Essay: Textile industry in India

The Textile industry in India traditionally, after agriculture, is the only industry that has generated huge employment for both skilled and unskilled labor in textiles. The textile industry continues to be the second largest employment generating sector in India. It offers direct employment to over 35 million in the country. The share of textiles in total exports was 11.04% during April’July 2010, as per the Ministry of Textiles. During 2009-2010, Indian textiles industry was pegged at US$55 billion, 64% of which services domestic demand. In 2010, there were 2,500 textile weaving factories and 4,135 textile finishing factories in all of India.
1.1.1 Historyof textile industry in India
The archaeological surveys and studies have found that the people of Harrapan Civilizationknew weaving and the spinning of cotton four thousand years ago. Reference to weaving and spinning materials is found in the Vedic Literature also.
There was textile trade in India during the early centuries. A block printed and resist-dyed fabrics, whose origin is from Gujarat is found in tombs of Foster, Egypt. This proves that Indian export of cotton textiles to the Egypt or the Nile Civilization in medieval times were to a large extent. Large quantity of north Indian silk were traded through the silk route in China to the western countries. The Indian silk was often exchanged with the western countries for their spices in the barter system. During the late 17th and 18th century there were large export of the Indian cotton to the western countries to meet the need of the European industries during industrial revolution. Consequently there was development of nationalist movement like the famous Swadeshi movement which was headed by the Aurobindo Ghosh.
There was also export of Indian silk, Muslin cloth of Bengal, Bihar and Orissa to other countries by the East Indian company. Bhilwara is known as textile city.
1.2 The Raymond Ltd.
The Raymond Group was incorporated in 1925 and within a span of few years, transformed from being an Indian textile major to a global conglomerate.
The Raymond Limited was established in September 1925 to acquire the Woolen Mills in Thane known as WADIA WOOLEN MILLS; it was managed by E. D. Sassoon & Co. Until November 1944 when the entire shareholding was acquired by JAGGILAL KAMALPAT SINGHANIA of Kanpur, subsequently J. K. Trust Bombay, acted as managing agents. There after the name was changed to Raymond Woolen Mills Limited.
In late 1994, the ‘Raymond Woolen Mills’ was changed to ‘Raymond Limited’. Traditional product lines were discounting. High quality becomes a numbers of watchwords and the diversification program got head start. Non-traditional blends of natural and manmade fabrics were introduced back by sound research & Development. This resulted in greater consumer satisfaction both at home and abroad.
The idea of J& K was to develop an organization with a diversified product line. Over the year the organization grew in structure and nature. To facilitate better involvement of the top management in the organization effort, the J. K. Organization was divided into three zones i.e., Western, Central and Eastern. The Raymond Limited in Chhindwara is a part of Western zone.
It is the third largest integrated manufacturer in the world, Raymond Limited (Textile Division) has more than 60% market share of the Indian market and 30% market share of the world market for worsted suiting fabrics .It has a capacity of million meters of wool & wool-blended fabrics. The company exports its suiting fabrics to more than 50 countries including USA, Canada, Europe, Japan and the Middle East. Promoted as an essential accessory for ‘the Complete Man’, its products have set a benchmark in that genre. Raymond Ltd has laid great emphasis on developing strong in house skill for research & development since its inception. This unwavering attention to innovation has enabled it to introduce path- breaking new products in the market. Raymond Ltd has raised the performance and product standards of the entire Indian textile industry, hailed as a pioneer and innovator.
Its manufacturing facilities include three world-class fully integrated plants in India, employing state- of- the art technology from wool scing to finishing stage and modern techniques of quality management. All the plants are self-sufficient in terms of providing educational, housing, recreation and spiritual support system for the employees and connected townships. Raymond Limited rightfully recognized as the most respected Textile Company of Indian in January 2003 by ‘Business World’, also produces and markets plush- velvet furnishing fabric in a wide array of designs and cols including carpeting for the niche markets of India and Middle East.
The Rs. 1400 Crores conglomerate transformation of the woollen mill since the inception in 1925 and its mantra for continuous growth has remained the same-pursuit of excellence; to achieve enhanced customer satisfaction through on-going innovation .The graph growth continues to rise higher and higher.
1.3 Overview of Chhindwara Unit
Figureure 1.1: Picture of Chhindwara Plant (Main Gate)
Raymond Limited Chhindwara is the Flagship Company of J. K. Groups (Western Division). It produces high quality polyester wool fabric and polyester viscose blends fabric.The hundred acres plot stood as a pioneer in the Socio-economic development of this region.
This plot stands as a pioneer in the socio-economic development of this region, operation at the plant commenced in July 1990. The plants were in full swing by 1st April, 1991. In short span of f years they have achieved stupendous success. They have rapidly improved upon the efficiency Figureure. The spinning and weaving department have charged ahead of 90% efficiency levels in all over the world. Taking into account the parameter of performance as production, performance, quality, customer and the people they have, they have surpassed all expectations to strive for excellence. It began its operation to cater to the growing demand of premium suiting .The plant is at a distance of 57 kilometres from Nagpur and 70 kilometres from Chhindwara on Nagpur-Chhindwara Road.
The present capacity of the plant after expansion, which has been concluded recently, is 45,000 metres per day. Thus approximately 153 lakhs meters is produced per annum at Chhindwara. The finishing department is the largest of its kinds in Asia, with a capacity of 40000 metres per day. These facts open to the possibility of carrying out finishing for other plants. As of now they process the complete production of Jalgaon unit.
The list factors leading to the selection of this location are:-
Cheap Land.
Labor availability at cheaper cost.
Easy availability of power, fuel and water.
Availability of land for Expansion.
Easy Transportation (because nearer to Nagpur which is well connected to Roads, Rail and Airways.)
Market Proximity.
15% of subsidy on total cost of project subject to maximum of 15 lacs.
Sales Tax exempt for 7 years initially.
Entry Tax exempted for 5 years extended by another five years due to major expansion.
5% Subsidy in electricity charges subject to a maximum of 10 lacs per annum.
1.3.1 The vision for setting up the unit at Chhindwara
To manufacture world ‘class polyester ‘wool and polyester-viscose blended suiting and furnishing fabrics at competitive prices,
To establish a large-scale unit in a backward area, this needed accelerated development
To ensure all- round socio-economic progress of the region and its hinterland
To pprox. the industrial potential of smaller towns of the country, and
To provide additional sces of employment to people in & around Chhindwara district.
The installed capacity of Chhindwara unit is 128 looms and 33528 spindles as against the license capacity of 1500 looms and 50000 spindles.
The plant is located on a 100 acre plot with a built-up area of 1, 40,000 sq meters and a green belt area of 65%. The plant is well equipped with the most modern machinery, ensuring high efficiency and productivity. The work force is adequately skilled, well trained and competent. This unit became operational in the year 1991.
1.3.2 Vital Statistics:
Manpower: Per day the no. of person working all around the three shifts (Including official staff) are 3626. The staff strength is 415.
Power Consumption: 1, 67,000 Unit per day
Water Requirement: 43 Lakhs litre per day
Coal Required: 58 Metric tonnes per day
Out Put: 40,000 meters fabric per day
Units Turn Over: Rs. 430 crores pprox. per annum
1.3.3 General Information:
Mill: B-1 Boregaon, Industrial Growth Centre, A.K.V.N, Kailash Nagar, Tehsil ‘ Saunsar.
Head Office: J. Billard Estate, K. Building, N. Morarjeemarg, Mumbai -400038.
Registered Office: Raymond Ltd. , 56/H. No F2, Village ‘ Zadgaon, Maharashtra
Works Director: Mr. Vinod Padmanabhan
Goods Manufacture: Suiting’s Only, P/V and P/W all wool and furnishing fabric.
1.4 Production Process
Mainly three types of raw materials are usedin this plant for the production of fabric and they are:
Wool: The Merino brand of wool is imported from Australia, and supplied as Tops by the wool Scing and Grey Combing department.
Polyester: A man made synthetic fiber which is in the form of staple fiber or tow. There are three varieties ‘ Normal, Sparkle and Low pill.
Viscose: A regenerated cellulosic fiber which is made from wood pulp. Generally it is dope dyed by suppliers and is in fibrous form.
The production operations at plant are coordinated by the production planning & control department. Its role is to gather information of all stock at various stages and communicate with the different departments; so that production activities are synchronized. The plant has six months order in advance and divide the production activities bi-annually in unison with the market, and Jalgaon and thane units.
First in the sequence is the raw material godown where the basic inputs procured are stored, accounted for and intimated to the commercial department. The first stage of processing is dying. According to a dyeing plan set by the production planners, the dyeing department is issued tops. Fabrics and yarn produced at further stages which are grey or do not have the desired pigmentation are also dyed.
Some polyester is procured in the form of tows. These are cut and converted into sliver form and converted into tops in the converter section. The material is sent back to the raw material godown from where it is sent to the dyeing department. Only after a perfect match with standard shades are the tops sent to the Recombing department.
In the Recombing department tops of polyester and wool in sliver form are blended and mixed to produce a uniform sliver (65% polyester & 35% wool). The processing ensures that fiber is untangled. Straightened and parallel.
All there Tops (polyester and wool) are sent for spinning in the WORSTED SPINNING department. The function of spinning is to form yarn fiber. The yarn made is wound on a bobbin and is called cheese.
*Tops ‘ roll of sliver
*Tow ‘ roll of continuous film or filament of fiber
*Sliver ‘ fiber in a rope like form.
Simultaneously polyester and viscose fiber is dispatched from the dyeing department and raw material godown (grey i.e. Undyed) to the blowroom or p/v spinning department where it is mixed in proportion (67% polyester and 33% viscose). This mix is transformed into sliver in the carding section which further processes and produces a poly-viscose yarn.
All yarn is stored for intermediate purpose in a double yarn room from here the yarn is issued to warping section of the weaving department. At this stage yarn is woven into fabric. In the mending department this fabric is under scrutiny for any defects to be identified and removed. Every meter of fabric produced is checked.
The next stage of processing is the finishing department. Fabric is washed cleaned and subjected to mechanical / chemical operations with the aim of giving the fabric a smooth regular texture, luster and anti-creasing effect. In the folding department, finished fabric is cut to proper length, wound and packed properly.
In addition to this we have a plush department where we manufacture furnishing fabric by procuring yarns from outside.The packed goods are stocked in the warehouse from where it is dispatch as per sales note to respective dealers. This transfer is communicated to the sales office.
1.5 Yarn Room Inventory
The yarn room inventor is the storage location of yarn from where the yarn is sent to the weaving department. The inventory is dived in two different locations; both are situated at two different ends of the weaving department. The total capacity of yarn room inventory including both the location is 180 Metric Tons; while the present inventory size is 270 M.T. means 90 M.T. is the exceeded inventory.Figureure 1.2 shows the two different locations of yarn room inventory
Figureure 1.2 Yarn Room Inventory Locations
The yarn is wounded in the form of doffs (bundles) of different size measured by weight. The doffs are hanged on the vertical trolleys and these trolleys are stored in the yarn room inventory. Figureure 1.3 shows the picture of doffs hanging on vertical trolley.
Figureure 1.3: Picture of doffs hanging on vertical trolley
2.1 Theory of Inventory
‘Sorry, we’re out of that item.’ How often have you heard that during shopping trips? Inmany of these cases, what you have encountered are stores that aren’t doing a very goodjob of managing their inventories(stocks of goods being held for future use or sale). Theyaren’t placing orders to replenish inventories soon enough to avoid shortages. These storescould benefit from the kinds of techniques of scientific inventory management that aredescribed in this chapter.
It isn’t just retail stores that must manage inventories. In fact, inventories pervade the business world. Maintaining inventories is necessary for any company dealing with physical products, including manufacturers, wholesalers, and retailers. For example,manufacturers need inventories of the materials required to make their products. They also need inventories of the finished products awaiting shipment. Similarly, both whole-sellers and retailers need to maintain inventories of goods to be available for purchaseby customers.
The total value of all inventory’including finished goods, partially finished goods,and raw materials’in the United States is more than a trilliondollars. This is more than$4,000 each for every man, woman, and child in the country.The costs associated with storing (‘carrying’) inventory are also very large, perhapsa quarter of the value of the inventory. Therefore, the costs being incurred for the storageof inventory in the United States run into the hundreds of billions of dollars annually. Reducing storage costs by avoiding unnecessarily large inventories can enhance any firm’scompetitiveness.Some Japanese companies were pioneers in introducing the Just-in-time inventory system.
System that emphasizes planning and scheduling so that the needed materials arrive ‘just-in-time’ for their use. Huge savings are thereby achieved by reducing inventorylevels to a bare minimum.Many companies in other parts of the world also have been revamping the way inwhich they manage their inventories. The application of operations research techniques inthis area (sometimes called scientific inventory management) is providing a powerful toolfor gaining a competitive edge.
The Study of inventory problems dates back to 1915, when F. N. Harris developed a very simplebut nonetheless useful model of an inventory problem (Shore, 1980). Inventory is the total amount of goods or materials contained in a store or factory at any given time. A store owner needs to know the exact number of items on the shelves and storage areas in order to place orderor control losses. Inventory management is a science primarily about specifying the shape and percentage of stocked goods. It is required at different locations within multiple locations of a supply network, to protect the regular and planned course of production against the random disturbance of running out of the materials or goods. Inventory management also concerns fine lines between the replenishment lead time, carrying costs, asset management, inventory forecasting, valuation of inventory, future inventory price forecasting, physical inventory, inventory visibility, available space for inventory, quality management, replenishment, returns ,defective goods and demand forecasting.
Possessing high amount of inventory for long periods of time is not usually good for a business because of inventory storage, obsolescence, and expiry, spoilage costs. On the other hand, the possessing of too little inventory isn’t good either, because the business can face the risk of losing out on potential sales and potential market share as well. Undoubtedly more business failures are caused by an overstocked or under stocked condition than any other factor. Inventory management strategies, such as a (J.I.T) just-in-time, is a tool which can help minimize inventory costs because goods are created or received only when needed.
A microeconomic theory of inventory behavior begins by specifying a reason why firms hold inventories. Inventories can be held to improve production scheduling, to smoothen production in the face of fluctuating sales, to minimize stock out costs, to speculate on or hedge against price movements, to reduce purchasing costs by buying in quantity, to shorten delivery lags, and so on. It is evident that no model can explain the rich variety of inventory behavior; an explanation that is plausible for one industry or type of inventory may be implausible for another. Any abstract theory of inventory behavior must simplify and generalize.
Inventory management systems are mostly applied in manufacture settings, where its viability and potential economic value are duly attained. The average business has 30% of its working capital tied up in inventories, while as, about 70% of its investment is in the plant and equipment (Sharma, 1984). It is an admitted fact that the carrying of inventories involves an exorbitant cost. According to the findings of Professor Alford and Bangs, ‘the annual cost of carrying a production inventory averages approximately 25 percent of the value of the inventory’. EverellWelch has also found that, ‘the annual carrying cost of inventory average somewhat 20 percent of the total inventory value, exhibiting a range of some 10 to 34 percent’.
2.1.1 Framework for Inventory Models
General framework for inventory models has five components:
(1) Demand
(2) Order Quantity
(3)Lead Time
(4) Safety Stock or Buffer Stock
(5) Cost of Possession of Inventories.
(1) Demand
Demand is an indispensable component of inventory management. Inventory decisions are always made with reference to the future demand. The decisions are taken when the manager is certain about the requirements in his department and again when the certainty is not ensured. The later state tells nothing about the likelihood of future levels.
(2) Order Quantity
After determining the quality to procure, the buyer must decide as how much to buy. Most material requirements are continuing requirements, cumulative or total needs. Such a system of requirements is a far better guide than the day to day needs. In the procurement function, the term quality has a special meaning and just as there is a need for a most suitable and economical quality of material, there is also a requirement for a most economical ordering quantity. In this connection, to establish an economic order quantity two extreme views are encountered. They are:
The production oriented solution i.e. to procure in very large lots in order to minimize the setup and procurement costs
The treasurer, comptroller or accountant oriented solution which believes in production in very small lots to minimize the investment in stock. In the above two extremes, none holds positively a better foothold, rather the answer is found between the two i.e. a combination of both. The economic order quantity should be established in such a way so as to balance all the variable costs of inventory. The variable costs of inventory are those which vary with the size of the order quantity. The objective of economic order quantity calculations is to determine an order quantity so that the total variable cost of inventory is kept to the minimum.
(3) Lead Time
There is always some interval between the time that the need for material is determined and order placed and the time this material is actually manufactured and delivered. This gap period is the lead time. The longer the lead time, the more time is required to get the results of production and vice versa. Inventories rise when lead time increases to maintain plant operations. However, no safety stocks would be required, if lead time is zero, as replenishment of the stock can be done immediately without any problem. In case the lead time is longer, it is more difficult to predict the usage or consumption, while the order is open. If the procurement is zero, it would be necessary to make any predictions. However, variations in lead time can be quite substantial.
(4) Safety Stock or Buffer Stock
In practice, the demand or usage is not generally known with certainty. Usually it fluctuates during agiven period of time. Typically, the demand for finished goods inventory is subject to the greatest fluctuations. In contrast, the usage of raw materials inventory and in transit inventory, both of which depend upon the production scheduling, is much more predictable. In addition to demand or urge, the lead time required to receive delivery of inventory, once an order is placed is subject to some variation. Owing to these fluctuations, it is not feasible to allow expected inventory to fall to zero before a new order is anticipated, as the firm could easily do when usage and lead time were known with certainty. Most firms maintain some margin of safety or safety stock to satisfy the demand at a particular time. In this connection, the order point is a predetermined signal which will indicate to the stock controller that he should consider the possibility of reordering the stock item in question. It is expressed in units of material as it is stocked and ordered. Whenever, an issue from stock causes the coverage of an item to drop below this pre-determined point, the item should be investigated. The order point must be selected at a Figureure high enough so that the state will be sufficient to satisfy the maximum number of expected demands upon the stock during the period when the replacement stock is on order. In brief:
Order point = Maximum expected usage during lead time.
But the lead time cannot always be accurately determined and the usage during lead time cannot always be accurately forecasted. However, in cases where both these are absolutely predictable, theorder point is simply stated:
Order point = Known requirements during lead time.
When material usage rates and/or each time are based on estimates rather than firm Figureures, it isexpedient to make an upward adjustment of the order point. This process is done through the introduction of safety stock.
Order point = Expected lead time usage + safety stock
Thus, ‘safety stock’ is referred to an extra inventory needed to protect against unrealizable andinaccurate forecasts. Excessive safety stocks boost inventory investment; inadequate safety stocks fail to have the desired protection against stock outs. Thus when forecasts of lead time and usage are perfectly accurate, then:
Maximum inventory = order quantity + safety stock
Minimum inventory = safety stock
Average inventory = 1/2 of the order quantity + Safety stock (if usage is steady)
(5) Cost of Possession of Inventories
It is an admitted fact that the carrying of inventories involves and exorbitant cost. According to thefindings of Professor Alford and Bangs, ‘the annual cost of carrying a production inventory averageapproximately 25 percent of the value of the inventory’. Everett Welch has also found that, ‘theannual carrying costs of inventory average somewhat over 20 percent of the total inventory value,exhibiting a range of some 10 to 34 percent’. Since there are numerous costs involved in holding inventories, but the main costs involved in possession inventories are (a) Cost of Capital, (b) Insurance Cost, (c) Property Taxes, (d) Storage costs (e) Obsolescence and Deterioration (f) Acquisition cost (g) Purchase cost and (h) Ordering cost.
These are briefly discussed in the following section.
(a) Cost of Capital: When a firm purchases production material and carry inventories, it leaves a lower capital available to the firm in the form of working capital for other purposes. To ascertain, whether the capital employed in inventories has been justified or not, the ratio of sales to inventory should be calculated. To raise this ratio, the company should either reduce inventoriesor increase sales without a corresponding increase in inventories. In this way the company’s earnings on investment will boost up. Since money tied up in inventories represent a ‘blockage of capital, therefore, it is logical for the company to charge a rate of interest equal to that it could have earned if invested somewhere else. The opportunity cost varies from company to company and from year to year. At the peak of the business cycle, carrying costs can be extremely high because very profitable alternative opportunities are available and vice-versa.
(b) Insurance Cost: The Company may be required to pay insurance charge to insure their assets against possible loss from fire and other forms of damage. This insurance cost is a 100 percent variable cost.
(c) Property Taxes: This cost may vary from state to state and is 100 percent variable in nature.
Property taxes are levied on the assessed value of a firm’s property. The greater the inventory value, the greater the property value and consequently the higher is the firms tax bill.
(d) Storage costs: The most obvious cost is the storage cost, which includes rent for storage facilities. Salaries and personnel and related storage expenses are involved in it Storage cost, however vary with the type of material stored, type of storage facilities used and so on.
(e) Obsolescence and Deterioration: It is an admitted fact that whenever there are inventories, a certain percentage of a given inventory becomes absolute. No matter how diligently the warehouse manager guards against this occurrence, a certain amount of obsolescence and deterioration always takes place. Well managed companies ruthlessly weed out surplus inventory and dispose it off from the warehouse. ‘The general rule is never to hold inventories for whichthere is no immediate need. And with new products being introduced at an increasing rate, theprobability of occurrence of obsolescence is increasing accordingly. Consequently, the larger theinventory, the greater is the absolute loss from this source.’
(f) Acquisition cost: Most companies carry inventory not because they need protection against stock-outs, but because of reducing their cost of acquisition. Since by ordering and buying largequantities they reduce both purchase cost and order cost. Therefore, it becomes necessary to know the cost of writing a purchase order, the cost of stocking material and the quantity discount available for the item being purchased/
(g) Purchase cost: When a company buys in large quantities suppliers will cut their prices because their costs are lower when they get a simple large order instead of a number of small orders. This enables them not only to reduce their administrative expenses but by manufacturing in larger lots they even reduce unit cost of production. A larger purchase order also increases buyer’s bargaining power and it is easier to wrangle concerns from suppliers.
(h) Ordering cost: Besides, these larger orders also reduce most other costs of acquisition e.g. the cost of making the purchase, excluding receiving, and paying for the material, interplant and intra plant transportation, packing and so on. However, ordering cost is insignificant only with purchases of very high value. Order costs may be substantially high if the purchase lots are in small items.
2.2 Inventory Management in Textile Industry
Store is the place where every type of raw materials, spares, finished goods are kept in proper system. Inventory control means the accurate calculation and data of every type of raw materials, spares and finished goods in time to time store. Inventory control in textile mill are necessary because
To know about the required amount of raw material
To know about the job no which would be processed
To be continued the production process
To find out the profit or loss of a company
Stock and stock value for consumption measuring
2.2.1 Frequency of Inventory Update:
Monthly inventory control.
Annual inventory control.
2.2.2 Scope of Inventory Management:
1.Raw materials
Dye store.
Other chemicals.
Grey fabrics.
2.Finished fabric
3. Spare parts
4. General store
Capital equipment
Accessories
Stationary
Maintenance parts
2.2.3 Inventory System for Raw Material:
Raw materials partially received from production planning & directly from head of’ce.
Material receiving & inspection report is prepared. Received quantity is mentioned and noted down.
Submitted to Q.C. department. Some are OK & few rejected.
Entry of data of goods in DATATEX.
Goods are arranged according to OK or rejected group.
Department gives store requisition to warehouse.
As per requisition materials supplied & this record are noted down.
2.2.4 Grey Fabric Store:
All the grey fabrics are stored in the fabric store near the batch section. Different types of fabric are listed in the sheet according to fabric types, quantity and cons1.uner’s requirement. Fabrics GSM, shrinkage, diameter & other properties are also taken into consideration. The batches are prepared by taking the required fabrics from the grey store.
Stages of Grey Fabric Inventory Control:
After knitting production.
Grey inspection.
Warehouse.
Batch preparation.
Dye house.
2.2.5Dyes and Chemicals:
There is a different store for dyes and chemicals. Varies types of dyes and chemicals are stored here according to dyes and chemicals companies. Different types of dyes and chemicals are listed in a sheet. In the sheet the stored quantity of dyes and chemicals are also included. Every day the sheet is updated and a copy of this sheet is supplied to the dyeing manager, dye house and lab section.
2.2.6Spares:
In any textile mill required amount of spears of different machines are stored in the mechanical store room. All the spears are listed in a sheet which is controlled by the mechanical & maintenance personnel. Spares are arranged in the store room according to their size, quantity & requirements. There are shelves in the store room to keep the small spare parts.
2.2.7Finished Goods:
Any textile mill supplies its ‘nished dyed fabrics to its garments section. So, dyed ‘nished fabrics are stored for short time in the ‘nishing section. All the delivered fabrics are noted on the tally account according to the lot no, quantity, fabrics diameter, buyer’s name, Color &considering other technical parameters.
Stages of Finished Fabric Inventory Control:
Finishing section.
After ‘nal inspection.
Warehouse.
2.2.8Others:
Normally keep a central store at mill. In that store the various types of forms, papers; stationary & other necessary goods are kept.
2.2.9Inventory Procedure:
Bin Card
Store Requisition
Store Ledger Account
Daily Inspection & Package Report
Monthly Stock &Consumption Report
Monthly LIC wise Delivery Report
Received Delivery & Balance Stock
2.3 Studies of Scholars
2.3.1 Md. Mazedul Islam, Adnan Maroof Khan and Md. Monirul Islam-2013, intheir study they have mentioned that the importance of the textile industry in the economy of Bangladesh is very high. The garments manufacturing sector earned $19 billion in the year to June 2012, one of the impoverished nation’s biggest industries. Currently the textile industry in Bangladesh is facing great challenges in its growth rate. The major reasons for these challenges can be the global recession, unfavorable trade policies, internal security concerns, the high cost of production due to increase in the energy costs, different safety issues specially fire, etc. With an in-depth investigation they found that the Bangladesh textile industry can be brought on top winning track if government and others individuals takes serious actions in removing or normalizing the above mentioned hurdles. Additionally, the government should provide subsidy to the textile industry, minimize the internal dispute among the exporters, withdraw the withholding and sales taxes etc. Purchasing new machinery or enhancing the quality of the existing machinery and introducing new technology can also be very useful in increasing the research and development (R and D)related activities that in the modern era are very important for increasing the industrial growth of a country.
2.3.2 Gerald Ochieng Ondiek-2012, The study has examined the recognition Kenyan manufacturing firms are giving to materials management and the benefits of adopting good materials management practices since long-term success and survival of any firm depends on how well their costs are managed. The study surveyed medium and large manufacturing firms based in Nairobi, Kenya. A stratified random sampling technique was used to select 55 firms, out of those 23 percent of the firms were found to recognize materials management as they had an in-charge reporting directly to the chief executive officer. However, generally Kenyan firms were not practicing professionalism in materials management and owing to the huge amount of resources they were committing on materials related activities. A lot of emphasis need to be directed towards materials management and it should be recognized as a top management function.
2.3.3 Mohammad Morshedur Rahman-2011, says that the textiles Industry plays a vital role in the socio-economic development of Bangladesh, but the profitability of this industry is not satisfactory. He studied whether the profitability is affected by Working Capital Management. Ratio Analysis, Correlation Matrix and Regression Analysis have been used in his study to show Profitability, Working Capital position, correlation between them and the impact of Working Capital on Profitability respectively. Annual Reports and official records as well as primary data collected through questionnaire were the sources of data. His study observed that profitability and Working Capital Management position of the Textiles Industry are not satisfactory which revealed that Correlation exists between Working Capital Management and Profitability. His study also shows that Working Capital Management has a positive impact on Profitability.
2.3.4 Shahid Ali-2011, He has studied the association between working capital management and the profitability of textile firms in Pakistan. Efficiency of working capital management is reflected by three variables, cash conversion efficiency, days operating cycle and days of working capital. We use return on assets, economic value added, return on equity, and profit margin on sales as proxies for profitability. A balanced panel dataset covering 160 textile firms for the period 2000’ 05 is analyzed and he estimates an ordinary least squares model and a fixed effect model. Return on assets is found to be significantly and negatively related to average days receivable, positively related to average days in inventory, and significantly and negatively related to average days payable. Also, return on assets has a significant positive correlation with the cash conversion cycle, which would suggest that a longer cash conversion cycle is more profitable in the textiles business. The findings of the regression analysis show that average days in inventory, average day’s receivable, and average days payable have a significant economic impact on return on assets. The findings of the fixed effect model reveal that average days in inventory and average day’s receivable both have a significant impact on return on assets.
2.3.5 HA,Mwansele, FJ,Sichona, RRJ,Akarro-2011, They examined inventory situation at Urafiki Textile Mills Co Ltd in Dar-es-Salaam, Tanzania and tried 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. Their study used cross section secondary data from Urafiki. They used normal distribution test to compare operational cost reduction. The use of Excel was made to find EOQ and the re-order point. Their result shows that the relationship between the EOQs and the ordered quantities at Urafiki in terms of operational cost reduction was significant. Therefore, it is recommended that in order to manage inventory effectively, Urafiki needs to employ inventory control methods such as the EOQ model to obtain reasonable ordered quantities for its raw materials.
2.3.6 Dr.T.S. Devaraja-2011, India is the world’s 2nd largest producer of textiles and garments after China. It is the world’s third largest producer of cotton’after China and the USA’and the second largest cotton consumer after China. The Indian textile industry is as diverse and complex as country itself and it combines with equal equanimity this immense diversity into a cohesive whole. The fundamental strength of this industry flows from its strong production base of wide range of fibres / yarns from natural fibers like cotton, jute, silk and wool to synthetic /man-made fibres like polyester, viscose, nylon and acrylic. The growth pattern of the Indian textile industry in the last decade has been considerably more than the previous decades, primarily on account of liberalization of trade and economic policies initiated by the Government in the 1990s. The relative ease of setting up clothing companies, coupled with the prevalence of developed-country protectionism in this sector, has led to an unparalleled diversity of garment exporters in the third world. Apparel is an ideal industry for examining the dynamics of buyer-driven value chains.
2.3.7 Lee-in Chen Chiu-2007, After 51 years of Japanese colony, starting 1945, Taiwan revitalized her textile industry via six stages: (1) recovery, (2) cotton product development, (3) export expansion and emerging product scope, (4) growth, (5) maturity and upgrading of technology, and (6) transformation, outward investment, and innovation. During the developing process, the role of government policies, such as investment friendly taxation and environment; development of small and medium sized enterprises; textile specific policy/regulation and institutions; development of complementary industries and a reasonable labour market and regulations play the important role. Current manufacturing strength has shifted to cross-strait division of labour in China and Southeast Asian countries. How to deal with the post quota era of changing WTO rules (e.g. rules of origin) will be the critical factors in influencing the success of ASEAN + China economic integration and the competitiveness of Taiwan’s textile industry.
2.3.8 Ian M.Taplin-2006 found while studying the EU textile and clothing industry, that clothing proves more robust in retaining an employment presence than the more capital-intense textile sector. This is surprising since labor intense industry is expected to suffer more from intensified global competition than capital intense ones. Job losses continue in both sectors but firms are innovating in restructuring practices to remain competitive and responsive to buyer pressure. Technological innovation and the pursuit of niche markets plus increased outsourcing are key responses. Thus among all the pressures they leave no scope for internal inefficiencies within the firm.
2.3.9 Donald S. Allen-1997, the common assumption is that firms use inventories to smooth production. Like his previous research based on aggregate data, his research at the level of individual companies fails to confirm this hypothesis, although select firms showed evidence of seasonal smoothing. But the results do confirm the stylized empirical regularity that production varies more than sales, both at the firm level and in the aggregate. One possible explanation of the failure to confirm smoothing is that increased demand prompts firms to raise their inventory targets levels; thus ‘planned’ inventory increases are positively correlated with sales. Unplanned inventory changes, which would reflect the buffer stock motivation, are negatively correlated with sales but insufficient to make the variance of production less than that of sales. In the buffer stock test of the correlation between changes in sales and changes in inventory, most firms’ showed negative correlations. This finding is consistent with the idea that inventories act as abuffer stock to unexpected changes in sales. The negative correlation between changes in sales and changes in inventory may be a better test of whether buffer stock movement is prompted by random demand in the presence of partial adjustment and serially correlated demand. Thus result also seems to suggest that many industries may be making partial adjustments in their inventories.
2.3.10 Pollution Prevention in The Textile Industry Developed by U.S. EPA/Semarnap Pollution Prevention Work Group-1996,the work group study reveals that properly controlling of raw materials, intermediate products, final products, and wastes is a significant way to minimize pollution. Wastes may consist of either raw materials that are out of date, no longer used, or unnecessary; or final products that are no more required or damaged. Including wastes in an inventory program can make them more recoverable. Improving inventory control ranges from simple modifications in the procedure of ordering materials to just-in-time (JIT) manufacturing techniques. Improved inventory control can reduce material expenses and reduce the wastethat is generated, and its associated costs.The following changes can improve inventory management:
Purchase only the amount of material needed.
Review materials for hazardous content, and examine alternatives that are less hazardous.
Track and control the use of materials to reduce excess use.
Designate specific employees/ departments as responsible for the purchase and disposition of supplies and material.
2.3.11 Pawan Kumar-1996, Inventories are viewed by most of the business world as a large potential role and not as a measure of wealth as was prevalent in old days. The inventory stocked in excess of demand may lead to drastic price cuts, so as to be saleable before it becomes worthless because of obsolescence. The inventory stocked less than the demand may lead to the business out of the market. There is a constant fear in the minds of businessmen because of uncertainty in the market situations, whether to stock or not to stock. With rather tight monetary market, optimization of resources through proper inventory control becomes one of the major challenges for the material managers in every organization. Widening gulf between theory and practice has become remarkable phenomena in this age of science and technology. When the frontiers of knowledge are widening and the theory is developing at fast rate, the practice is lagging far behind. This is probably true about all branches of knowledge and especially true for inventory management area. Inventories play essential and pervasive role in almost every sector.
2.3.12 Donald S. Allen-1995, His study support the anecdotal evidence that inventory management methods in the United States have changed significantly over the past decade or two, which is evident in the reduced business inventory-to-sales ratio, driven almost entirely by lower inventories of work-in-process, and materials and supplies rather than finished goods. The impact of these changes in inventory management techniques on business cycles is ambiguous. All other things being equal, inventory management innovations should reduce the probability of unintended accumulation. But as long as firms overestimate or underestimate future demand, inventory cycles will persist. And if cutbacks in production are required to reduce inventory then the resulting reduction in income could result in lower demand and further inventory buildup.
Inventory management innovations are not a panacea for all the business cycles. In the long run these innovations in Inventory management can contribute to a faster response of production to changes in demand. It can in turn reduce the boom-bust cycle in the economy.
2.3.13 Dan M. Becker- and Stephen Stanley-1992,stated that with the advent of the computer and changes in business management techniques it is believed that there is an improvement in inventory control, which is evident as most analysts cite the decline in the ratio of inventories to sales in manufacturing. The improved inventory control implies a faster adjustment of inventories to changes in sales as well as a decline in the average ratio of inventories to sales. There are other goods-stocking sectors to consider besides manufacturing. In contrary to widelyheld opinion, improved inventory control can result in increased, rather than reduced, volatility in inventory investment. The question of whether inventory control has improved is an empirical one; the resolution has important implications for the business cycle because recessions largely turn on the behavior of inventory adjustments. The findings provide clear evidence of improved inventory control in manufacturing, both in finished goods stocks and in inventories of materials and supplies and work in progress. For retail and wholesale trade, the results are mixed. Finally, they seek to determine empirically what effect these refinements have had on inventory investment volatility. Their findings show that, contrary to popular belief, investment volatility has increased in both the manufacturing and trade sectors.
2.3.14 Richard A. Lancioni & Keith Howard-1978,in their study considers the inventorymanagement as an extremely important function to any business, the inadequacies in control can result in serious problems. If inventories are managed in an inefficient manner, it is likely to result in delays in production, dissatisfied customers, or curtailment of working capital.
2.3.15 Mehrunisa Sajjad and Khuram Shahzad Bukhari – The study done in Pakistan presents an in-depth analysis of how cash management, inventory management and trade credit management practices affects the Working Capital Management in a local spinning, weaving and composite units’ setting and the way they impact the firm’s profitability. They observed that with relatively poor cash management and inventory management practices, textile companies have remarkably better trade credit management arrangements. Larger companies have superior cash management, inventory management and trade credit management as compared to medium and smaller units. Due to absence of inventory control systems in majority of the firms with no effective re-ordering techniques, there appears a serious need to review and strengthen the inventory management policies and based on revised inventory controls an appropriate reordering system should be designed. Textile companies are remarkably better at trade credit management and most of the companies have special mechanisms to expedite collections and cheques. Putting it together, larger spinning, weaving and composite units have superior working capital management practices as compared to the smaller and medium textile units (spinning, weaving and composite).The dilemma of the industry is the mindset of managers always relying on past experience and traditional judgment. A very few have adopted the sophisticated techniques for cash management, inventory management and trade credit management. All components have a significant impact on earnings per share and EBIT of the respective organization as illustrated by linear regression analysis with cash management having the strongest impact and are found to be critical decisive in the success or failure of a textile firm. Their research findings are likely to be beneficial for the corporate decision makers of the textile industry, financial institutions and policy makers in Pakistan in order to execute the most favorable strategies to support industrial growth.
3.1 Statement of the Problem
The problem is stated as ‘Analysis and Optimization of Yarn Room Inventory, A Case Study at Raymond’s Textile Mill, Chhindwara’.It is verily cleared by the statement of the problem that it deals with a specific case so that the thesis has been designed as a case study.
Basically the problem lies in the region of inventory control but due the chosen industry (i.e. textile industry); it does not remain as a general inventory control problem. In a textile mill the material is stored at several places on different stages. The Raymond Ltd. Chhindwara unit has following storage locations:
Storage Location Description Purpose
RMG (Raw Material Godown) The RMG is the storage location for the raw material fibers wool, polyester and viscose purchased from outside. The purpose of RMG is to continuously provide the raw material for smooth production.
TOPS GODOWN The fibers converted in sliver form and spirally rolled by a machine. The spiral roll of the sliver is called Top and these tops are stored in TOPS GODOWN. The Tops from TOPS GODOWN are sent to the Grey Combing department; where the material is being cleaned by the combing machine.
Yarn Room Inventory The sliver turns into yarn in Spinning Department and goes to the Yarn Room Inventory for storage. The purpose of Yarn Room Inventory is to provide the material of required quantity for Weaving Department on the time.
Warehouse The warehouse is the storage for finished fabric. To supply the material to goods recipient.
Table 3.1: Different storage locations inside the plant
3.2 Explanation of the Problem
For understanding the problem in detail; we have to first understand the working procedure of the plant. It may be understood by following flow diagram:
Figureure3.1: Block diagram of material flow
The Yarn Room Inventory is actually the transaction stage from where the fibre turns into fabric. There are basically three types of yarn stored in the inventory:
Yarn produced from PW Spinning and PV Spinning
Yarn from outside
Leftover yarn
The general capacity of Yarn Room Inventory is 180 M.T. but presently it contains 270 M.T.; it means 90 M.T. is the exceeded inventory which we have to optimize. This exceeded inventory is due to high volume of left over yarn. The higher production rate is also a cause of this exceeded inventory.
3.2.1 Purpose of Work:
We have to strike two aims in throughout our work:
To classify the leftover material for optimizing the existing inventory.
To establish a system for overcoming the problem in future (reducing future inventory).
3.2.2 Parts of Work:
There are two parts of our work. One is analysis and other is optimization.
Analysis:In this part we did a deeply analysis of leftover yarn and also the manufactured yarn on both macro level and micro level to know that which types of yarn are highly consuming the inventory.
Optimization: In this part we classified the leftover yarn on the basis of modified HML analysis to optimize the existing inventory as well as we also found out the yarn which have frequently higher productivity to reformulate the MRP1 and this will lead us to the future inventory control.
4.1 Inventory Control Techniques & Tools
However, for the proper management of inventories, various techniques have been developed.The important ones are discussed as under:-
4.1.1 ABC Analysis
ABC (always better control) or CIE (control by importance and exception) is an analytical approach aimed at keeping the investment low and also avoiding the stock out of critical items at the same time. A stock out of production parts and materials can be costly, production may be held up if either item is out of stock. Safety stocks almost always are a better value for low cost items they are far expensive ones. Modern inventory control system takes this into account by classifying items by value of usage. The high value items have lower safety stocks, because the cost of protection is so high. However, the low ‘ value items carry much higher safety stocks. This necessitates the controlling manager to recognize the rupee importance of each individual inventory items. Each item should be studied in terms of its price, usage and lead time as well as specific procurement or technical problems. On this basis, it would be easier to allocate departmental effort and expense to tasks of controlling thousands of inventory items. ABC analysis is a basic analytical management tool which enables top management to place the efforts where the results will be greatest. This technique, popularly known as ‘Always Better Control or the Alphabetical Approach’ provides maximum overall protection against stock outs for a given investment in safety stocks. This analysis reveals a measure of the inventory importance of each component helping to put ‘first things first’. It is an analytical approach that provides ‘the most control for the least amount of controlling. Herbert J. Richmond designates this plan as proportionate Value Analysis (PVA). The procedure for ABC analysis consists of the following steps:-
Prepare a list of all items to be held in inventory
Average the items in order to value to be spend in descending order
Assign serial numbers to items as arranged above
Computer for each items percentage proper in the total for: (a) total cost ‘ total cost of eachitem divided by total cost of all material, (b) items ‘ number of items divided by total numberof items
Convert simple percentage into cumulative percentage both for the items and valueconsumption
The items covering up to certain percentage may be 65 percent of total consumption in valuemay be considered to be A items; the next set of items whose aggregate value covers say 20percent of the total may be considered as B items; and the remaining set of items whoseaggregate value covers by 15 percent of the total may be put under C category. Finally findalso the percentage of A, B and C group items in relation to total items.
The Table 2.1 exhibits the comparative importance of A, B and C group items:-
A B C
Close Control Moderate Control Loose Control
Budgeted almost on hand to mouth approach Based on past usage When supply gets low, order more
Close check on schedule revision Some check on change in needs No check against needs
Continual expediting Expediting for prospective shortage No expediting
Low safety stocks Larger safety stocks Large safety stocks
Keep record of receipt and use Keep record of receipt and use No record and less paper work
Table 4.1: Comparative Importance of A, B and C group items
After throwing light on ABC analysis and its uses, however, there are various other techniques which have come forth from time to time in order to arrive at a better control in inventory management. They are discussed in the following section.
4.1.2 The HML Classification
This method is similar to ABC classification but in this case instead of the consumption value of items, the unit value of the item is considered. As the name itself implies, the materials are classified according to their unit value as high, medium or low valued items. The cut off points will depend on the individual items. For example, kerosene will be a low value item for a jewelerand a high value item for a shopkeeper. However, the focus in this classification is so directed as is control the purchase prices.
4.1.3 The XYZ Classification
The XYZ Classification has the value of inventory stored as the basis of differentiation. This exercised is usually undertaken once a year during the annual stock taking exercise. X items are those whose inventory values are high, while Z items are those whose inventory values are low. Understandably, Y items fall in between these two categories. This classification helps in identifying the items which are being extensively stocked.
4.1.4 The VED Classification
The VED classification is applicable largely to spare parts. Spares are classified as vital, essential and desirable. This implies that V class of spares has to be stocked adequately to ensure the operation of the plant because by definition the non-availability of vital spares can cause havoc and stop the wheels of organization. Some risk can be taken in respect of the E class of spares. Stocking of desirable (D) spares can even be done away with if the lad time for their procurement is low. However, it is essential that this classification is done by the technical department or by those in charge of the maintenance of the plant. This classification can be very helpful to capital intensive process industries. A combination of XYZ and VED methods can give an idea of what are the items that should be disposed off so as to trim the inventory.
4.1.5 The SDE Classification
The SDE classification is one where the materials are sorted as scarce to obtain or difficult to obtain. This classification is primarily directed towards controlling purchase, lead ‘ zinc and related supply source problems.
4.1.6. The GOLF Classification
Under this classification, materials are classified according to the nature of suppliers. The nature of suppliers will determine the quality, continuity of supply, lead time, payment terms and clerical work involved, G, category covers Government supplier. O, category implies open suppliers, who usually form the bulk of suppliers. Local suppliers i.e. L category are those fromwhom cash purchases can be made. And, lastly F category refers to the foreign suppliers.
4.1.7 The Limit Technique
A technique called LIMIT (Lot Size Inventory Management Interpolation Technique) has been developed to make it possible to attain the economics of the EOQ concept and to study the alternatives available in balancing ordinary and inventory carrying costs. This technique was developed as part of a special project for the American Production and Inventory Society, Chicago in the year 1963. Limit is designed to handle a family of items which passes over common manufacturing facilities. All the parts that pass through a screw machine, department or a milling machine department or all parts purchased by one buyer would be logical groups to be handling with LIMIT.
4.1.8Two Bin System
The oldest and simplest is the ‘two bin system’. One bin holds a reserve of material equal to the amount that will normally be consumed during the lead time, plus an extra amount for safety stock. The other holds the balance of the inventory. When stock in the second bin is used up, the order point is reached. A clerk requisitions a new supply of material and then draws on the reserve for his needs. When the order is delivered, the reserve supply is brought up to its former level, and the balance of the order is put into the other bin to be drawn on for immediate needs.
The two bin system is best suited for items of low value, fairly consistent usage and short lead time. It is most commonly used for office supplies. And in smaller plants it also is used for maintenance, repair and operating supplies. It rarely is suitable for production materials because it does not provide any record of stock on hand and is not sensitive to changes in demand or lead time. The solution of the inventory problem is to find the approximate levels for holding inventories and the ordinary sequence and the quantities so that the total cost incurred is minimized. The demand and supply conditions impose the constraints within which the relevant costs have to be optimized. The three conditions can be termed as the demand being certain, risky and uncertain respectively. On the supply front, there are two possibilities which can be termed as static, if only a single supply is possible during the consumption period; and dynamic if otherwise.
4.1.9 Economic Order Quantity (EOQ) Concept
Economic order quality is referred to that size of order which gives maximum economy in purchasing the materials. It is also known as optimum or standard order quality or EOQ offers solutions to inventory problems. The concept of EOQ is equally more applicable to raw materials, storage of finished goods and in transit inventories. Economic order quality concept helps in finding approximate levels for holding inventories. It facilitates the fixation of ordering sequence and the qualities so as to minimize the total material cost. Thus, before taking a decision on economic order quantity, the inventory cost are considered and analyzed threadbare. EOQ is the point of minimum cost at which the ordering cost will be just equal to the carrying cost such that neither excess material is ordered, nor too many orders are placed for the same material during a period in time. This also depends upon the nature and complexity of production etc. One of the formulae for calculating EOQ is as:
When:
Q = Ideal purchase quantity
S = Cost of ordering
D = Annual usage or demand in units
I = Inventory carrying cost expressed as a percentage of annual inventory
C = Unit cost of material
Then:
EOQ='(2DS/CI)
OR
EOQ='(‘(2X(Annual Usage or Demand in units)X@(Order Cost in Re-Order))/'((Unit cost of material in Re.unit)X@(carrying cost in % year)))
Where
(Inventory carrying cost) = (Average Inventory) X
(Unit cost of material) X
(Inventory carrying cost in percent per period)
And where:
Annual Set – up cost=DS/Q
4.1.10 Inventory turnover ratio
A ratio showing how many times a company’s inventory is sold and replaced over a period. The days in the period can then be divided by the inventory turnover formula to calculate the days it takes to sell the inventory on hand or ‘inventory turnover days’
Generally calculated as:
Inventory Turnover=(Cost of Sales)/(Average Inventory)
5.1 Data Collection Method
The data is extracted from SAP module of Raymond Ltd. The data contains each and every details of the yarn held in the Yarn Room Inventory. We accounted the data of yarn which is older than three months because the inventory for running production program is about three months. The data is then arranged in tabular form in MS-Excel spreadsheet for further analytical operations. A total number of 4805 different yarns’ data has been collected.
5.1.1 System Application Data Processing (SAP)
SAP is kind of ERP package. ERP stands for Entrepreneur Resource Planning. This is a software package used for planning, organizing and coordination the resources available in the factory for optimum utilization. In a SAP each department is equivalent to some module. Raymond has implemented 6 modules. They are:-
Material Management
Financial Accounting
Production Planning
Quality Control
Sales and distribution
Human resource management
Any document consisting of data related to the above stated module is feeded in the system is called as transaction. All the users of the system, which are mainly the department head are given the password and login name to access the system.SAP initially was developed in German language. The 5 employees of IBM developed it in the year 1972.
Initially Raymond used only one module for financial accounting and the utility efficiency and the speedy decision making lead to the application of other modules. All the modules are inter ‘ related and the changes made in data of 1 module get updated in all the other modules. There is a master data for each of the module. The modules are provided in the package but if needed is felt new modules can be developed and the collection of program can be attached. Information with similar links is kept in the same module. This shows the adaptation of new technological innovations by Videocon to improve efficiency and minimize the time factor.
5.2 Nomenclature of Data
5.2.1 Storage Location: There are different types of storage locations for different types of yarn inside the Yarn Room Inventory.
YN02 ‘ location of the yarn for running production plans in worsted spinning
YN03 ‘ location of knitted yarn for future plans
YN04 ‘ location of sale yarn (Q.C. rejected)
YN06 ‘ location of the yarn for running production plans in PV spinning
YNST ‘ location for stock lot
5.2.2 Material Group (Blend): The material group or blend stands for the mixing of two different fibers. It is just like the alloys in metallurgy. The different percentage ratio of polyester-wool and polyester-viscose are coded as different blends and they are like 130, 170, 870 etc.
5.2.3 Material Number: The material number is the unique identity of yarn. It represents the shade (colour) of yarn. Example: DY20-0491226SA
5.2.4 Material Description:The material description represents the whole technical details of yarn such as blend, count, twist and shade. Example: 130-2/32N-491226X
5.2.5 Batch: The batch or batch number is that identity of yarn for which particular order it is manufactured. There may be a number of different yarns in a single batch. Example: FD1201
5.2.6 Quantity: We have exerted three types of quantity of yarn from SAP:
Ordered Quantity ‘ The quantity of yarn required for a particular batch defined by the central SCM according to MRP1
Receipt Quantity ‘ The quantity of yarn actually manufactured by the plant and receipt by the Yarn Room Inventory.
Unrestricted Stock ‘ The quantity of yarn leftover after weaving or not consumed by the weaving department due to any reason.
5.2.7 Age:For how long time the yarn is stored in the Yarn Room Inventory is known as yarn’s age. It is calculated in days.
5.2.8 Batch Created Date:It is the date on which the batch or order is created in SAP.
5.2.9 Last GR Date: It is the date on which the yarn manufactured and stored in Yarn Room Inventory.
5.2.10 Last Change Date:It is the date on which the leftover quantity of yarn is knitted (adjusted) in a different batch or order.
5.2.11 Goods Recipient: It is the code of the customer for whom the yarn is manufactured. There may be a number of batches for a single goods recipient. Example: C1033A41T
5.2.12 External Material Group:It is the code represents the material group. There are five types of external material groups based on the different contents of fibers.
AW ‘ All Wool (contains only wool fibre and it is highly costly)
WR ‘ Wool Rich (contains higher amount of wool fibre and its less costly then AW)
PW ‘ Polyester Wool (contains both polyester and wool fibres)
PV ‘ Polyester Viscose (contains polyester and viscose fibers)
OT ‘ Outside Yarn
5.3 Sample Data Sheet
5.4 Summarized Data Sheets
Hence we have a lot of data so it is not possible to show all in this thesis; though we have summarized the data according to material group (blend) and shown in the below table. The detail data sheets are present in the CD ROM submitted with this dissertation.
Material Group Sum of
Ordered Quantity
(in Kg) Sum of
Manufactured Quantity
(in Kg) Sum of
Access Quantity
(in Kg) Sum of
Leftover Quantity
(in Kg)
130 1610.107 1671 60.893 105
132 1869.947 1922 52.053 209
133 1664.792 1783 118.208 211
140 723.472 745 21.528 112
141 620.326 691 70.674 41
142 53.537 59 5.463 12
145 73.449 71 -2.449 15
147 1030.388 1087 56.612 158
160 1771.97 1824 52.03 132
165 15237.89 15618 380.11 652
166 59 70 11 26
170 1872.241 1904 31.759 122
171 333.522 344 10.478 14
172 1512.322 1582 69.678 161
177 3492.743 3640 147.257 180
195 1163.229 1170 6.771 108
196 4498.608 4315 13.237 848
197 165.931 175 9.069 29
198 407.755 449 41.245 59
200 754.527 756 1.473 107
202 272.829 261 -11.829 18
203 319.522 375 55.478 38
204 54.044 54 -0.044 11
208 96.114 98 1.886 13
213 1192.837 1213 20.163 180
214 446.54 460 13.46 92
216 17417.987 17066 -351.987 721
217 1935.434 2034 98.566 143.614
218 405.524 396 -9.524 29
219 704.326 720 15.674 80
227 467.9 466 -1.9 93.4
230 166.671 166 -0.671 15
231 88.397 92 3.603 19
232 707.533 707 -0.533 69
236 6922.574 7308 385.426 362
237 5057.041 4640 248.768 962.471
238 8739.646 8597 150.387 1129
240 989.999 1022 32.001 26
241 4495.942 4688 192.058 289
243 136698.878 119338 2283.816 6975.857
244 95.013 96 0.987 29
245 2239.351 2362 122.649 619
246 82.385 90 7.615 11
247 1403.891 1450.783 46.892 109
248 3522.66 3569 46.34 832
250 9749.291 10354 604.709 515
255 1145.572 1183 37.428 63
257 1295 1282 -13 26
258 8276.799 8464 187.201 1325
260 1257.997 1291 33.003 37
262 6205.711 6385 179.289 419
263 94.846 122 27.154 18
265 890.264 911 20.736 174
266 13178.859 12848 -140.596 648
268 1478.912 1513 34.088 129
270 2435.682 2032 21.291 342
271 19284.28 19587 302.72 1292
272 1346.116 1349 2.884 73
273 1205.245 1238 32.755 139
274 331.894 302 4.598 66
278 11712.011 11806 93.989 955
279 82 87 5 12
283 200 198 -2 89
284 15625.365 6243 135.381 462.935
287 1002.419 622 17.873 186
288 2203.714 2251 47.286 420
289 390.431 413 22.569 16
290 7654.365 7490 -164.365 112
291 80 74 -6 11
292 3777.87 3135 -26.623 473
293 12981.019 12787 309.141 1723.499
294 23113.905 23441 327.095 639
295 12982.754 13037 54.246 413
296 21731.522 22134 402.478 1214.901
297 1516.029 1578 61.971 211
298 19244.238 18848 -396.238 525
351 221.142 208 -13.142 9
354 2142.012 2230 87.988 927
356 7215.735 6574 12.773 599.391
360 840.453 862 21.547 44
361 1711.167 1717 5.833 90
362 93.766 93 -0.766 7
369 7700.791 7613 76.071 689
370 2275.744 2370 94.256 96
372 10408.351 10544 135.649 557
375 436.04 439 2.96 26
377 390.294 415 24.706 20
379 2907.795 3035 127.205 97
380 54380.848 55381 1000.152 4105.299
381 7686.126 7999 312.874 1036
386 12404.626 12666 261.374 1261.265
391 2980.62 3092 111.38 766
393 7330.985 7269 -61.985 1525.8
530 3216.039 3456 239.961 336
535 4964.626 5159 194.374 769
574 1204.787 1259 54.213 64
760 186.318 190 3.682 93
857 4700.482 4606 -94.482 757.36
871 65518.366 65819 300.634 5620.453
884 16851.764 17298 446.236 2499.051
956 175.933 172 -3.933 20
147-48 902.811 1022 119.189 192
160-20 1916.578 1942 25.422 87
165-32 286.613 350 63.387 79
170S-70 6854.856 7192 337.144 636
177G-64 66.808 72 5.192 13
177S-64 1068.724 1080 11.276 86
191-15 450.114 457 6.886 37
196-48 2015.942 2087 71.058 369
200-50 176.927 178 1.073 15
203S-80 4235.871 4343 107.129 165
216-50 716.925 781 64.075 118
217-60 1581.79 1632 50.21 81
219L-100 1400.682 1472 71.318 244
232-50 741.261 785 43.739 89
237-60 1643.699 1754 110.301 431
238-50 2237.987 2350 112.013 203
241-50 933.268 1006 72.732 107
243/243 3401.018 3443 41.982 272
243-50 349.209 370 20.791 33
243G-70 3185.235 3237 51.765 165
243L-70 3299.406 3362 62.594 338
243L-80 5268.529 5530 261.471 699
243S-70 44615.253 46136 1520.747 2105
246-60 157.111 173 15.889 13
248-60 1162.857 1203 40.143 470
250L-30 6446.897 6266 -180.897 731
257L-70 98.104 98 -0.104 13
257S-80 401.883 406 4.117 22
262L-60 4285.406 4302 16.594 132
262L-70 35.156 39 3.844 6
262S-60 1452.22 1491 38.78 80
265-50 64.774 67 2.226 9
266L-70 10007.019 10433 425.981 415
266L-80 2103.313 2173 69.687 125
266S-80 341.95 354 12.05 31
270-50 239.008 253 13.992 19
270-60 106.651 122 15.349 26
271L-70 26338.65 27098 759.35 3117
271L-80 1660.614 1787 126.386 107
271S-70 191.452 208 16.548 19
271S-80 13157.371 13421 263.629 1168
278-58 10564.268 10753 188.732 505.313
283-50 150 152 2 55
287-60 311.28 330 18.72 55
288-50 654.877 678 23.123 127
290L-70 105.347 115 9.653 19
292-50 1038.603 1060 21.397 224
293-50 2398.521 2535 136.479 330
294-50 27884.48 28508 623.52 1498
295L-70 12043.15 12071 27.85 705
296L-70 9896.131 10457 560.869 1231
298-38 33.256 35 1.744 6
298-50 7060.063 7215 154.937 294
298L-70 4671.611 5028 356.389 41
298L-80 599.238 621 21.762 96
356S-70 3218.065 3343 124.935 182
360S-48 520.29 532 11.71 48
369-50 242.651 244 1.349 43
574-44 160.496 166 5.504 12
857-68 92 92 0 61
871/871 547.705 643 95.295 138
871-48 875.588 930 54.412 444
871-60 334.252 231 88.118 128
871L-68 17906.902 18193 286.098 2215
884/884 97.021 116 18.979 30
884-34 456 456 0 159
972S-60 242.969 267 24.031 29
Table5.2: Summarized data sheets
6.1 Analysis of Leftover Yarn
Thepurpose of leftover yarn’s analysis is to optimize the present inventory. The leftover yarn has been analyzed on following basis:
We have calculated the quantity of leftover yarn in percentage against the receipt quantity to categorize the leftover yarn.
We have calculated the quantity of leftover yarn on according to external material groups.
We have calculated the quantity of leftover yarn according to storage locations.
We have year wise calculated the quantity of leftover yarn
All these calculations have been done on MS-Excel.
The data is arranged in a excel spreadsheet.
The analysis is also shown by charts.
6.1.1 Summarized Analysis Sheet of LeftoverYarn
Blend % Left Blend % Left Blend % Left Blend % Left
130 6.28% 246 12.22% 372 5.28% 250L-30 11.67%
132 10.87% 247 7.51% 375 5.92% 257L-70 13.27%
133 11.83% 248 23.31% 377 4.82% 257S-80 5.42%
140 15.03% 250 4.97% 379 3.20% 262L-60 3.07%
141 5.93% 255 5.33% 380 7.41% 262L-70 15.38%
142 20.34% 257 2.03% 381 12.95% 262S-60 5.37%
145 21.13% 258 15.65% 386 9.96% 265-50 13.43%
147 14.54% 260 2.87% 391 24.77% 266L-70 3.98%
160 7.24% 262 6.56% 393 20.99% 266L-80 5.75%
165 4.17% 263 14.75% 530 9.72% 266S-80 8.76%
166 37.14% 265 19.10% 535 14.91% 270-50 7.51%
170 6.41% 266 5.04% 574 5.08% 270-60 21.31%
171 4.07% 268 8.53% 760 48.95% 271L-70 11.50%
172 10.18% 270 16.83% 857 16.44% 271L-80 5.99%
177 4.95% 271 6.60% 871 8.54% 271S-70 9.13%
195 9.23% 272 5.41% 884 14.45% 271S-80 8.70%
196 19.65% 273 11.23% 956 11.63% 278-58 4.70%
197 16.57% 274 21.85% 147-48 18.79% 283-50 36.18%
198 13.14% 278 8.09% 160-20 4.48% 287-60 16.67%
200 14.15% 279 13.79% 165-32 22.57% 288-50 18.73%
202 6.90% 283 44.95% 170S-70 8.84% 290L-70 16.52%
203 10.13% 284 7.42% 177G-64 18.06% 292-50 21.13%
204 20.37% 287 29.90% 177S-64 7.96% 293-50 13.02%
208 13.27% 288 18.66% 191-15 8.10% 294-50 5.25%
213 14.84% 289 3.87% 196-48 17.68% 295L-70 5.84%
214 20.00% 290 1.50% 200-50 8.43% 296L-70 11.77%
216 4.22% 291 14.86% 203S-80 3.80% 298-38 17.14%
217 7.06% 292 15.09% 216-50 15.11% 298-50 4.07%
218 7.32% 293 13.48% 217-60 4.96% 298L-70 0.82%
219 11.11% 294 2.73% 219L-100 16.58% 298L-80 15.46%
227 20.04% 295 3.17% 232-50 11.34% 356S-70 5.44%
230 9.04% 296 5.49% 237-60 24.57% 360S-48 9.02%
231 20.65% 297 13.37% 238-50 8.64% 369-50 17.62%
232 9.76% 298 2.79% 241-50 10.64% 574-44 7.23%
236 4.95% 351 4.33% 243/243 7.90% 857-68 66.30%
237 20.74% 354 41.57% 243-50 8.92% 871/871 21.46%
238 13.13% 356 9.12% 243G-70 5.10% 871-48 47.74%
240 2.54% 360 5.10% 243L-70 10.05% 871-60 55.41%
241 6.16% 361 5.24% 243L-80 12.64% 871L-68 12.18%
243 5.85% 362 7.53% 243S-70 4.56% 884/884 25.86%
244 30.21% 369 9.05% 246-60 7.51% 884-34 34.87%
245 26.21% 370 4.05% 248-60 39.07% 972S-60 10.86%
Table: 6.1: Leftover Yarn Analysis Sheets
6.1.2 Quantity of Leftover Yarn According to External Material Group
External Material Group Sum of
Ordered Quantity
(In Kg.) Sum of
Receipt Quantity
(In Kg.) Sum of
Leftover Quantity
(In Kg.) %Left
AW 51529.593 53133 4734 8.91%
PV 107380.08 108384 12098.864 11.16%
PW 332733.071 338641 28222.068 8.33%
WR 419919.676 395703.783 27743.677 7.01%
Table 6.2:Quantity of Leftover Yarn According to External Material Group
Chart: 6.1
Chart: 6.1: Quantity of Leftover Yarn According to External Material Group
6.1.3 Quantity of Leftover Yarn According to Storage Locations
Storage
Location Sum of
Ordered Quantity
(In Kg.) Sum of
Receipt Quantity
(In Kg.) Sum of
Leftover Quantity
(In Kg.) %Left
YN02 101825.645 101303 5815.543 5.74%
YN03 468844.83 467013.783 39811.788 8.52%
YN04 74283.689 74330 3716.071 5.00%
YN06 57542.117 54720 5685.76 10.39%
YNST 206460.633 195804 15957.447 8.15%
Table 6.3: Quantity of Leftover Yarn According to Storage Locations
Chart: 6.2: Quantity of Leftover Yarn According to Storage Locations
6.1.4 Year Wise Quantity of Leftover Yarn
Year Sum of
Ordered Quantity
(In Kg.) Sum of
Receipt Quantity
(In Kg.) Sum of
Leftover Quantity
(In Kg.) %Left
2007 198.659 251 148 58.96%
2008 1436.651 1558 173 11.10%
2009 6221.7 6304 468 7.42%
2010 7809.056 7979 409 5.13%
2011 22939.406 23328 1323 5.67%
2012 51753.487 53305 3805.614 7.14%
2013 347132.37 354597.783 27517.85 7.76%
2014 440575.797 448539 34439.92 7.68%
Table: 6.4: Year Wise Quantity of Leftover Yarn
Chart: 6.3: Year Wise Quantity of Leftover Yarn
6.2 Analysis of Manufactured Yarn
The purpose of manufactured yarn’s analysis is to find out the materials which have frequently high productivity. This data may be used for reformulating the MRP1 to reduce the future inventory and to do a better production planning also. For this we have done following calculations:
We have calculated the difference between the ordered quantity and manufactured quantity of yarn.
We have also calculated the above quantity in percentage in order to focus the materials with higher productivity.
All these calculations have been done on MS-Excel.
The data is arranged in a excel spreadsheet.
The analysis is also shown by charts
6.2.1 Summarized Analysis Sheet of Manufactured Yarn
Blend % Access Blend % Access Blend % Access Blend % Access
130 3.78% 246 9.24% 372 1.30% 250L-30 -2.81%
132 2.78% 247 3.34% 375 0.68% 257L-70 -0.11%
133 7.10% 248 1.32% 377 6.33% 257S-80 1.02%
140 2.98% 250 6.20% 379 4.37% 262L-60 0.39%
141 11.39% 255 3.27% 380 1.84% 262L-70 10.93%
142 10.20% 257 -1.00% 381 4.07% 262S-60 2.67%
145 -3.33% 258 2.26% 386 2.11% 265-50 3.44%
147 5.49% 260 2.62% 391 3.74% 266L-70 4.26%
160 2.94% 262 2.89% 393 -0.85% 266L-80 3.31%
165 2.49% 263 28.63% 530 7.46% 266S-80 3.52%
166 18.64% 265 2.33% 535 3.92% 270-50 5.85%
170 1.70% 266 -1.08% 574 4.50% 270-60 14.39%
171 3.14% 268 2.30% 760 1.98% 271L-70 2.88%
172 4.61% 270 1.06% 857 -2.01% 271L-80 7.61%
177 4.22% 271 1.57% 871 0.46% 271S-70 8.64%
195 0.58% 272 0.21% 884 2.65% 271S-80 2.00%
196 0.31% 273 2.72% 956 -2.24% 278-58 1.79%
197 5.47% 274 1.55% 147-48 13.20% 283-50 1.33%
198 10.12% 278 0.80% 160-20 1.33% 287-60 6.01%
200 0.20% 279 6.10% 165-32 22.12% 288-50 3.53%
202 -4.34% 283 -1.00% 170S-70 4.92% 290L-70 9.16%
203 17.36% 284 2.22% 177G-64 7.77% 292-50 2.06%
204 -0.08% 287 2.96% 177S-64 1.06% 293-50 5.69%
208 1.96% 288 2.15% 191-15 1.53% 294-50 2.24%
213 1.69% 289 5.78% 196-48 3.52% 295L-70 0.23%
214 3.01% 290 -2.15% 200-50 0.61% 296L-70 5.67%
216 -2.02% 291 -7.50% 203S-80 2.53% 298-38 5.24%
217 7.06% 292 -0.84% 216-50 8.94% 298-50 2.19%
218 7.32% 293 2.48% 217-60 3.17% 298L-70 7.63%
219 11.11% 294 1.42% 219L-100 5.09% 298L-80 3.63%
227 5.09% 295 0.42% 232-50 5.90% 356S-70 3.88%
230 -2.35% 296 1.85% 237-60 6.71% 360S-48 2.25%
231 2.23% 297 4.09% 238-50 5.01% 369-50 0.56%
232 -0.41% 298 -2.06% 241-50 7.79% 574-44 3.43%
236 -0.40% 351 -5.94% 243/243 1.23% 857-68 0.00%
237 4.08% 354 4.11% 243-50 5.95% 871/871 17.40%
238 -0.08% 356 0.19% 243G-70 1.63% 871-48 6.21%
240 5.57% 360 2.56% 243L-70 1.90% 871-60 61.67%
241 5.67% 361 0.34% 243L-80 4.96% 871L-68 1.60%
243 1.78% 362 -0.82% 243S-70 3.41% 884/884 19.56%
244 3.23% 369 1.01% 246-60 10.11% 884-34 0.00%
245 4.27% 370 4.14% 248-60 3.45% 972S-60 9.89%
Table: 6.5: Summarized Analysis Sheets of Manufactured Yarn
6.2.2 Quantity of Manufactured Yarn According to External Material Group
External Material Group Sum of
Ordered Quantity
(In Kg.) Sum of
Receipt Quantity
(In Kg.) Difference
(In Kg.) %Access
AW 51332.748 53133 1800.252 3.51%
PV 107188.71 108384 1195.29 1.12%
PW 331321.514 338641 7319.486 2.21%
WR 388224.154 395703.783 7479.629 1.93%
Table: 6.6: Quantity of Manufactured Yarn According to External Material Group
Chart: 6.4: Quantity of Manufactured Yarn According to External Material Group
6.2.3 Quantity of Manufactured Yarn According to Storage Locations
Storage
Location Sum of
Ordered Quantity
(In Kg.) Sum of
Receipt Quantity
(In Kg.) Difference
(In Kg.) %Access
YN02 100022.592 101303 1280.408 1.28%
YN03 457847.398 467013.783 9166.385 2.00%
YN04 73176.254 74330 1153.746 1.58%
YN06 53207.594 54720 1512.406 2.84%
Table: 6.7: Quantity of Manufactured Yarn According to Storage Locations
Chart: 6.5: Quantity of Manufactured Yarn According to Storage Locations
7.1 Optimization of Present Inventory
It is clear by the analysis that the high volume of inventory is due to the leftover yarn. The optimization of present inventory can only be done by reusing the leftover yarn as soon as possible.
We have applied the HML classification for leftover yarn. This will show the priority of reusing (knitting) the leftover yarn for upcoming plans.In our case the HML classification is based the percentage of leftover yarn against the manufactured quantity (in Kg.). We have blend wise classify the leftover yarn on following percentage scale:
75.01% – 100% (Highest) ‘ 1st Priority
50.01% – 75.00% (High) ‘ 2nd Priority
25.01% – 50.00% (Medium) ‘ 3rd Priority
10.01% – 25.00% (Low) ‘ 4th Priority
0.00% – 10.00% (Surplus) ‘ No Priority
This classification has been done on MS-Excel. Here we only show a sample sheet and all the sheets can be found on CD ROM.
7.1.1 Leftover Yarn Classification (Sample Sheet)
7.2 The PPC Team Must Think About!
Though the previous classification of leftover yarn is definitely helpful to optimize the present inventory but it will only able to find out the leftover yarn which has left higher in percentage against the manufactured quantity. It does not mean that higher percentage shows the higher participation of a particular yarn in total inventory.
The PPC (Production Planning & Control) team of the plant must think about of this:
41042.125 Kg.
In the previous screenshot one can easily understand that the selected 18 blends are playing an important role in the exceeded inventory. Their %Left is not so high but their quantity in Kg. tells all the truth. These 18 blends cover more than 50% size of the exceeded inventory. This issue cannot be further deal by any Industrial Engineer because textile engineering is not our cup of tea.
The PPC team of the plant must take right actions for these 18 blends in order to minimize the inventory as soon as possible.
7.3 Using FIFO for Knitting The Yarn
Knitting means the leftover yarn will be used for the upcoming production of fabric. The yarn which matches the requirement for the upcoming plans is used in that particular plan and hence the required amount to produce new yarn becomes less.
7.3.1 What is FIFO?
FIFO stands for ‘First-in, Firs-out’;this is an inventory control tool. FIFO technique is used to consume or sell the goods in the order they manufactured or in the order they take place in inventory. It means the goods which are firstly produced goods or firstly brought in inventory will be sold or consumed first. This method is best to remove the decay between use and reuse of the goods.
In Out
Figure7.2: A simple block diagram of FIFO
7.3.2 How We Will Apply FIFO?
To understand the application of FIFO we take an example of the blend 243 of Jan-2013. Following are the data of Jan-2013:
Material Number Batch Ordered Receipt Left Last GR Date
DY20-0872707SA FM1913 1186.855 1245 59 12.01.2013
DY20-0272704ZB ZK2601 83.175 89 17 15.01.2013
DY20-094218XSA FM9843 463.689 467 10 22.01.2014
DY20-0872802SA FD0115 91.928 89 9 21.01.2014
DY20-074209XSA FM1772 178.892 185 7 03.01.2013
Table 7.2: Data of blend 243 in Jan-2013
As we know that the date is the decision variable for applying the FIFO, in above matrix the ‘Last GR Date’ is our key column on the basis of which we will make FIFO allocations for the upcoming plans. The date is now arranged in the first row and in ascending order to adjust the leftover yarn. Now we consequently form three matrices which show the Leftover Inventory, Demand and the Balance Inventory.
FIFO Application for Blend-243 (January-2013)
LEFTOVER INVENTORY
Material Number Qty. Last GR Date
DY20-074209XSA 7 03.01.2013
DY20-0872707SA 59 12.01.2013
DY20-0272704ZB 17 15.01.2013
DY20-0872802SA 9 21.01.2014
DY20-094218XSA 10 22.01.2014
DEMAND
Material Number Demand Adjustment Manufacture Date
DY20-074209XSA 15 7 8 07.02.2013
DY20-0872707SA 21 21 0 26.02.2013
DY20-0272704ZB 9 9 0 01.03.2013
DY20-0872802SA 43 9 34 11.03.2013
DY20-094218XSA 14 10 4 19.03.2013
BALANCE INVENTORY
Material Number Qty. Last GR Date
DY20-0872707SA 38 12.01.2013
DY20-0272704ZB 8 15.01.2013
We repeat this exercise for the top four blends also, those are 871, 380, 271L-70 and 884.
FIFO Application for Blend-871 (April-2013)
LEFTOVER INVENTORY
Material Number Qty. Last GR Date
DY20-079308XSA 11 06.04.2013
DY20-0630352SA 16 18.04.2013
DY20-0978800SA 11 23.04.2013
DY20-0230378SA 52 28.04.2013
DY20-0978609SA 13 29.04.2013
DEMAND
Material Number Demand Adjustment Manufacture Date
DY20-079308XSA 17 11 6 03.05.2013
DY20-0630352SA 10 10 0 12.05.203
DY20-0978800SA 40 11 29 17.05.2013
DY20-0230378SA 21 21 0 21.05.2013
DY20-0978609SA 30 13 17 29.03.2013
BALANCE INVENTORY
Material Number Qty. Last GR Date
DY20-0630352SA 6 18.04.2013
DY20-0230378SA 31 28.04.2013
FIFO Application for Blend-380 (January-2013)
LEFTOVER INVENTORY
Material Number Qty. Last GR Date
DY20-047327XSA 11 02.01.2013
DY20-077302XSA 50 03.01.2013
DY21470-00564ZB 6 07.01.2013
DY21470-00630SA 10 08.01.2013
DY21770-00859ZB 10 16.01.2013
DY21740-00884SA 12 18.01.2013
DY20-08687XXSA 6 18.01.2013
DY21770-00845ZB 12 20.01.2013
DY21770-00845SA 10 20.01.2013
DY20-047308XSA 23 27.01.2013
DY20-077308XSA 7 28.01.2013
DY20-07699XXSA 6 28.01.2013
DY20-04626XXSA 14 29.01.2013
DY20-057302XSA 17 31.01.2013
DEMAND
Material Number Demand Adjustment Manufacture Date
DY20-047327XSA 34 11 23 03.02.2013
DY20-077302XSA 22 22 0 07.02.2013
DY21470-00564ZB 45 6 39 09.02.2013
DY21470-00630SA 18 10 8 14.02.2013
DY21770-00859ZB 32 10 22 17.02.2013
DY21740-00884SA 30 12 18 04.03.2013
DY20-08687XXSA 41 6 35 11.03.2013
DY21770-00845ZB 15 12 3 19.03.2013
BALANCE INVENTORY
Material Number Qty. Last GR Date
DY20-077302XSA 28 03.01.2013
DY20-047308XSA 15 27.01.2013
DY21770-00845SA 10 20.01.2013
DY20-047308XSA 23 27.01.2013
DY20-077308XSA 7 28.01.2013
DY20-07699XXSA 6 28.01.2013
DY20-04626XXSA 14 29.01.2013
DY20-057302XSA 17 31.01.2013
FIFO Application for Blend-271L-70 (April-2013)
LEFTOVER INVENTORY
Material Number Qty. Last GR Date
SYL271-0972329S 9 04.04.2013
SYL271-0976303Z 6 06.04.2013
SYL271-0876302Z 7 12.04.2013
SYL271-086817XZ 18 28.04.2013
SYL271-0272330Z 20 29.04.2013
SYL271-0972329Z 9 29.04.2013
SYL271-0876302S 9 29.04.2013
SYL271-0272330S 5 29.04.2013
DEMAND
Material Number Demand Adjustment Manufacture Date
SYL271-0972329S 42 9 33 05.05.2013
SYL271-0976303Z 67 6 61 13.05.2013
SYL271-0876302Z 23 7 16 21.05.2013
SYL271-086817XZ 10 10 0 30.05.2013
SYL271-0272330Z 5 5 0 4.06.2013
BALANCE INVENTORY
Material Number Qty. Last GR Date
SYL271-086817XZ 8 28.04.2013
SYL271-0272330Z 15 29.04.2013
SYL271-0972329Z 9 29.04.2013
SYL271-0876302S 9 29.04.2013
SYL271-0272330S 5 29.04.2013
FIFO Application for Blend-884 (March-2014)
LEFTOVER INVENTORY
Material Number Qty. Last GR Date
DY20-0878301SA 592 05.03.2014
DY20-09943XXSA 12 10.03.2014
DY20-089828XSA 8 15.03.2014
DY20-099810XSA 13 19.03.2014
DY20-099810XSA 17 22.03.2014
DY20-089828XSA 5 24.03.2014
DEMAND
Material Number Demand Adjustment Manufacture Date
DY20-0878301SA 120 120 0 01.04.2014
DY20-09943XXSA 10 10 0 12.04.2014
DY20-089828XSA 35 8 27 23.04.2014
DY20-099810XSA 42 13 29 29.04.2014
BALANCE INVENTORY
Material Number Qty. Last GR Date
DY20-0878301SA 472 05.03.2014
DY20-09943XXSA 2 10.03.2014
DY20-099810XSA 17 22.03.2014
DY20-089828XSA 5 24.03.2014
7.3.2 Floor Layout for FIFO
A simple material movement mechanism can be used to apply the FIFO technique for consumption of leftover yarn. Hence the time is the main factor in FIFO; we must arrange the material as per their admission in the inventory and the exit of material should be convenient from the material handling point of view. We divided floor on the basis of different blends as per their quantity.
`
Figure 7.3: A simple floor layout diagram for application of FIFO
7.3.3Monthly Review System of Yarn Room Inventory
Only applying FIFO is not sufficient for overcoming the problem of exceeding inventory, an integrated feedback system is also necessary for maintaining the inventory in its capacitive conditions. This can be done by a monthly review system. The review should be done by the plant’s SCM department and send the feedback to central SCM department which perform the MRP function for the factory.
Figure 7.4: A simple block diagram of review and feedback system
7.4 Reducing Future Inventory
Though the previous two techniques HML analysis and FIFO will be helpful to optimize the present inventory but how can we say that this problem will not occur in the future? For answering this question we have to enlist the reasons behind this problem. The yarn is left due to one or more of the following reasons:
The yarn is manufactured in higher quantity than required.
The yarn is left due to quality issue.
The yarn is left due to less production of one or more component which is required to weave the fabric.
The yarn is left due to fully or partially cancellation of the order by goods recipient.
The future inventory may be reduced by eliminating above reasons. The SCM department of Chhindwara plant and the central SCM department of the Raymond Company must do some exercises in order to overcome from the problem. Here we want the central SCM department of Raymond Company to pay attention on reformulating the MRP1. We have listed the top 10 blends which are higher in productivity.
Material Group Sum of
Ordered Quantity
(In Kg.) Sum of
Manufactured Quantity
(In Kg.) Sum of
Exceeded Quantity
(In Kg.) % Participation
243 117054.184 119338 2283.816 11.85%
243S-70 44615.253 46136 1520.747 7.89%
380 54380.848 55381 1000.152 5.19%
271L-70 26338.65 27098 759.35 3.94%
294-50 27884.48 28508 623.52 3.23%
250 9749.291 10354 604.709 3.14%
296L-70 9896.131 10457 560.869 2.91%
884 16851.764 17298 446.236 2.31%
266L-70 10007.019 10433 425.981 2.21%
296 21731.522 22134 402.478 2.09%
Table7.3: Top 10 blend of high productivity
CONCLUSION
Research and development is not a one time jobbut a continuous work; same thing is applied to inventory control or inventory management. Our case study is a special case of inventory control and the yarn room inventory is a special kind of inventory where all the technical aspects of inventory control such as lead time, buffer stock, ordering level, economic ordering quantity etc. are not applicable because the control of this inventory is not in the hand of inventory management team. The only job of the yarn room inventory’s staff is to receive the yarn from spinning department, store the yarn properly, deliver it to weaving department and to take care of leftover yarn also.
Since the factors affecting the inventory size of the yarn room inventory are not the inside factors but they somewhere lying in the field of Production, Planning and Control or somewhere in the Supply Chain Management; so we hardly tried to make an equilibrium between the PPC and yarn room inventory in order to eliminate all those factors which are affecting the inventory size. In a Birdseye view it seems that the exceeded inventory is all due to the leftover yarn but when we did an in-depth analysis from macro level to micro level, we found that there is also a major role of higher production rate due to which the yarn is continuously leaving over.
Our first task was to reduce the size of present inventoryas soon as possible; for this, we have classified the leftover yarn on the basis of HML analysis so that the yarn will be utilized according to the priority level. We have also enlisted those blends which are contributing very much in the exceeded size of the inventory. Our second task was to establish such a mechanism for future inventory control so that the same problem should not occur in the future; for this we have suggested FIFO for knitting the yarn and also the reformulation of MRP1 for those blends which are performing very well on machines.
Research and development is an all-time on-going process. Today’s solutions may become tomorrow’s problems but the show must go on. Finally in the end; I would like to conclude my thesis with the famous quotation ‘Stay hungry, Stay foolish’. This single statement contains all what I want to say about my work. Thank You!
BIBLIOGRAPHY
Islam,Md.Mazedul, Khan,Adnan Maroof, Islam,Md.Monirul, 2013, Textile Industries in Bangladesh and Challenges of Growth, Department of Textile Engineering, Daffodil International University, Bangladesh, Research Journal of Engineering Sciences, Vol. 2(2), 31-37.
Ondiek,Gerald Ochieng, 2012, Assessment of Materials Management in Kenyan Manufacturing Firms, University of Nairobi, Odhiambo Odera, Masinde Muliro
Devaraja, Dr.T.S, 2011, Indian Textile and Garment Industry, Department of Commerce, University of Mysore, Hassan,India.
Shahid Ali, 2011, Working Capital Management and the Profitability of the Manufacturing Sector: A Case Study of Pakistan’s Textile Industry. The Lahore Journal of Economics 16: 2 (Winter 2011): pp. 141’178.
Rahman, Mohammad Morshedur, 2011, Working Capital Management & profitability: A Study on Textile industry, ASA University Review, Vol. 5 No.1.
Mwansele,HA, Sichona,FJ, Akarro,RRJ, Determination of Inventory Control Policies at Urafiki Textile Mills Co Ltd ,Dar-es-Salaam, Tanzania, Business and Economics Journal, Volume 2011: BEJ-23.
Chiu,Lee-in Chen, 2007, The Policy, Institution And Market Factors In The Development Of Taiwan’s Textile/Garment Industry, Chung-Hua Institution for Economic Research, 75 Chang-Hsing Street, Taipei, Taiwan 106, Republic of China, Working Paper Series No.2007-2.
Taplip, Ian M, 2006, Restructuring and ReconFigureuration: The EU Textile & Clothing Industry Adapts a Change, Business Review, volume 18, pp. 172-186.
Allen, Donald S, 1997, Do Inventories Moderate Fluctuations in Output, economist at the Federal Reserve Bank of St. Louis.
Kumar,Pawan, 1996,Analytical Study of Inventory Management in Punjab State Electricity Board, Finance India, Vol. X No. 2, Pages’ 412’415.
Allen, Donald S, 1995, Changes in Inventory Management and the Business Cycle, economist at the Federal Reserve Bank of St. Louis.
Shafi, Mohammad, 1994, Unused Inventories ‘An Analytical Study, Management
Becker, Dan M, Stanley,Stephen, 1992, Evidence of Improved Inventory Control, Economic Review. January/February.
Shafi, Mohammad, 1992, Management Of Inventory-An Analysis Of Its Vital Dimensions,
Sharma,P.C,1984,Materials Management,Kitab Mahal, Allahabad.
Shore, Barry,1980, Operations Management, Tata Mcgrah-Hill, New Delhi.pp.363.
Lancioni, Richard, A & Howard Keith, 1978, Inventory Management Techniques,International Journal Of Physical Distribution & Logistics Management, Vol 8, ISS:8, pp. 388,428.
SINGAPOREAN Journal Of Business Economics, And Management Studies VOl.2, NO.7, 201459
University of Science and Technology, Journal of Business Studies Quarterly, Vol. 3, No. 3, pp. 40-49, ISSN 2152-1034.
Sajjad, Mehrunisa, Bukhari,Khuram Shahzad, Relationship between Working Capital Management and Profitability- Case of Pakistan Textile Sector, Institute of Management
Sciences Bahauddin Zakariya University Multan, Pakistan.
Management Review, Narsee Monjee Institute of Management Studies (NMIMS), Mumbai, pg 28-38
Review, Narsee Monjee Institute of Management Studies (NMIMS), Mumbai, pg 27-29