stock.

An inventory can also be a self examination, a moral inventory.

2

INDUSTRY PROFILE

Essar Oil's assets include developmental rights in proven exploration blocks, a 18 MMTPA

refinery on the west coast of India and over 1,400 Essar-branded oil retail outlets across India.

Plans are underway to increase its exploration acreage in various parts of the globe and expand

its refinery capacity to 20 MMTPA.

Essar has a global portfolio of onshore and offshore oil and gas blocks, with about 45,000 sq km

available for exploration. We have over 750,000 bpsd (barrels per stream day) of global crude-

refining capacity (Vadinar+Stanlow+Kenya), which includes the 80,000-bpsd refinery of Kenya

Petroleum Refineries (Essar-owned 50-per cent controlling stake).

Global exploration portfolio

Essar’s exploration and production business has 2.1 billion barrels of oil equivalent of reserves

and resources. Of this, approximately 150 million barrels are 2P and 2C resources, 1 billion

barrels are prospective resources and 1 billion barrels are unrisked, in-place resources.

Largest CBM player in India

We have an acreage of over 2,700 sq km in India, which gives us the largest CBM acreage in the

country. Our CBM block in Raniganj is close to commercial production and has signed customer

contracts with several companies.

Large refining capacity

We have a 18 MTPA refinery at Vadinar in Gujarat, which started commercial production on

May 1, 2008. It has been built with state-of-the-art technology and has the capability to produce

petrol and diesel suitable for use in India as well as advanced international markets.

The refinery produces LPG, Naphtha, light diesel oil, Aviation Turbine Fuel (ATF) and

kerosene. It has been designed to handle a diverse range of crude — from sweet to sour and light

3

to heavy. It is supported by an end-to-end infrastructure setup including SBM (Single Buoy

Mooring), crude oil tankage, water intake facilities, a captive power plant (currently 380 MW,

being expanded to 890 MW), product jetty and dispatch facilities by both rail and road.

We have made substantial investments in installing the most advanced equipment and units in

our refinery. At 97 m, the refinery’s crude column is Asia’s tallest and capable of enhanced

separation of petroleum products. The DHDS reactor is also the largest in its category capable of

producing Euro V-compliant diesel. The refinery is, in fact, unique in its complexity and its

ability to produce value-added products. All units have operated many notches over their rated

capacities with the crude unit achieving over 14 million tonnes (300,000 bpsd) in the very first

year of operation. This is a first for any refinery in India. The refinery capacity was expanded to

18 million tonnes with an increase in its complexity from 6.1 currently to 11.8 on the Nelson

index in 2012, making it India's second largest single-location refinery. As part of a continuous

optimisation programme, the company has decided to further expand the refinery’s capacity by 2

million tonnes to 20 million tonnes (405,000 bpsd) by September 2012.

Until date, our Vadinar refinery has successfully processed more than 50 varieties of crude from

across world, including some of the “toughest crudes”.

4

Company profile

Agriculture Products - Manufacturer, Export / Import,

Pvt. Ltd. Firm since 1995

Established in the year 1989, Sri Kaliswari Metal Powders Private Limited, are a reputed

company engaged in the manufacturing and exporting of a wide range of Air Atomized

Aluminum powder, Pyrotechnic Aluminum powder, Cellular concrete Aluminum powder and

Aluminum pastes (Leafing & Non-leafing Grades).By making use of advanced ERP System, we

are instrumental in offering our range of metal powders as per the international standards

prescribed by the industry

The success story began with the establishment of the Kaleesuwari Refinery Pvt. Ltd. in 1995.

Since then, the company has made incredible strides in the edible oil market with its flagship

brand "Gold Winner". Driven by the goal to provide quality sunflower oil at competitive prices,

Gold Winner within a short span of time, has become the most preferred brand.

Gold Winner is a sunflower oil brand produced by Kaleesuwari Refinery Pvt Ltd. The early

history of the company goes back to 1970s with a small grocery store started by G. Munusamy.

He bought Kaleesuwari Refinery Private Limited near Chennai] in 1993 and has markets

in India, Singapore, Malaysia, Brunei, Kuwait, Dubai, Australia, UK and SriLanka.The company

also sells other products such as vanaspati, soybean oil and groundnut oil. In 2005, it has

received HACCP (Hazard Analysis Critical Control Points) certification which certifies that the

oil does not have any physical, chemical or biological contamination and valid for 5 years. It was

also awarded ISO 9001:2000 for its oil manufacturing plant atVengaivasal, near to Chennai by

TUV Management Services Gmbh, Germany.

5

In 2007, the company signed a memorandum of understanding with U.S. Consultant Robert M.

Pierce, Fats & Oils Refining Consultant. The consultant is expected to suggest ideas to improve

the current product and produce new products.

CHENNAI: Kaleesuwari Refineries has signed an MoU with a leading U.S. Consultant Robert

M. Pierce, Fats & Oils Refining Consultant, to add value to the Gold Winner sunflower oil

brand. According to a release, the consultant will suggest ways to improve the existing process

and develop new products.

6

NEED OF THE STUDY

To identify overall reduction in unit cost.

To right product/material in right quantity at right time.

To meeting the material/product requirement efficiently.

To maintain optimum inventory level.

In order to reduce cost of stock in hold by maintaining optimum level of inventory.

7

SCOPE OF THE STUDY

Inventory systems include valuing the inventory, measuring the change in inventory and

planning for future inventory levels.

The value of the inventory at the end of each period provides a basis for financial

reporting on the balance sheet.

Measuring the change in inventory allows the company to determine the cost of inventory

sold during the period.

The inventory level and changes allow the company to plan for future inventory needs.

The study uses the annual report of kaleesuwari refinery for the past five years

8

OBJECTIVE OF THE STUDY

Primary Objectives:

A study on inventory management in KALEESUWARI REFINERY PRIVATE LIMITED, CHENNAI.

Secondary Objectives:

To calculate the EOQ for various products

To calculate the ABC analysis has helped in reduce their clerical costs and improved

inventory turnover.

Management of inventory is designed to regulate the volume of investment in goods.

In inventory, include raw materials, finished goods, work in progress, supplies and other

accessories.

The analysis has calculated for last five year statement.

9

RESEARCH METHODOLOGY:

Research design;

Analytical research design:

The research design is the conceptual structure within which the research is conducted, it

constitute the blue print for the collection measurement an analysis of data. This study is an

Analytical Research.

The analysis of inventory according to their data available in the company. The data

collection of inventory for analysis by the direct store department. We should record primary

and secondary data by the helps of assistants ledger books. We went to all inventories as raw

material, work in progress inventory, finished goods inventory by the proper observation of

data’s of the company.

SOURCES OF DATA:

Primary data are those data that are originated very first time or fresh data with the help of

primary data formulated the research objectives. Primary data are the accurate attainable

reliable and useful data.

TOOLS AND TECHNIQUES FOR ANALYSIS:

Various tools and techniques are used for the analysis are as follows:

1. ABC Analysis

2. Economic Order Quantity

3. Correlation Analysis

Economic order quantity (EOQ)

10

Is that size of the order which gives maximum economy in purchasing any material and

ultimately contributes towards maintaining the materials at the optimum level and at the

minimum cost.

In other words, the economic order quantity (EOQ) is the amount of inventory to be ordered

at one time for purposes of minimizing annual inventory cost.

The carrying cost of inventory may include:

Interest on investment of working capital

Property tax and insurance

Storage cost, handling cost

Deterioration and shrinkage of stocks

Obsolescence of stocks.

Economic Order Quantity= 2*quantity required*ordering cost

Carrying cost

EOQ= 2AO

C

11

CORRELATION ANALYSIS:

Correlation is the study of the degree of relationship between two variables. In statistical

analysis the study on two variables where in the change in the value of one variable

produces a change in the value of the other variable.

∑ XY - ∑ X*∑ Y

_________

N

r = _______________________________________________

√∑ X2- (∑X)2 √∑ Y2- (∑Y)2

N N

Positive correlation:

Two variables are said to be positively correlated if for an increase in the value of one

variable is also an increase in the value of the other variable or for a decrease in the value

of one variable there is also an decrease in the value of the other variable; that is the two

variable change in the same direction.

Negative correlation:

Two variables are said to be negatively correlated if for an increase in the value of one

variable there is a decrease in the value of the other variable; that is; the two variables

change in opposite direction

12

LIMITATIONS OF THE STUDY

The study is based on the secondary data. So the reliability of the data may not be

accurate.

The study is limited to the past five-year’s data only.

The time period is being limited and is not possible for analyzing the overall performance

of inventory system in KALEESUWARI REFINERY PRIVATE LIMITED

13

REVIEW OF LITERATURE

INVENTORY MANAGEMENT

Author(S): David Waller and Barbara Rosenbaum

An inventory is a detailed, itemized list or record of goods and materials in a company's

possession. "The main components of inventory, “wrote Transportation and

Distribution contributors David Waller and Barbara Rosenbaum, "are cycle stock: the order

quantity or lot size received from the plant or vendor; in-transit stock: inventory in shipment from

the plant or vendor or between distribution centers; [and] safety stock: each distribution center's

inventory buffer against forecast error and lead time variability."

Author(S): Howard J. Weiss and Mark E. Gershon

Writing in Production and Operations Management, Howard J. Weiss and Mark E. Gershon

observed that, historically, there have been two basic inventory systems: the continuous review

system and the periodic review system. With continuous review systems, the level of a company's

inventory is monitored at all times. Under these arrangements, businesses typically track

inventory until it reaches a predetermined point of "low" holdings, whereupon the company

makes an order (also of a generally predetermined level) to push its holdings back up to a

desirable level. Since the same amount is ordered on each occasion, continuous review systems

are sometimes also referred to as event-triggered systems, fixed order size systems (FOSS), or

economic order quantity systems (EOQ). Periodic review systems, on the other hand, check

inventory levels at fixed intervals rather than through continuous monitoring.

References

Allen, Kelley L. "Lose that Inventory Baggage." Across the Board. January 2000.

Gleckman, Howard. "A Tonic for the Business Cycle." Business Week. April 4, 1994.

14

Haire, Kelvin C. "Keeping the Merchandise Moving." Baltimore Business Journal. August 2,

1996.

Krupp, James A. "Measuring Inventory Management Performance." Production and Inventory

Management Journal. Fall 1994.

Scanlon, Patrick C. "Controlling Your Inventory Dollars." Production and Inventory Management

Journal. Fall 1993.

.Valero, Greg. "Minimize Inventory for Maximum Success." U.S. Distribution Journal. July-

August 1997.

Waller, David G., and Barbara A. Rosenbaum. "Plan Inventory Decisions to Cut

Costs." Transportation and Distribution. November 1990.

INVENTORY MANAGEMENT TECHNIQUES

Author(s): by John H. Blackstone, James F. Cox

Abstract: Small businesses, both manufacturers and retailers, now have the opportunity to reduce

inventory-related costs significantly through the use of various inventory techniques implemented

on a micro- or mini-computer. Inventory techniques are divided into two categories--those for

independent demand items (finished goods) and those for dependent demand items

(manufacturing-in-process items and raw material). The use of micro-computers is growing

rapidly, with material requirements planning (MRP) systems currently available for use on micro-

and mini-computers. These MRP systems assist the small manufacturer in planning and

controlling inventory levels of dependent demand items and in scheduling work centers (for

example, see Cox and Clark).1 Several techniques offer potential for savings with independent

demand items. Independent demand item techniques are subdivided into continuous review

models, periodic review models, and mixed models.

15

References

James F. Cox and Steven J. Clark, "Material Requirements Planning System Development,'

Computers and Industrial Engineering, vol. 2 (1978), pp. 123-139.

W. E. Dollan, Purchasing Management and Inventory Control for Small Business, Small

Business Management Series No. 41, U.S. Small Business Administration (1980).

E. Lin, "Inventory Control Systems for Small Business,' American Journal of Small Business

(spring 1980), pp. 11-19.

The continuous review technique, while very practical for a computerized inventory system

collecting point-of-sale data, is not practical for manual systems handling numerous different

items.

CONTINUOUS REVIEW MODEL

There are dozens of variations of the continuous review inventory model.4 the version

discussed here is derived from the following assumptions:

4 This article discusses only the simplest model. More complete discussions can be found

in Rein Peterson and Edward A. Silver, Decision Systems for Inventory Management and

Production Planning (New York: John Wiley & Sons, 1979), and E. Naddor, Inventory

Systems (New York: John Wiley & Sons, 1966).

16

The item under consideration is independent of all other items (no joint replenishment).

Demand for the item varies (is random), but the average demand is constant over time.

Lead time is known and constant.

Holding costs and replenishment costs are known and constant.

The inventory position is maintained at all times

The effect of inventory management on firm performance

Author(s): Dimitrios P. Koumanakos, (Industrial Management and Information Systems

Laboratory, Department of Mechanical Engineering and Aeronautics, University of

Patras, Rio, Greece)

Citation: Dimitrios P. Koumanakos, (2008) "The effect of inventory management on

firm performance", International Journal of Productivity and Performance Management,

Vol. 57 Iss: 5, pp.355

Keywords: , Inventory management, Lean production, Organizational performance

Publisher: Emerald Group Publishing Limited

17

Abstract: Purpose – Lean management is getting more and more attention in today's

highly competitive environment. In this context, the aim of this study is to test the

hypothesis that efficient (lean) inventory management leads to an improvement in a

firm's financial performance

Design/methodology/approach – Data for the analysis came from the ICAP database,

which contains financial information on all medium to large Greek firms. The sample

period extended from 2000 to 2002. For each year all manufacturing firms with the

corporate form of societies anonyms operating in any one of the three representative

industrial sectors in Greece: food, textiles and chemicals were selected.

Findings – Preliminary results, obtained by cross-section linear regressions, reveal that

the higher the level of inventories preserved (departing from lean operations) by a firm,

the lower its rate of returns. Findings are additionally tested by the use of pseudo-

likelihood ratio test which constitutes a more reliable tool, thus verifying the robustness

of the linearity of the relationship

Research limitations/implications – Given the great number of the possible determinants

of performance it is difficult to isolate the effect of inventories even by using large

samples and advanced methodologies.

Originality/value – Since the results from other empirical studies on the microeconomic

determinants and consequences of inventories are somewhat contradictory, this study

sheds more light to this issue by employing more sophisticated statistical tests applied to

a large and recent sample of Greek manufacturers across different industries.

18

Inventory management research in major logistics

Author(s): Brent D. Williams, (Department of Marketing and Logistics, Sam M. Walton

College of Business, University of Arkansas, Fayetteville, Arkansas, USA),

Travis Tokar, (The Ohio State University, Fisher College of Business, Marketing and

Logistics, Columbus, Ohio, USA)

Citation: Brent D. Williams, Travis Tokar, (2008) "A review of inventory management

research in major logistics journals: Themes and future directions",

International Journal of Logistics Management, the, Vol. 19 Iss: 2, pp.212 – 232

Keywords: Inventory management, Research, Supply chain management

Publisher: Emerald Group Publishing Limited

Abstract: Purpose – The purpose of this paper is to provide a review of inventory

Management articles published in major logistics outlets, identify themes from the

Literature and provide future direction for inventory management research

To be published in logistics journals

19

Design/methodology/approach – Articles published in major logistics articles, beginning

in 1976, which contribute to the inventory management literature are reviewed and

cataloged. The articles are segmented based on major themes extracted from the literature

as well as key assumptions

Findings – Two major themes are found to emerge from logistics research focused on

inventory management. First, logistics researchers have focused considerable attention on

integrating traditional logistics decisions, such as transportation and warehousing, with

inventory management decisions, using traditional inventory control models. Second,

logistics researchers have more recently focused on examining inventory management

through collaborative models

20

S NO PARTICULARUNIT PRICE

ANNUAL CONSUMPTION

VALUE OF CONSUMPTION CUM CUM% CLASS

1 TOP UP 1 53 2200.00 116600.00 116600.00 16.73% A

2 INK I 2 50 2304.00 115200.00 231800.00 33.27% A

3 TOP UP 3 45 2200.00 99000.00 330800.00 47.48% A

4 INK I 1 40 2304.00 92160.00 422960.00 60.70% A

5 TOP UP 2 38 2202.00 83676.00 506636.00 72.71% B

6WASH DOWN

WD 2 62 636.00 39432.00 546068.00 78.37% B

7WASH DOWN

WD 3 60 636.00 38160.00 584228.00 83.85% B

8 INK I 3 15 2304.00 34560.00 618788.00 88.81% B

9 INK I 5 10 2304.00 23040.00 641828.00 92.12% C

10 TOP UP 4 8 2202.00 17616.00 659444.00 94.64% C

11 TOP UP 8 8 2200.00 17600.00 677044.00 97.17% C

12WASH DOWN

WD 1 25 636.00 15900.00 692944.00 99.45% C

13WASH DOWN

WD 6 6 636.00 3816.00 696760.00 100% C

21

ABC ANALYSISTable No:

Table Showing the ABC Analysis Of 2007

Chart No: Chart Showing the ABC Analysis Of 2007

31%

31%

38%

CONSUMPTION VALUE 2007 %

ABC

Inference:

The above chart clearly shows the category of products in A is 31%, B is 31%, and C is

38%. It inferred from above table for 2007 it was identified that the C class item as high

consumption. Category A and B consumption is less compare to the C class item, consumption

level of class A and B is compare the other class.

22

S NO PARTICULAR

UNIT PRICE

ANNUAL CONSUMPTIO

NVALUE OF

CONSUMPTION CUM CUM% CLASS

1 INK I 2 34 4302.00 146268.00 146268.00 14.80% A

2 INK I 15 30 4302.00 129060.00 275328.00 27.85% A

3 TOP UP 16 32 2662.00 85184.00 360512.00 36.47% A

4 INK I 18 18 4302.00 77436.00 437948.00 44.30% A

5 TOP UP 1 28 2662.00 74536.00 512484.00 51.84% A

6 TOP UP 26 26 2662.00 69212.00 581696.00 58.84% A

7 TOP UP 7 21 2662.00 55902.00 637598.00 64.50% A

8 INK I 3 12 4302.00 51624.00 689222.00 69.72% A

9 TOP UP 19 19 2660.00 50540.00 739762.00 74.83% B

10 INK I 1 11 4302.00 47322.00 787084.00 79.62% B

11WASH

DOWN WD 3 54 826.00 44604.00 831688.00 84.13% B

12 TOP UP 4 16 2660.00 42560.00 874248.00 88.44% B

13 TOP UP 3 15 2660.00 39900.00 914148.00 92.47% C

14WASH

DOWN WD 17 34 826.00 28084.00 942232.00 95.31% C

15WASH

DOWN WD 5 20 826.00 16520.00 958752.00 96.98% C

16 TOP UP 5 5 2660.00 13300.00 972052.00 98.33% C

17WASH

DOWN WD 6 12 826.00 9912.00 981964.00 99.33% C

18WASH

DOWN WD 4 8 826.00 6608.00 988572.00 100% C

Chart No:

23

ABC ANALYSIS

Table No:


Chart Showing the ABC Analysis Of 2008

44%

22%

33%


ABC

Inference:


33%. It inferred from above table for 2008 it was identified that the A class item as high

consumption. Category B consumption is less compare to the A and C class item, consumption

level of class B is less compare to the other class.

24

ABC ANALYSIS

Table No:


S NO

PARTICULAR

UNIT PRICE

ANNUAL CONSUMPTION

VALUE OF CONSUMPTION CUM CUM% CLASS

1 INK I 15 45 5302.00 238590.00 238590.00 21.94% A

2 INK I 2 30 5304.00 159120.00 397710.00 36.57% A

3 INK I 18 18 5302.00 95436.00 493146.00 45.35% A

4 TOP UP 16 32 2599.00 83168.00 576314.00 53% A

5 INK I 3 15 5304.00 79560.00 655874.00 60.31% A

6 TOP UP 26 26 2592.00 67392.00 723266.00 66.51% A

7 INK I 1 11 5304.00 58344.00 781610.00 71.88% B

8 TOP UP 1 22 2577.00 56694.00 838304.00 77.09% B

9 TOP UP 19 19 2599.00 49381.00 887685.00 81.63% B

10WASH

DOWN WD 3 51 936.00 47736.00 935421.00 86.02% B

11WASH

DOWN WD 17 34 936.00 31824.00 967245.00 88.95% B

12 TOP UP 4 12 2592.00 31104.00 998349.00 91.81% C

13 TOP UP 3 12 2577.00 30924.00 1029273.00 94.65% C

14 TOP UP 7 7 2592.00 18144.00 1047417.00 96.32% C

15WASH

DOWN WD 5 15 934.00 14010.00 1061427.00 97.61% C

16 TOP UP 5 5 2592.00 12960.00 1074387.00 98.80% C

17WASH

DOWN WD 4 8 931.00 7448.00 1081835.00 99.48% C

18WASH

DOWN WD 6 6 934.00 5604.00 1087439.00 100% C

25


33%

28%

39%


ABC

Inference:




level of class B is compare to the other class.

ABC ANALYSIS

Table No:

26


S NO

PARTICULAR

UNIT PRICE

ANNUAL CONSUMPTIO

N

VALUE OF CONSUMPTIO

N CUM CUM%CLASS

1 INK I 2 70 5304.00 371280.00 371280.00 27.07% A

2 INK I 1 46 5304.00 243984.00 615264.00 44.86% A

3 TOP UP 1 73 2600.00 189800.00 805064.00 58.69% A

4 TOP UP 3 45 2600.00 117000.00 922064.00 67.22% A

5 INK I 3 21 5304.00 111384.00 1033448.00 75.34% B

6 TOP UP 2 38 2600.00 98800.00 1132248.00 82.55% B

7WASH

DOWN WD 2 92 936.00 86112.00 1218360.00 88.82% B

8WASH

DOWN WD 3 60 936.00 56160.00 1274520.00 92.92% C

9 INK I 5 5 5304.00 26520.00 1301040.00 94.85% C

10WASH

DOWN WD 1 25 936.00 23400.00 1324440.00 96.56% C

11 TOP UP 8 8 2600.00 20800.00 1345240.00 98.07% C

12 TOP UP 4 8 2600.00 20800.00 1366040.00 99.59% C

13WASH

DOWN WD 6 6 936.00 5616.00 1371656.00 100.00% C

27


31%

23%

46%


ABC

Inference:




level of class B is compare to the other class.

ABC ANALYSIS

28

Table No:


S NO

PARTICULAR

UNIT PRICE

ANNUAL CONSUMPTIO

N

VALUE OF CONSUMPTI

ON CUM CUM%CLAS

S

1 INK I 2 16 5304.00 84864.00 84864.00 24.44% A

2 INK I 1 11 5304.00 58344.00 143208.00 41.24% A

3 TOP UP 1 18 2600.00 46800.00 190008.00 54.72% A

4 TOP UP 3 15 2600.00 39000.00 229008.00 65.95% A

5 INK I 3 6 5304.00 31824.00 260832.00 75.11% B

6WASH

DOWN WD 2 24 936.00 22464.00 283296.00 81.58% B

7WASH

DOWN WD 3 24 936.00 22464.00 305760.00 88.05% B

8 INK I 4 4 5304.00 21216.00 326976.00 94.16% C

9 TOP UP 2 6 2600.00 15600.00 342576.00 98.65% C

10WASH

DOWN WD 5 5 936.00 4680.00 347256.00 100.00% C


29

40%

30%

30%


ABC

Inference:


30%. It inferred from above table for 2011 it was identified that the A class item as high

consumption Category B and C consumption is less compare to the A class item, consumption

level of class B and C is compare to the other class.

30

Chart showing EOQ Analysis INK I 1

.0

10000

20000

30000

40000

50000

60000

70000

80000

33946.6 3359226520

73666.67

13260

2007 2008 2009 2010 2011

31

Table showing EOQ Analysis INK I 1

YEAR ANNUAL MATERIAL ORDERING COSTCARRYING

COST EOQ

2007 32 5304 10 33945.60

2008 38 5304 12 33592.00

2009 40 5304 16 26520.00

2010 125 5304 18 73666.67

2011 25 5304 20 13260.00

Inference:

In this table it clearly shows that the EOQ analysis is increased continuously. In the year 2007

range is 33946.6. It has been increased to 13260 in the year 2011.

32

Table showing EOQ Analysis WASH DOWN WD 1

YEAR ANNUAL MATERIAL ORDERING COST CARRYING COST EOQ

2007 120 936 10 22464.00

2008 90 936 12 14040.00

2009 80 936 16 9360.00

2010 67 936 18 6968.00

2011 40 936 20 3744.00

Chart showing EOQ Analysis WASH DOWN WD 1

0

5000

10000

15000

20000

25000 22464

14040

93606968

3744

2007 2008 2009 2010 2011

33

Inference:


range is 22464. It has been increased to 3744 in the year 2011.

34

Table showing EOQ Analysis TOP UP 1

YEAR ANNUAL MATERIAL ORDERING COSTCARRYING

COST EOQ

2007 336 2600 10 174720.00

2008 420 2600 12 182000.00

2009 295 2600 16 95875.00

2010 661 2600 18 190955.56

2011 154 2600 20 40040.00

Chart showing EOQ Analysis TOP UP 1

.0

50000

100000

150000

200000

250000

174720.00 182000.00

95875.00

190955.56

40040.00

2007 2008 2009 2010 2011

35

Inference:


range is 174720. It has been increased to 40040 in the year 2011.

36

CORRELATION BETWEEN INVENTORY AND SALES

Table No:

Table showing Correlation between Inventory and Sales (RS.In

Crores)

Inventory (X) Sales

Year (Y) X2 Y2 XY

2007 106 1055 11236 1113025 111830

2008 211 1140 44521 1299600 240540

2009 134 1387 17956 1923769 185858

2010 237 1634 56169 2669956 387258

2011 956 1756 313936 3083536 1678736

TOTAL 1644 6972 1043818 10089886 2604222

37

∑ XY= 2604222,

∑ X=1644,

∑ Y=6972,

∑ X2=1043818,

∑ Y2=10089886,

∑ XY - ∑ X*∑ Y

_________

N

r = _______________________________________________

√∑ X2- (∑X) 2 √∑ Y2- (∑Y) 2

N N

38

2604222-(1644*6972)

5

r =

√1043818-(1644)2 √10089886-(6972)2

5 5

2604222-2292393.6 311828.4

r = =

√503270.8 * √368129.2 709.4*606.7

311828.4

r =

430392.98

r = 0.72

39

Inference:

The above calculation reveals that inventory and sales are positively related. It shows that the

value of inventory increase, the sales value also increase and vice-versa.

40

CORRELATION ANALYSIS

Correlation or co-relation refers to the departure of two variables from independence,

although correlation does not imply causation. In this broad sense there are several coefficients,

measuring the degree of correlation, adapted to the nature of data.

The correlation is defined only if both of the standard deviation are finite and both of

them are non- zero. It is a corollary of the Cauchy-Schwarz inequality that the correlation cannot

exceed 1 in absolute value.

Table No.10

Correlations

X-Annual consumption

Y-Value consumption

annual value

annual Pearson Correlation 1 .491

Sig. (2-tailed) .089

N 13 13

value Pearson Correlation .491 1

Sig. (2-tailed) .089

N 13 13

41

**. Correlation is significant at the 0.01 level (2-tailed).

INFERENCE:

Thus there exists a Positive Correlation between Income and Expenditure.

From the above calculation it can be inferred that annual consumption and value of

consumption are highly correlated.

Thus increase in annual leads to increase in profit and vice versa.

Table No.11

Regression

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .491a .241 .172 705.31379

a. Predictors: (Constant), value

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 1735597.969 1 1735597.969 3.489 .089a

Residual 5472142.954 11 497467.541

Total 7207740.923 12

a. Predictors: (Constant), value

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ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 1735597.969 1 1735597.969 3.489 .089a

Residual 5472142.954 11 497467.541

Total 7207740.923 12

b. Dependent Variable: annual

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) 1257.222 328.896 3.823 .003

value .009 .005 .491 1.868 .089

a. Dependent Variable: annual

Case Processing Summary

N

Total Cases 13

Excluded Casesa 0

Forecasted Cases 0

Newly Created Cases 0

a. Cases with a missing value in any

variable are excluded from the

analysis.

43

Variable Processing Summary

Variables

Dependent Independent

annual value

Number of Positive Values 13 13

Number of Zeros 0 0

Number of Negative Values 0 0

Number of Missing Values User-Missing 0 0

System-Missing 0 0

Model Summary and Parameter Estimates

Dependent Variable:annual

Equation

Model Summary Parameter Estimates

R Square F df1 df2 Sig. Constant b1

Linear .241 3.489 1 11 .089 1.257E3 .009

The independent variable is value.

44

CHART NO.10

CHART SHOWING THE RELATION BETWEEN THE

ANNUAL CONSUMPTION & VALUE OF CONSUMPTION

45

Table No.12

Chi-Square Test

46

annual

Observed N Expected N Residual

636 4 3.2 .8

2200 3 3.2 -.2

2202 2 3.2 -1.2

2304 4 3.2 .8

Total 13

value

Observed N Expected N Residual

3816 1 1.0 .0

15900 1 1.0 .0

17600 1 1.0 .0

17616 1 1.0 .0

23040 1 1.0 .0

34560 1 1.0 .0

38160 1 1.0 .0

39432 1 1.0 .0

83676 1 1.0 .0

92160 1 1.0 .0

99000 1 1.0 .0

115200 1 1.0 .0

116600 1 1.0 .0

Total 13

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Test Statistics

annual value

Chi-Square .846a .000b

Df 3 12

Asymp. Sig. .838 1.000

a. 4 cells (100.0%) have expected

frequencies less than 5. The minimum

expected cell frequency is 3.3.

b. 13 cells (100.0%) have expected

frequencies less than 5. The minimum

expected cell frequency is 1.0.

48

FINDINGS

It’s clearly shows the category of products in A is 31%, B is 31%, and C is 38%. It

inferred from above table for 2007 it was identified that the C class item as high

consumption. Category A and B consumption is less compare to the C class item,

consumption level of class A and B is compare the other class.


inferred from above table for 2008 it was identified that the A class item as high

consumption. Category B consumption is less compare to the A and C class item,

consumption level of class B is less compare to the other class.




consumption level of class B is compare to the other class.




consumption level of class B is compare to the other class.


inferred from above table for 2011 it was identified that the A class item as high

consumption. Category B and C consumption is less compare to the A class item,

consumption level of class B and C is compare to the other class.

It clearly shows that the EOQ analysis is increased continuously. In the year 2009 range

are 26520 it has been increased to 13260 in the year 2011.

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are 9360. It has been increased to 3744 in the year 2011.


is 95875. It has been increased to 40040 in the year 2011.

50

SUGGESTIONS

The company can concentrate more on reducing further the level of stocks maintained

and thereby reduce the holding cost

The inventory control can be improved by reducing the inventory holding of ‘C’ class

items while, at the same increasing the level of ‘B’ class item. This is on the basis of

control of ‘Vital Few’ and relaxing the control of ‘trivial many’.

The company can concentrate more on ‘A’ and ’B’ class items inventory control and

relax the control on ‘C’ class items without affecting the value of inventory holdings.

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CONCLUSION

A study on inventory management in KALEESUWARI REFINERY PRIVATE LIMITED,

CHENNAI. Showed that the company was very sound in managing its inventory and is capable

of meeting the future needs and demands of the customer’s requirements.

In inventory maintenance two types of costs are involved carrying cost & ordering costs the firm

should minimize the total cost (carrying plus ordering cost). The firm follows inventory control

techniques as A-B-C technique EOQ technique for better holding inventories.

The study gave a detailed picture of the various inventories the company possessed and

technique it used to manage the same. This study was very useful for both the researcher and the

company for their future activities.

52

BIBLIOGRAPHY

Websites:

www.google.com

www.kaleeswari.com

Books Referred:

Book name author

Financial management - I.M.pandy

Production - R.panneerselvam

and operations management

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http://www.kaleeswari.com/

http://www.google.com/

a study on inventory management with reff to kallishwari company

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