Effect of Economic Order Quantity at Small Scale Textile Mill:

A Case Study

S.M. Kavishwar¹*, S. P. Daf², P.R. Daharwal¹

¹Asst. Prof., Department of Mechanical Engineering, Nagpur Institute Technology, Nagpur India

²Asst Prof., Department of Mechanical Engineering, Priyadarshani Bhagawati College of Engineering, Nagpur India

*Corresponding Author: samratkavishwar@yahoo.in

ABSTRACT:

This paper evaluates inventory situation at Shivkumar Textiles Maharashtra Solapur. The objective of this paper is to develop the Economic Order Quantity (EOQ) model that will be used to determine number of units of an item to order at a time and the re-order point (r), that is the level to which stocks of items are allowed to fall before ordering other items, for raw materials. The resulting EOQ for each raw material is compared to the actual ordered quantities so as to see whether there is any relationship between them in operational cost reduction. The comparison of operational cost reduction was done by using normal distribution test. MS Excel was used to find EOQ and the re-order point. The results show that the relationship between the EOQs and the ordered quantities in terms of operational cost reduction was significant. Therefore, it was concluded that the ordered quantities at Shivkumar Textile mill were not optimal.

KEY WORDS: Inventory; cost reduction EOQ; re-order point; total cost.

INTRODUCTION:

Inventory represents an important decision variable at all stages of product manufacturing, distribution and sales, in addition to being a major portion of total current assets of many businesses. Inventory often represents as much as 40% of total capital of industrial organizations (Moore et al.1993)^[2]. It may represent 33%of company assets and as much as 90% of working capital (Sawaya Jr. and Giauque, 1986)^[3]. Since inventory constitutes a major segment of total investment, it is crucial that good inventory management be practiced to ensure growth and profitability. Inventory constitutes a major component of working capital. To a large extent, the success or failure of a business depends upon its inventory management performances. Proper management and control of inventory not only solve the problem of liquidity but also increase profitability. Inventory establishes a link between production and sales. Every business undertaking needs inventory in adequate quantity for efficient processing and in-transit handling.

Since, inventory itself is an idle asset and involves holding cost; it is always desirable that investment in this asset should be kept at the minimum possible level. Inventory should be available in proper quantity at all times, neither more nor less than what is required.

Inadequate inventory adversely affects smooth running of business, whereas excess of it involves extra cost, thus reducing profits. The primary objective of inventory management is to avoid too much and too little of it so that uninterrupted production and sales with minimum holding costs and better customer’s services may be possible. The term ‘inventory’ refers to the stockpile of the products a firm is offering for sale and various components that make up these products. As per accounting terminology, inventory means “the aggregate of these items of tangible property which i) are held for sale in the ordinary course of business, ii) are in the process of production for such sale, and iii) are to be available for sale”. Thus, inventory includes the stock of raw materials, goods-in-process, finished goods and stores and spares. James H. Greene states that inventory comprises “the movable articles of the business which are eventually expected to go into the flow of trade”.

Table I Raw material data summery of year 2008

Raw material	Annual Demand (D)	Avg. Price of unit (P)	Ordering Costs	Annual Holding Cost (I) (%)	Lead time in days
Cotton yarn	242706.5kg	1502	801431	0.25	12
Fabrics	500771.1 meter	578	1120152	0.25	25
Chemicals	150599.5kg	1123	773303.5	0.25	25
Dyes	862kg	6022	188105	0.25	25

A. Calculating the EOQ, annual total cost and the re-order point for raw materials

Employing the EOQ formulae input data from Table 1,

the Economic Ordering Quantity (EOQ), which is given as

Q* =

D = Annual demand, C = Ordering costs, H = Holding cost

About industry

Shivkumar textiles are located at Nilam Nagar MIDC Solapur. It is small scale textile firms at solapur and it was established in 2008. Its principal products include linen, kitenge (cotton-like covering attire), drills, general prints, curtain, bandage materials and bed sheets for local consumption. In its production, the company needs raw materials such as cotton yarn, fabrics, chemicals and dyes. This research explains the use of Economic order quatity.

Table II EOQ Calculations

Name of raw material	EOQ
Cotton yarn	32187.24 Kgs
Fabrics	88112.856Metres
Chemicals	28803.274 Kgs
Dyes	464.1l1 Kgs

B. Re-order point calculations

Where, r = Re-order point, d = Demand per day, m = Lead-time for a new order in days, t.

Table III Reorder point calculations

Raw material	Re-order point
Cotton yarn	11649.91 Kgs
Fabrics	50077.11 Meters
Chemicals	15059.95 Kgs
Dyes	86.2 Kgs

Having worked out the EOQ, comparison was made to ascertain whether there were any differences in operational costs.

Total cost is given as TC = (½ × Q* × H) + (D/Q*× C)

REVIEW OF LITERATURE:

Niranjan Mandal and Dutta Smriti Mahavidyalaya, (2010)^[4] in their study makes an attempt to provide an insight into the conceptual side of working capital and to assess the impact of working capital management on liquidity, profitability and non-insurable risk of ONGC, a leading public sector enterprise in India over a 9 year period (i.e. from 1998-99 to 2006-07). It also makes an endeavor to observe and test the liquidity and profitability position of the enterprise and to study the correlation between liquidity and profitability as well as between profitability and risk. They may be concluded that working capital management is very much useful to ensure better productive capacity, good profitability and sound liquidity of an enterprise, specifically the PSE in India, for managerial decision making regarding the creation of sufficient surplus for its growth and survival stability in the present competitive and complex environment. Wild^[5] and Axsater^[6] used inventory technique methods in solving real inventory issues for business in a variety of industries from aerospace to retail consumables and from automotive to process chemicals. They noted that appropriate database was a prerequisite for the application of the techniques.

This paper uses the principles of inventory management and control to develop a system to minimize operation costs and developed the model which help company to know the exact amount of raw materials to order and when to place new orders for each raw material.

OBJECTIVES OF THE PAPER:

1) To determine the Economic order quantity

2) To find an optimal re-order level.

3) To test the annual total cost of inventory before the application of the EOQ against annual total cost of Inventory after the application of the EOQ model.

TERMINOLOGY’S USED:

Ordering Cost: This is the sum of the fixed costs incurred each time an item is ordered. This cost has nothing to do with the quantity ordered. Instead, it is connected with the manual labour for processing the order.

Shortage Cost: This is a cost associated with a temporary or permanent loss of sales, when demand cannot be met.

Economic Order Quantity (EOQ): This is the number of units which a company is supposed to add to the inventory for each order to minimize the total cost of the inventory.

All inventory models are expected to answer the two questions below:

1. How much material should the company order?

2. When should a company order?

DEVELOPMENT OF ECONOMIC ORDER QUANTITY MODEL:

This model assumes demand for a product has a constant or nearly constant rate and when the entire quantity ordered arrives in inventory at one point in time. We know for sure employment of the EOQ model for instance there are no records for orders placed at Shivkumar textiles but not honored and so on. Such records would pave ways of estimating probabilities of stock outs and so forth. However, this can be regarded as a starting point for which more complex, realistic and probabilistic models can be developed. However, even at this juncture, it can be shown that a significant amount of cost reduction to the firm can be enhanced by the use of EOQ hence the usefulness of this paper.

The basic formula for EOQ is given below.

This is the optimal quantity to order i.e. the EOQ.

Where

R = Order quantity that will minimize the sum of ordering and holding costs.

D = Annual demand for an item.

H = Annual cost of holding one unit of inventory.

P = Unit price for the items.

I = Annual holding cost rate expressed as percentage of carrying one unit in inventory per year.

C = Ordering cost.

TC = Total cost of inventory.

Raw Materials:

These are materials used for the production of components, sub-assemblies or finished goods.

Inventory Management: This is the implementation of the management’s inventory policies in a manner that assures that the objectives of having an inventory are reached.

Fixed Re-order Stock Level: Through this method, a business identifies the minimum level of stocks that it can have and places new orders when the stocks reach that level

DATA COLLECTION AND ANALYSIS:

In this research, data collection for annual demand and the price per unit of each raw material. taken from Shivkumar Textiles. The collected data for Data on annual ordering and holding costs and the lead times for each raw material were obtained from raw materials ordering record for 2008 from the company. Table 1 shows the summary of the data on raw materials for 2008. Some data were not given directly; so some calculations were made to get such data. For example, the researchers made some calculations to get data on ordering costs.

The EOQ and the re-order point for each raw material were calculated using the appropriate formulae. There after comparing total cost before applying EOQ model and after applying EOQ model.

EOQ AND THE RE-ORDER LEVEL CALCULATIONS:

The calculations of EOQ and Re-order level for each raw material are presented in Table 1.The EOQ model employed in this study is based on the following assumptions:

1. Demand is constant throughout the year at D items per year. This is so done to take advantage of the formulae. This assumption can be justified because at the end of the day, the demand of the material is cumulated on yearly

basis and not on a periodic basis.

2. The company ordered the same amount of a given raw material every time when making orders.

3. Purchasing price per unit is constant (no discounts).

4. Lead-time for each order for every raw material is known.

5. Receipt of inventory is not instantaneous, that is, ordered items for some raw materials such as cotton lint arrive in the inventory at different batches in different times without affecting the demand.

6. Planned shortages are not allowed.

From Table 4 it is seen that the total cost of an inventory before applying the EOQ model was higher than after applying the model.

This means that if the company employed the EOQ model, it would reduce its annual total cost (holding and ordering costs) substantially as shown in Table 4. The differences in operational costs could be attributed to ordering costs as shown in Table 5.

Table V Number of orders before and after applying eoq

Name of raw material	Number of orders before applying the EOQ model (D/Q)	*Number of orders after applying the EOQ model (D/Q)**
Cotton yarn	17	6
Fabrics	20	6
Chemicals	8	6
Dyes	5	2

Above table shows that the number of orders was much higher before applying the EOQ model than it was after applying it. This applies to all types of raw materials dealt with in this study. By having a large number of orders, the company increases ordering costs, hence increasing the annual total cost of inventory.

CONCLUSION:

It can be concluded that Shivkumar Textiles Maharashtra Solapur. Needs a formalized inventory system to minimize operational costs. If the Economic Order Quantity model is objectively used, with the aid of some judgment by the management, holding costs and ordering costs will become low. The use of this model will help the company to know the exact amount of raw materials to order and when to place new orders for each raw material. Economic Order Quantity model thus provides optimum quantity figure to order to minimize extra cost in inventory.

REFERENCES:

1 Bhattacharya, H. “Working capital Management Strategies &, Techniques”, Prentice Hall of India Pvt. Ltd.., New Delhi, 2001.

2 Moore L. J., Lee S. M. and Taylor, III B. W. (1993), Management Science, 4th Ed., Allyn and Bacon, Needham Heights, MA, pp. 321 – 384.

3 Sawaya, JrZ W. J. and Giauque W. C. (1986), Production and Operations Management Harcourt Brace Jovanovich, Inc., Orlando, FL, pp. 121 – 303.

4 Niranjan Mandal, Dr. B. N. Dutta Smriti (2010), Impact Of working Capital management On Liquidity, Profitability and Non-Insurable Risk And Uncertainty Bearing:A Case Study Of Oiland Natural Gas Commission (ONGC), University of Burdwan, Great Lakes Herald Vol 4, No 2.

5 Wild T, 2002. Best Practice in Inventory Management. Butterworth – Heinemann, 2nd edition, August, 2002. ISBN – 13: 398 -07506511586.

6 Axsater S, 2006. Inventory Control. Springer. ISBN 978 – 0 387-33250-s

7 Philips RS, 1987. Operations Research Principles and Practice. 2^nd edition. John Wiley and Sons.

8 Wild T, 2002. Best Practice in Inventory Management. Butterworth – Heinemann, 2^nd edition, August, 2002. ISBN –13:398-07506511586

Received on 11.12.2013 Accepted on 12.01.2014

Research J. Engineering and Tech. 5(1): Jan.-Mar. 2014 page 01-04

Raw material	Total cost before applying the EOQ model TC(Q) in Tshs	Total cost after applying the EOQ model TC(EOQ) in Tshs	Difference between TC(Q) and TC(EOQ) in Tshs
Cotton yarn	15010655.18	12086310.32	2924344.86
Fabrics	19243839.97	12732304.88	6511535.09
Chemicals	8330456.02	8086519.40	243936.62
Dyes	861282.55	700241.73	161040.82