Using EFS and HVI Tested Cottons Part I: Fiber-to-Yarn ... deals primarily with producing an optimum quality/cost yarn from the fiber attributes associated with a bale of cotton; a

El Mogahzy- Measuring Economic Benefits to a Spinning Mill Using EFS® & HVI Tested Cottons

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Measuring Economic Benefits to a Spinning Mill Using EFS® and HVI Tested Cottons

Part I: Fiber-to-Yarn Analysis

Dr. Yehia El Mogahzy

WestPoint Stevens Professor

Auburn University Introduction Over the last twenty years, Cotton Incorporated EFS® system has set the standards for cotton bale management from the field to the textile mill and for selecting cotton mixes of optimum quality and maximum consistency. The results reported by hundreds of EFS® mill users in the United States and in other areas of the world clearly prove that this system stands as the world most viable approach to producing top quality yarns. Some of the major merits resulting from the implementation of the EFS® system, which have been reported by many EFS® mill users are [1,2, 3, 4,5]:

? The inherent capability to achieve a cost-effective bale management and cotton purchasing strategy

? The great potentials to minimize manufacturing cost ? The impact of EFS® system utilization on the quality consistency of end products in such

a way that EFS® end products are uniquely distinguished in the market place The economical merits of the EFS® system listed above are results of basic implementation of the EFS® system. However, they do require an organized effort and a great deal of management commitment to successfully accomplish. Two of the key criteria that should be met to achieve successful EFS® implementation are:

- The ability of a company to fully understand the system and realize its great potentials - The speed at which the company can adjust its management strategy to accommodate

effective and efficient implementation of the EFS® system These two criteria can be met at no additional cost to the company. They only require commitment and strive to do things differently using the exiting qualifications. In addition, continuous appropriate implementation of the EFS® system will eventually lead to substantial reduction in personnel involvement (personnel that can be switched to other areas in the company to do different tasks). This is a direct result of the great deal of systematic work that the EFS® system can perform, which otherwise would require many people to do. In a typical spinning company, the use of the EFS® system may range from basic utilization of the system to advanced utilization. Figure 1 illustrates the tasks involved in a basic implementation of the EFS® system. These mainly consist of bale management, warehouse management and HVI/EDI data handling. In summary, these are as follows:

- Well-defined bale management plan from the field to the textile mill passing through all the essential channels in the market flowchart. Typically, this plan may vary from one company to another depending on the domestic market at which the company is located and the different market channels that the company deals with. The EFS® system has built-in flexibility that accommodates different markets as evident by its global spread.


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- Warehouse management is a key aspect of the EFS® system. Bales should be distinguished by a number of criteria including cotton type, cotton source, gin identification and fiber properties. In addition, they should be stored according to pre-specified categories and groups assigned by the EFS® system. Bales should be stored in such a way that allows easy identification and retrieval. Details on the category and group systems can be found in the book written by El Mogahzy & Chewning, titled "Cotton Fiber to Yarn Manufacturing Technology" Published by Cotton Incorporated, 2002.

- HVI data are critical information in the process of selecting consistent cotton mixes by the

EFS® system. All bales that are handled by the EFS® system must be tested using the High Volume Instrument (HVI). The data generated by the HVI are utilized by the EFS® system algorithms for selecting cotton bale laydowns suitable for the spinning mill in question.

- EDI data are HVI fiber properties and bale information of each shipment sent

electronically by the merchants to the mill. The EFS®-MillNet system handles this data automatically.

The above tasks, if implemented properly, will allow a full basic implementation of the EFS® system. The outcome of this implementation will be reflected in consistent cotton mixes (or bale laydown) that represent a fiber profile of minimum variability. In this regard, the difference between a company using the EFS® system and a company using a manual approach could mean a substantial difference in cost, unnecessary use of many human resources, and frequent mistakes that can lead to major costs down the chain of processing and to major adverse impacts on the quality of yarn and end products.


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The second phase of EFS® implementation is the advanced phase. This phase stems from the fact that in today’s global market, the value added by utilizing a certain raw material has become the most important competitive factor. In recent years, we have witnessed the American cotton going global, competing with cotton varieties produced in different areas in the world. Although significant efforts have been made to globally standardize cotton classing, the final decisive factor of which cotton to use will always depend on the true utilization efficiency of the cotton. In this regard, three key factors should be addressed (see Figure 2): (a) Quantity Utilization Efficiency (QnUE) (b) Quality Utilization Efficiency (QlUE) (c) End Product Added Value (EPAV). The QnUE deals primarily with maximizing the utilization of the bale content or minimizing cotton waste. The QlUE deals primarily with producing an optimum quality/cost yarn from the fiber attributes associated with a bale of cotton; a classic example of QlUE is the called fiber-to-yarn strength efficiency (or fiber strength-yarn strength ratio). The EPAV primarily aims at selecting raw material suitable for a given end product or a given predetermined specifications of end product performance.

The advanced phase of the EFS® system complements the basic phase in many ways, specifically in relation to cost-related aspects. As indicated above, basic utilization of the EFS® system can yield immediate economical and technological gains to the spinner. However, in order to fully explore all the gains resulting from the use of the EFS® system, a company should be prepared to implement the advanced phase. Figure 3 shows some of the main elements of the advanced implementation. The primary critical tasks of this phase are as follows:


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? Task A: Using the EFS® system in determining the technological value of cotton and optimizing mix cost

? Task B: Exploring areas of material-related manufacturing cost reductions based on the diagnostic measures inherent in the EFS® system

? Task C: Producing yarns that are EFS®-Stamped for uncontested quality and low cost ? Task D: Characterizing the EFS® fiber profiles with respect to end product (fabric and

apparel) quality ? Task E: Establishing an overall systematic approach of measuring cost saving resulting

from the use of the EFS® system In this paper, the focus will be on Tasks A and B. In next year conference, Tasks C through E will be addressed in detail.

Cost Analysis: Basic Concepts The two basic economic components that determine the survival and prosperity of any business are cost and revenue. The overall financial status of a spinning company depends largely on the profit that a company makes from selling the yarn. This profit can only occur if there is a positive difference between the price of yarn (the yarn value in the marketplace) and the cost encountered to make the yarn. Figure 4 shows the key factors influencing yarn price and manufacturing cost in a spinning mill. The key to achieve a sound and consistent profit is to continually attempt to maximize revenue and minimize cost. Before proceeding with the discussion on how the EFS® system can assist in meeting these goals, we first discuss some basic economic concepts.


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Cost Cells

In general, a cost is defined as the value of economic resources used as a result of producing a product or offering a service. In this regard, a mill can divide the entire fiber-to-yarn system into a number of cells depending on the significance of the cost associated with each cell. Figure 5 shows two ways of classification of the fiber-to-yarn system cost cells. This type of classification allows better resolution of the cost analysis of each stage of processing so that priorities of cost reduction can be established. It is also important that each cost cell be associated with a cost unit (or output). In a spinning mill, the cost unit at each stage of processing is the pound or kilogram of intermediate or final product produced (e.g. kilogram fibers produced per hour from the opening and cleaning line, kilogram sliver produced from the carding or combing process, or kilogram yarn).

Another benefit of classifying the cost structure into cost cells is to determine the relative contribution of each stage of processing (or cost cell) to the overall manufacturing cost. For a given raw material (or cotton mix), the relative cost contributions of different cost cells are largely dependent on the spinning system being used. For instance, rotor spinning is expected to require lower cost than ring spinning within the coarse to medium yarn count range. In fine to very fine yarn count range, rotor spinning becomes neither feasible nor economical.

Manufacturing cost cells can be divided into three main cells, namely; preparation, ring spinning, and winding. The relative cost contributions of these three cells will depend on the yarn count produced. For coarse yarns, spinning preparation cell will encounter the largest cost among the three cells. This is primarily due to the labor cost. As the yarn count becomes finer, the cost


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associated with ring spinning increases at higher rate than that of preparation and winding. This is primarily due to labor and energy cost.

In light of the above discussion, a spinning mill producing coarse to medium counts of ring spun yarns (up to 25’s) should focus its initial cost reduction activities on the preparation stage. On the other hand, a spinning mill producing medium to fine counts of ring spun yarns (above 25’s) should focus its initial cost reduction activities on the spinning process itself. Obviously, this does not mean that other cells should be ignored.

Costing Methods

Another important cost concept is the method of costing. In general, there are two main methods: job costing and process costing. A job costing is typically used to ascertain the cost associated with a specific job or work order for which costs are separately collected and computed. This method of costing is normally implemented when a spinning mill has to produce a yarn type of special features that are not typically mass produced by the mill. Because of the unusual circumstances of the yarn required, separate cost analysis should be implemented. Process costing on the other hand is the commonly used method and it is performed for mass production environments in which standard procedures and continuous routine operations are used.

It is important that a spinning mill has a standard cost for each cost cell against which the actual cost can be compared. This standard test may be determined from expert analysis or from historical record of cost performance. The standard cost should represent the minimum possible cost that the cost cell should require for given yarn specifications. One of the difficulty associated with establishing a standard cost lies in the fact that some cost components are fixed (fixed costs) and others are variable (variable costs). In this case, the so called marginal costing can be


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implemented, in which cost is divided into fixed and variable costs. The focus of determining the cost associated with a cost cell can then be on the variable cost.

In general, fixed costs are those that do not change significantly with the change in output (or the number of units produced). In other words, they remain constant in "total" amount over a wide range of activity for a specified period of time and do not increase or decrease significantly when the volume of production varies. Variable costs on the other hand change in accordance to production level. Figure 6 gives examples of fixed and variable costs in the spinning mill.

Costs may also be divided into direct costs and indirect costs depending on the basis of their identification with a cost cell. Direct costs are those that are incurred for and conveniently identified with a particular cost cell. For a spinning mill, costs of raw material used, packing material, freight etc are direct costs. Indirect costs are general costs and are incurred for the benefit of a number of cost cells. In a spinning mill, power cost, administrative wages, managerial salaries, materials used in repairs etc represent indirect costs. Figure 5 gives examples of direct and indirect costs in a spinning mill.

It should be pointed that the use of the terms “direct” or “indirect” to describe costs will largely depend on the purpose of the cost analysis. In this regard, a direct cost in one situation may be considered as indirect in another situation.


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The term “expenses” is also commonly used to describe all costs other than material and labor. In this regard, one can also classify expenses into direct or indirect expenses using the same concept discussed above. Table 1 shows the basic expressions associated with cost formulation.

Table 1 Cost & Revenue Formulation Methods Cost Type Formula

Prime Cost ExpensesDirectLaborDirectMaterialDirect ?? Overhead ExpensesIndirectLaborIndirectMaterialIndirect ?? Total OverheadCostimeCostTotal ?? Pr

Uncorrected Profit [fixed cost is not considered]

P = (price/unit)x no. of units – (variable cost per unit)x no. of units

Corrected Profit P = R(q) – C(q) R(q) = revenue function, C(q) = cost function

Revenue Function R(q) R(q) = price per unit (p) x no. of units (q) = pq

Cost Function C(q) C(q) = Cfixed + Cavg x q Where Cavg = the average variable cost

Cost Function C(q) C(q) = Cfixed + ? ?q) x q where ? ?q) = a function expressing the change in variable cost with the number of units being produced Examples of ? ?q):

? ? ?q) = (Cavg – a.q) when a discount is placed on larger orders. In this case, the average variable cost decreases as the quantity, q, increases.

? ? ?q) = (Cavg + b.q) when the cost increases with larger orders due to additional preparation, more demand, higher price of raw material, etc. In this case, the average variable cost increases as the quantity, q, increases.

A spinning mill continuously aims at controlling manufacturing cost in all areas of manufacturing from the cotton mix to the yarn package. In this regard, there are ample opportunities of cost reduction. The area at which maximum cost reduction can be achieved is “fiber selection and cotton blending”. This is simply because raw material represents more than 50% of the total manufacturing cost of yarn. Furthermore, cotton price may fluctuate substantially from crop to crop, week to week and month to month. This represents continuous opportunities to make appropriate judgments of cotton purchasing and fiber utilization. As indicated earlier, the EFS® system can assists in the reduction of the cost of raw materials through two critical tasks:

? Task A: Using the EFS® system in determining the technological value of cotton and optimizing mix cost

? Task B: Exploring areas of material-related manufacturing cost reductions based on the

diagnostic measures inherent in the EFS® system These two tasks are discussed below.


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TASK A: Determining the Technological Value of Cotton and Optimizing Mix Cost Introduction: Factors Determining the Value of Cotton in the Marketplace One of the difficult aspects associated with the cotton market is the inability to predict cotton price from year to year and sometimes from period to period within a year. Now, with the market going global, forecasting cotton price has become a more complex task due to the many unknown factors that are often politically oriented. Indeed, over the years cotton price has had its ups and downs and economists have always found a way to explain the fluctuating trends. One of the primary reasons for cotton price fluctuation is the complex interaction between supply and demand factors. Table 2 lists examples of supply and demand factors determining cotton price.

Table 2 Supply and Demand Factors Determining Cotton Price Demand Factors Supply Factors Availability (to consumer) Yield

Price acceptability by consumers Price desired by suppliers

Styles and fashion attraction Speed of technological development (R&D) Alternatives & substitutes (fibers) Alternatives & substitutes (crops) Quality Cost of quality

Primary factors influencing cotton supply include the price of cotton received by producers relative to prices for alternative crops, anticipated environmental changes, total cost of lint production (land rent, planting seed, fertilizer, harvesting and ginning). The price received by the producer is the key factor in the supply aspect. This price is subject to many factors including: global competition, exchange rates, and economical gains resulting from developing technologies. In some countries, these important factors are overshadowed by governments subsiding producers, and distorting markets resulting from government polices. On the demand side, consumers today have immense choices of fibers and end products to choose from. Traditional demand factors include income, price, alternatives (e.g. synthetic or other natural fibers), and fashion. In today’s competitive market, consumer demand is often a reaction to successful promotional efforts. This places new challenges on most suppliers from the fiber producers to the spinners and weavers. More specifically, the spinner today must sell a yarn that is fully described in terms of end product performance. This point will be addressed in the second part of this study. Economical analysts normally analyze the market value of cotton in terms of many factors influencing the price per pound of cotton (Chen, Ethridge, 1995, 1996, 1997, 1999, Karaky, R.H., D. Ethridge., and H. Floeck, 1999). These factors include:

? Recognized fiber attributes (e.g. Micronaire, color grade, strength, and staple length) ? The type of sale (fixed or call) ? The region of origin ? Other contract stipulations

Using a database representing these factors, the analyst develops price-quality relationships by regressing the cotton price on fiber characteristics and other non-quality variables. The multiplicity of factors influencing the price per pound and the declining marginal productivity of fiber attributes in the manufacturing process (Chen and Ethridge, 1996) often lead to non-linear relationships. Another type of economical analysis is through developing relationships describing fiber consumption by textile manufacturers (Plssmann and Jones, 1999, Sanford, 1988, Lewis, 1972).


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In these relationships, the primary dependent variable is the fiber consumption and independent variables may include:

? The price of cotton ? The price of synthetic fibers ? Yarn price ? Fabric price

The approaches mentioned above, namely price and cotton consumption modeling, provide very useful information about the marketing profile of cotton fibers, and the competitive status between cotton and other synthetic fibers. A review of the many models developed in recent years reveals the following points:

? Cotton color is a dominant factor in determining the price of cotton in the global market ? The staple length significantly influences cotton prices ? Premiums and discounts associated with color and staple length vary depending on the

cotton source region ? Fiber strength generally affects the cotton price in all regions. However, larger premiums

for strength may be paid in some regions than others. Regions that provide overall high strength fibers do not get as much premiums for strength as regions that provide wide ranges of fiber strength

? The market value of cotton typically increases as Micronaire increases, then decreases as Micronaire increases beyond an optimal value. This parameter is highly regional sensitive because of its known association with maturity

? Fluctuation in cotton fiber prices, coupled with low prices of cotton textile products often result in a profit margin squeeze at the intermediate textile mill level

? Mill cotton fiber consumption is more related to the price of the yarn used for apparel end-uses than to fiber price

? Mill sensitivity to output price is apparent for those yarn and fabric types used for apparel end-uses. Lower sensitivity is normally shown for yarn and fabric types used for home-textiles end-uses. This means that yarns and fabrics applied to apparel are more susceptible to price fluctuations at the output level than those used for home-textile end uses. This is due to the higher value-added goods of home textiles without a necessary increase in the amount of fiber input used.

Another view of the cotton value in the market place is that based on examination of the proportions of the retail dollar received by cotton industry segments. This type of analysis is very difficult because of the difficulty of accessing all the data required from different industry segments, and the immense factors involved in determining the proportion of the retail dollar for each segment. In 1998, Bondurant and Ethridge presented an excellent paper to the U.S. Cotton Beltwide Conference concerning this important factor using data from the year 1995. The underlying assumption of their study was that the final retail value of a cotton end product reflects the aggregate value of production, including the costs of marketing services of each cotton industry segment and the profits associated with those services. Every participant in the cotton market receives a proportion of these final retail values and has different cost of producing the different types of value-added. The authors defined the margins by the differences between the prices at two different points in the market channel. These margins are made up of the costs associated with production and marketing services and profits from providing the services between the two points. According to Bondurant and Ethridge: “Profit can vary with many factors, including risk and competitive structure of the market i.e. market power of individuals, firms, or groups of firms. Demand and supply interactions at the retail level dictate the final retail values of cotton consumer goods. Price signals communicate


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product value from consumers to producers and can be identified at certain points in the marketing channel. Retail price changes should be transmitted through the market back to the farm level if the market is operating efficiently”. A key point in the Bondurant and Ethridge paper was that the cotton producer’s share of the final retail value of a cotton product is larger when the rest of the marketing chain operates efficiently (i.e. at optimum cost). In this regard, the authors state: “If a market segment is inefficient, it will produce a product at higher costs than if it was efficient. The inefficient market segment may try to pass these higher production costs back to the previous market segment in the marketing channel in the form of paying less for the raw inputs. This translates to lower prices for the producers at the beginning of the marketing channel. Market participants may be able to pass higher costs backwards in the marketing channel, but they are less likely to be able to pass these cost increases forward in the marketing channel”. Among the many factors influencing the proportions of the retail dollar received by cotton industry segments, consumer’s demand for cotton products is the most important one. An expansion in this demand will certainly result in significant increases in the proportions of the retail dollar received by cotton industry segments. In general, there are three main categories of cotton end products: apparel, home furnishings, and industrial products. In the U.S. market, apparel products are generally divided into two main categories of apparel: national brands (in the 1990’s it was about 30% of the market) and store or private labels and niche brands (about 70%). These are dynamic factors and are likely to change over the years, which call for close monitoring of market trends and directions. In general, the U.S. apparel market is subject to tough competition by foreign products resulting from an open market for products of good quality made by inexpensive labor. It is well recognized that apparel manufacturing is typically a very-labor intense sector. The home furnishing manufacturing, on the other hand, is a more automated sector. However, only few companies in the U.S. produce most of the home furnishing products (sheets and towels). In addition, this market only involves few item types. This lack of product diversity often results in little flexibility when establishing prices for these items. In light of the above discussion, it follows that in order for the industrial countries to survive in the textile global market, they must implement new economical and technological approaches. These approaches should be robust against the differential market disadvantages imposed by factors such as flexible trade regulations and cheap labor. In addition, they should set universal standards of quality and cost factors that can eventually result in a global competitive balance. The Technological Value of Cotton A spinning mill primarily reflects a value-in/value-out system. The value-in is represented by the raw material being used and the value-out is represented by the yarn being produced. The term “value” is used here to indicate a combination of price and quality. In this regard, the best value-in (raw material value) situation is achieved when quality is at is highest possible level and price is at its lowest possible level. On the other hand, the best value-out (yarn value) is achieved when quality is at its highest possible level and price is correspondingly high (from a spinner viewpoint). This is the only way to accomplish profit in the spinning business. Yet, it is the most difficult way to achieve profit particularly in today’s competitive market. The real dilemma here is that the value-in contributes to the value-out in an imbalanced and seemingly unfair way. Simply put, if the cotton price is doubled next month, the yarn price will not increase linearly with this increase. This leaves the spinner profit very vulnerable to the price of raw material. In other words, just as the spinner is interested in discount cotton, the yarn buyer (weaver or knitter) is also interested in discount yarn. This is the traditional “commodity-in/commodity-out” approach. Very few companies have been able to overcome this traditional


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approach through creative and intelligent ideas implemented at both ends of the value-in/value-out system. The EFS® system can provide substantial assistance in this implementation. In light of the above discussion, it is important that the spinning mill seeks efficient and effective ways to maximize the value of cotton (minimum price/maximum quality) and the value of yarn (maximum price gain/maximum quality) at the least cost possible. Using the advanced implementation methodologies of the EFS® system, this complex objective can be met through a number of tasks (see Figure 7). These tasks include (details on these tasks can be found in reference 4]:

? Determine what cotton types are suitable for your process (i.e. spinning system used,

yarn count and yarn twist, and end product). EFS® users have access to many useful guidelines in this regard through direct communication with Cotton Incorporated. In addition, there is some literature that can assist in this regard [e.g. ref. 4].

? Among the different cotton types accessible in the market, select different cotton

types that can meet in part or in full the technological and quality requirements of your process (i.e. spinning system used, yarn count and yarn twist, and end product). The key to an appropriate selection is to achieve a cotton mix exhibiting the average desired fiber properties with respect to your process, and consisting of cottons that exhibit values of fiber noise that are below your maximum acceptable limits. Fiber noise here implies short fiber content, neps, trash, and contamination.

? Obviously, the set of cotton types selected in the previous task will also exhibit

different costs (price plus accessibility expenditures). In this case, it is important to determine an optimum cost of the cotton mix. In simple terms, it is important to determine what proportion of each cotton type should be used in the mix (or what percent of each cotton type should be purchased) so that the net cotton mix exhibits the desirable fiber attributes, the least fiber noise and at the lowest cost possible.

? Determine the impact of the above two tasks on the actual values of yarn quality. It

should be pointed out that different yarn types will be different in their desired levels of yarn quality

? The above tasks represent a cycle that can be repeated for different processes. In

addition, the analysis can be made systematic so that if the impact is not satisfactory, the cycle can be repeated until an optimum raw material cost can be achieved.

It should be pointed out that the above tasks can be made largely systematic through developing simple software programs that can perform the tasks in a user-friendly atmosphere and allow the user a great input and manipulation depending on its specific applications.


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Task B: Exploring Material-Related Manufacturing Cost As indicated earlier, the cost of yarn manufacturing involves fixed costs and variable costs (Figure 6). Typically, the fixed costs are function of a number of factors that are unique for each operation. These factors include:

? The size and the capacity of the spinning mill (e.g. cotton consumption and number of spindles)

? The standard of living or the economical status of the country in which the spinning mill is operating. Some economical experts tend to blame the deteriorating textile industry in industrialized countries solely on labor cost. Other experts believe that some of the countries that have low labor cost also have high capital cost, which tends to even the base for competitive market. These factors should be accounted for in any analysis of wage differentials.

? Taxes, utility, lease cost, transport, and regulation fees The variable cost is the cost that changes in accordance to production level. In a classic cost function, the fixed and variable costs are represented as follows:

qCCqC avgfixed .)( ??

where Cfixed = the total fixed cost Cavg = the average variable cost


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q = the number of units (in a spinning mill, a unit may be expressed in kilogram or lb) The EFS® system can assist in reducing both sources of cost. On the long run, the fixed cost can be reduced through a substantial reduction in manpower, redistribution of personnel assignments in such a way that can provide maximum service to the spinning mill, and better logistics and production control. In addition, utilization of appropriate cotton mixes can result in a long-term improvement in machinery performance, and in a longer service life of opening and carding wires. With regard to variable costs, the EFS® system aims at continually reducing manufacturing cost through the following critical tasks:

? Maximizing fiber-to-yarn yield efficiency (QnUE) ? Maximizing fiber-to-yarn conversion efficiency (QlUE) ? Diagnosing quality problems ? Improving yarn productivity and efficiency

Fiber-to-Yarn Yield (FYY) Efficiency Fiber-to-yarn yield efficiency can be defined by the quantity of yarn (in kg or lb) that can be produced from a certain quantity of bale fibers (in kg or lb). This is expressed as follows:

100)(cot

)( ??lbquantitytonbale

lbquantityyarnEfficiencyFYY

The above expression has two virtual extremes: 100% efficiency at which all cotton in the bales is converted into yarn (no waste) and zero efficiency at which no yarn was produced (all waste). Typical values of FYY efficiency are 80% for carded yarns, and 75% for combed yarns. This is a result of the additional waste imposed by combing (comber noils).The key to determine a reliable FYY efficiency is to determine the various components influencing it. Figure 8 shows these components. The EFS® system can assist in maximizing the yield through appropriate selection of cotton types that have minimum potential waste. In this regard, critical fiber properties are cotton grade, fiber fineness (Micronaire), fiber length, length uniformity, short fiber content, and fiber maturity. In some situations, where waste materials are recycled by mixing with the primary material, the EFS® system can assist in the addition of careful and pre-calculated proportions of waste fibers to the primary material. Unfortunately, there are no standard procedures to implement these tasks and they have to be performed in view of the given conditions of the spinning mill in question (machinery type, cotton types used, cotton fiber properties, yarn type, and end product type). It should be pointed out that the FYY efficiency represents one of the key factors that differentiate between the performance of one spinning mill and another. It is directly related to variable cost reduction since each 1% increase in FYY efficiency could mean a major reduction in the manufacturing cost and additional thousands of pounds of the yarn produced. Indeed, a company using 500,000 cotton bales annually can save over $15 million dollar (based on average upland cotton price in the last five years) by reducing its waste by only 1%.


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Fiber-to-Yarn Conversion (FYC) Efficiency One of the key aspects of producing a high quality yarn is to achieve an optimum conversion of fiber properties into yarn characteristics. For example, it is well known that fiber strength to yarn strength conversion efficiency may range from 60% to 90% depending on yarn count and twist, yarn type, cotton type and fiber properties (length, fineness, strength, and elongation). It is also well known that longer, finer, and stronger fibers can produce higher strength efficiency than shorter, coarser, and weaker fibers. Appropriate selection of optimum combinations of these fiber properties is the only way to produce optimum strength efficiency. The EFS® system provides many ways to achieve this optimum combination. Indeed, it is through the use of the EFS® system that a deficiency in the value of one fiber characteristic can be compensated for by an improvement in another fiber characteristic. This approach has been proven to be both economically and technologically sound. It should be pointed out that the key aspect of yarn strength is consistency. During weaving, the yarn does not break when the tension exceeds its average strength; it breaks when the tension exceeds the strength of the weakest point of the yarn. It is important therefore to achieve consistent yarn strength with minimum weak points. This can only be accomplished through appropriate fiber selection and consistent blending. In other situations, a combination of strength and flexibility or pliability may be required (mostly in knit yarns). In this case, the cotton mix should be selected in such a way that minimum acceptable strength associated with high yarn flexibility is obtained. Advanced implementation of the EFS® system can surely accomplish this goal.


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The issue of fiber-to-yarn conversion efficiency is a detailed one, and it has to be dealt with in view of the application in hand. This is because, yarn quality is typically defined in view of the type of processing used and the end product intended. In general, the spinner may define yarn quality as an index of appearance, strength, uniformity, and level of imperfections. The knitter may have more detailed criteria of yarn quality. These may include: • A yarn that can unwind smoothly and conform readily to bending and looping while

running through the needles and sinkers of the knitting machine. This translates to flexibility and pliability.

• A yarn that sheds low fly in and around the knitting machine. This translates to low hairiness and low fiber fragment content

• A yarn that leads to a fabric of soft hand and comfortable feeling. This translates to low twist, low bending stiffness, and yarn fluffiness or bulkiness.

• A yarn that has better pilling resistance. This translates to good surface integrity. The weaver may have a different set of yarn quality criteria: • A yarn that can withstand stresses and potential deformation imposed by the weaving

process. This translates to strength, flexibility, and low strength irregularity. • A yarn that has a good surface integrity. This translates to low hairiness and high

abrasion resistance. • A yarn that can produce defect-free fabric. This translates to high evenness, low

imperfection, and minimum contamination. In light of these different and often conflicting views of yarn quality, the spinner must customize the yarn to meet its intended purpose. In this regard, the EFS® system represents a powerful tool to meet different end product and processing requirements through appropriate selections of the combinations of fiber attributes suitable for each process. Through the use of the EFS® system quality logistics can be accomplished so that different fibers can be used for different purposes corresponding to fiber capability. Again, the issue of FYC efficiency has to be dealt with through advanced implementation of the EFS® system in which mill management is committed to take appropriate actions and make intelligent decisions. It is important to point out that such implementation can be achieved at minimum or no disturbance to mill production. Again, in today’s competitive market FYC represents one of the secret recipes of success that can differentiate between the performance of one spinning mill and another. Diagnosing Quality Problems When quality problems occur, a logical question that typically arises is whether the problem is fiber-related or machine-related. The difficulty associated with this question stems from the fact that there is a great deal of fiber/machine interaction that makes it difficult to isolate each effect efficiently. This point was clearly realized in the early generation of the EFS® system. It was addressed through developing a prediction (regression) equation relating laydown fiber properties to some quality parameters (e.g. yarn strength or yarn irregularity). The predicted profile of the quality parameter was then compared with the actual profile. A reliable prediction equation based on sound mill data can provide good prediction of the quality parameter. As a result, the predicted profile should agree (at least in trends) with the actual fiber profile as shown in Figure 9. When the actual yarn quality profile deviates from the predicted profile (as shown by the dotted circle areas of Figure 9), the difference typically indicates processing-related problems.


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Improving Yarn Productivity and Efficiency As indicated earlier, variable cost is associated with the number of units produced by the spinning mill. Commonly, the unit is represented by yarn weight in kilogram or pound. It is important therefore to evaluate how the EFS® system can influence the production rate directly or indirectly. The yarn production rate primarily depends on three main factors: spinning system, yarn count and yarn twist. Figures 10 and 11 show ideal production rates for ring spinning and rotor spinning at different spindle or rotor speeds, for different yarn counts, and different twist multiplier. These rates are ideal in the sense that they assume no loss in production efficiency, no endsdown, and a smooth flow of material through the spinning process. They also assume that the mechanical twist inserted will be approximately equal to the actual twist obtained in the yarn (a key aspect determined only by fiber properties). Deviations from these ideal rates will immediately result in loss. Assuming that the spinning machine is operating under optimum conditions, the primary interruption will result from a variation in the incoming material. Although this variation can result from between-machine variation in the spinning preparation process, it is often the cotton mix that is to be blamed when excessive endsdown or loss of efficiency is encountered. In this regard, different spinning systems are different in their sensitivity to particular fiber attributes. Table 3 shows material-related causes of endsdown or loss of production efficiency of the three major commercial spinning systems. These causes are listed according to their order of importance.


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All the material-related causes of endsdown or loss of production efficiency can be handled through appropriate fiber selection and consistent blending. Note that endsdown do not occur due to particular average levels of fiber properties; they occur due to variation in the values of fiber properties, or excessive levels of fiber noise (short fibers, trash, and contamination). Overcoming these problems represent primary tasks that can be performed by the EFS® system. It is very important therefore that spinning mills utilizing the EFS® system monitor endsdown and production efficiency to measure the gain resulting from this system. This is particularly important for new mills that have been implementing different approaches of bale management. Table 3. material-related causes of endsdown or loss of production efficiency of the three major commercial spinning systems

Spinning Type

Material-Related Causes of Endsdown

Ring Spinning (or Compact Spinning)

? Variation in fiber length (short fiber content) ? Variation in fiber fineness ? Variation in roving twist (caused by inconsistency of

fiber length and fineness) ? Variation in fiber elongation ? Presence of trash particles

Rotor Spinning

? Short fibers ? Trash particles ? Excessive neps or seedcoat fragments ? Variation in fiber fineness ? Fiber contamination

Air-Jet (Vortex Spinning)

? Trash particles ? Short fibers ? Fiber stiffness (elongation and length) ? Fiber contamination

Fiber-to-Yarn Conversion (FYC) Efficiency: Roles of Carding & Combing The process of minimizing the cost of yarn manufacturing should emphasize the effects of carding and combing on FYC efficiency. These two stages of processing influence the three main noise parameters: short fibers, neps and trash. The carding machine represents the most intense opening and cleaning process in the entire spinning line. It is responsible for three basic functions:

? Finalizing the opening and cleaning process for carded yarns ? Removal of fiber neps ? Forming the first linear fiber strand (carded sliver)

In relation to opening and cleaning, it is well known that long fibers are more sensitively influenced by the carding process than medium or short fibers. In other words, the longer the fiber, the higher the risk of fiber breakage during carding. Similarly, finer fibers have greater risk of damage than coarser fibers by virtue of their larger amounts (by number) during carding. This


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is why it is often the case that the merits of using long and fine fibers over short and coarse fibers are not reflected in the quality of yarn. The short fiber outcome of the carded sliver will have a significant effect on the outcome of the combing process. In other words, carded slivers of high short fiber content will yield combed slivers of high short fiber content in comparison with carded slivers of low short fiber content and at the same noil percent level. This point is illustrated in Figure 12. It is also important to realize that for a given average fiber length and fiber fineness, different cotton types are expected to exhibit different propensities for opening and cleaning. Figure 13 illustrates this point. This is a fact that is well realized by spinners who deal with a wide range of cotton types and continuously changing cotton mixes. These are key issues that should be addressed and coordinated with the process of fiber selection and blending. All spinners clearly realize that the higher the comber noils, the higher the overall waste and the greater the cost of yarn manufacturing. However, they tend to use high noils percent to improve the quality of the comber sliver and the yarn. What spinners need to realize is that the increase in noils percent, as much short fibers that can be extracted, can also extract long fibers (by-weight). This effect becomes more significant the longer the fiber length and the finer the fibers used. The above discussion reveals a major technological/economical trade-off that the use of EFS® system can greatly assists in optimizing its effect. From a technological/quality viewpoint, the increase in noils will result in improvement in yarn quality and spinning performance up to a certain point where technological advantages will disappear and in some situations a reverse in quality may occur (too much loss of good fibers). From an economical viewpoint, the initial increase in noils will result in economical advantage resulting from a quality upgrade that yields value-added quality and price premium. This advantage can be measured by determining the difference between price premium resulting from a certain noils level and the cost associated with fiber waste. A positive difference will obviously justifies noils extraction. Again, this trend will continue until a point is reached where the difference becomes negative and economical gains are turned into losses. Accordingly, an optimum trade-off between the technological/quality advantage and the economical gains/losses should be achieved. This optimum trade-off could certainly mean the true difference in profit margins. The trade-off discussed above is conceptually illustrated in Figure 14. As indicated earlier, the fiber type and fiber characteristics used represent key criteria in determining an optimum trade-off. This is where the EFS® system can truly assist. Similar concepts of cost reduction can be illustrated for trash content (cleaning efficiency) and neps (nep removal efficiency). The key point here is achieving the reduction in these unwanted attributes at minimum fiber damage or maximum fiber utilization.


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Closing Remarks of this Part of the Analysis This paper reveals many of the merits resulting from the use of the EFS® system in the area of cost reduction. The basic implementation of the EFS® system can provide immediate cost reductions by virtue of the fact that bale management and decisions associated with appropriate cotton mix selection can be time-consuming and resource-consuming. Art and experience have been a part of this industry practice for many years. In today’s technology, yesterday’s experience may provide very little to today’s practice. The EFS® system combines reliable science with mill-proven educated experience to achieve the best bale management strategy and to formulate consistent cotton mixes that are designed with respect to the spinning system in use, the type of yarn, and the type of end product. Advanced implementations of the EFS® system can maximize the potential merits of the system. Like any powerful tool, it is how we use it is what makes the difference. In part II of this series, the focus will be on the end product (fabrics, apparel, etc.). In this part, we will show how the merits of the EFS® system can truly expand to the final product using actual examples from textile mills.


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References

1. Johnson Rober Go, Jr. General manager, Litton Mills, Inc., Partners in Progress: Litton Mills & The EFS® system, 15th Annual, EFS Conference, 2002

2. Alan J. Barber, Director of Purchasing, Delta Woodside, EFS® System- How the System Has Helped Delta Woodside. 14th Annual, EFS Conference, 2001.

3. El Mogahzy, Y.E., Fabric Defects- The Role of the Cotton Mix, 13th Annual, EFS Conference, 2000

4. El Mogahzy, Y. E., and Chewning, C. Jr., "Cotton Fiber To Yarn Manufacturing Technology", Published by Cotton Incorporated, 2002

5. El Mogahzy, Y. e., "Statistics & Quality Control for Engineers & Manufacturers" From Basic to Advanced Topics, Published by Quality Tech Press, 2002

6. Stryckman, J. Une Mèthode de Mesure de la Productivitè du Travail et du Matèrial en Filature de Coton, Centexbel, Belgium, May 1983

7. Lord, P. R., Handbook of Yarn Production, Technology, Science and Economics, CRC-WP, The Textile Institute 2003

8. Chen, C. and Don E. Ethridge. “Premiums and Discounts Paid for Cotton Fiber Quality Attributes by U.S. Manufacturers.” 1995 Beltwide Cotton Conferences,Proceedings (Addendum). Cotton Economics and Marketing Conference, National Cotton Council, Memphis, TN, pp. 92-96.

9. Chen, C. and Don E. Ethridge. “Valuation of Cotton Characteristics by U.S. Textile Manufacturers.” 1996 Beltwide Cotton Conferences, Proceedings. Cotton Economics and Marketing Conference, National Cotton Council, Memphis, TN, pp. 427-434.

10. Ethridge, D. E., and C. Chen. “Values Placed on US Cotton-fiber Attributes by Textile Manufacturers.” The Journal of Textile Institute, 88 (No.1, 1997): 4-12.

11. Karaky, R.H., D. Ethridge., and H. Floeck. “Cotton Quality Price Differentials Paid by US Textile Mills.” 1998 Beltwide Cotton Conferences, Proceedings, Cotton Economics and Marketing Conference, National Cotton Council, Memphis, TN, pp. 370-373.

12. Zhang, P., S. M. Fletcher, and D. E. Ethridge. 1994. Interfiber competition in textile mills over time. Journal of Agricultural and Applied Economics, 26(1), 173-182.

13. Dodd, E., Oxenham, W., Outlook for the U.S. Short Staple Industry, JTATM, Vol. 2, Issue 3, Summer 2002.

Documents

Using EFS and HVI Tested Cottons Part I: Fiber-to-Yarn ... deals primarily with producing an optimum quality/cost yarn from the fiber attributes associated with a bale of cotton; a