By: – T.Sureshram
Junior Scientific Officer, Department of Textile Physics,
The South India Textile Research Association, Coimbatore-14

Combination of textile technology and medical sciences has resulted into a new field called medical textiles. Medical textiles are one of the most rapidly expanding sectors in the technical textile market. Textile materials in the medical textile field gradually have taken on more important roles. The wide range of textile products used in the medical industry are classified in to four major segments namely non-implantable materials, implantable materials, extracorporeal devices and healthcare & hygiene products. This paper deals with the specifications/properties required and different types of test methods involved for evaluating the characteristics of the medical textile products.

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Testing Specification

Standardisation Of Testing

When a textile material is tested certain things are expected from the results. Some of these are explicit but other requirements are implicit. The explicit requirements from the results are either that they will give an indication of how the material will perform in service or that they will show that it meets its specification. The implicit requirement from a test is that it is reproducible, that is if the same material is tested either at another time, or by another operator or in a different laboratory the same values will be obtained. In other words the test measures some ‘true’ or correct value of the property being assessed. If the test results vary from laboratory to laboratory then the test is not measuring anything real and it is pointless carrying it out. However, the values that are obtained from testing textile materials are not expected to be exactly the same, so that appropriate statistical criteria should be applied to the results to see whether they fall within the accepted spread of values.

The lack of reproducibility of test results can be due to a number of causes.

Variation in the material

Most textile materials are variable, natural fibres having the most variation in their properties. The variation decreases as the production progresses from fibres to yarns to fabrics, since the assembly of small variable units into larger units helps to smooth out the variation in properties. The problem of variable material can be dealt with by the proper selection of representative samples and the use of suitable statistical methods to analyse the results.

Variation caused by the test method

It is important that any variations due to the test itself are kept to the minimum. Variability from this source can be due to a number of causes:

1 The influence of the operator on the test results. This can be due to differences in adherence to the test procedures, care in the mounting of specimens, precision in the adjustment of the machine such as the zero setting and in the taking of readings.

2 The influence of specimen size on the test results, for instance the effect of specimen length on measured strength.

3 The temperature and humidity conditions under which the test is carried out. A number of fibres such as wool, viscose and cotton change their properties as the atmospheric moisture content changes.

4 The type and make of equipment used in the test. For instance pilling tests can be carried out using a pilling box or on the Martindale abrasion machine. The results from these two tests are not necessarily comparable.

5 The conditions under which the test is carried out such as the speed, pressure or duration of any of the factors.

It is therefore necessary even within a single organisation to lay down test procedures that minimise operator variability and set the conditions of test and the dimensions of the specimen. Very often in such cases, factors such as temperature, humidity and make of equipment are determined by what is available.

However, when material is bought or sold outside the factory there are then two parties to the transaction, both of whom may wish to test the material. It therefore becomes important in such cases that they both get the same result from testing the same material. Otherwise disputes would arise which could not be resolved because each party was essentially testing a different property.

This requires that any test procedures used by more than one organisation have to be more carefully specified, including, for instance, the temperature and humidity levels at which the test takes place. The details in the procedure have to be sufficient so that equipment from different manufacturers will produce the same results as one another. This need for standard written test methods leads to the setting up of national standards  for test procedures so making easier the buying and selling of textiles within that country. Even so certain large organisations, such as IWS or Marks and Spencer, have produced their own test procedures to which suppliers have to conform if they wish to carry the woolmark label or to sell to Marks and Spencer.

Most countries have their own standards organisations for example: BS (Britain), ASTM (USA) and DIN (Germany) standards. The same arguments that are used to justify national standards can also be applied to the need for international standards to assist world-wide trade, hence the existence of International Organization for Standardization (ISO) test methods and, within the European Union, the drive to European standards.

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Reasons For Textile Testing

The testing of textile products is an expensive business. A laboratory has to be set up and furnished with a range of test equipment. Trained operatives have to be employed whose salaries have to be paid throughout the year, not just when results are required. Moreover all these costs are non productive and therefore add to the final cost of the product. Therefore it is important that testing is not undertaken without adding some benefit to the final product.

There are a number of points in the production cycle where testing may be carried out to improve the product or to prevent sub-standard merchandise progressing further in the cycle.

Checking raw materials

The production cycle as far as testing is concerned starts with the delivery of raw material. If the material is incorrect or sub-standard then it is impossible to produce the required quality of final product.

The textile industry consists of a number of separate processes such as natural fibre production, man-made fibre extrusion, wool scouring, yarn spinning, weaving, dyeing and finishing, knitting, garment manufacture and production of household and technical products. These processes are very often carried out in separate establishments, therefore what is considered to be a raw material depends on the stage in processing at which the testing takes place. It can be either the raw fibre for a spinner, the yarn for a weaver
or the finished fabric for a garment maker. The incoming material is checked for the required properties so that unsuitable material can be rejected or appropriate adjustments made to the production conditions. The standards that the raw material has to meet must be set at a realistic level. If the standards are set too high then material will be rejected that is good enough for the end use, and if they are set too low then large amounts of inferior material will go forward into production.

Monitoring production

Production monitoring, which involves testing samples taken from the production line, is known as quality control. Its aim is to maintain, within known tolerances, certain specified properties of the product at the level at which they have been set. A quality product for these purposes is defined as one whose properties meets or exceeds the set specifications. Besides the need to carry out the tests correctly, successful monitoring of production also requires the careful design of appropriate sampling procedures and the use of statistical analysis to make sense of the results.

Assessing the final product

In this process the bulk production is examined before delivery to the customer to see if it meets the specifications. By its nature this takes place after the material has been produced. It is therefore too late to alter the production conditions. In some cases selected samples are tested and in other cases all the material is checked and steps taken to rectify faults. For instance some qualities of fabric are inspected for faulty places which are then mended by skilled operatives; this is a normal part of the process and the material would be dispatched as first quality.

Investigation of faulty material

If faulty material is discovered either at final inspection or through a customer complaint it is important that the cause is isolated. This enables steps to be taken to eliminate faulty production in future and so provide a better quality product. Investigations of faults can also involve the determination of which party is responsible for faulty material in the case of a dispute between a supplier and a user, especially where processes such as finishing have been undertaken by outside companies. Work of this nature is often contracted out to independent laboratories who are then able to give an unbiased opinion.

Product development and research

In the textile industry technology is changing all the time, bringing modified materials or different methods of production. Before any modified product reaches the market place it is necessary to test the material to check that the properties have been improved or have not been degraded by faster production methods. In this way an improved product or a lower-cost product with the same properties can be provided for the customer. A large organisation will often have a separate department to carry out research and development; otherwise it is part of the normal duties of the testing department.

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Basic Structural Features of Spun Yarn

The end product of the cotton fiber-to-yarn conversion system is a spun yarn or a staple-fiber yarn, which is suitable for making numerous end products from knit apparels to woven fabrics, from towels to sheets, and from carpets to industrial fabrics. The diversity of yarn-based products results in different views of what constitutes a yarn quality. Indeed, different textile manufacturers often express different views of yarn quality depending on the particular end product produced and the type of downstream processing used.

In general, the spinner may define yarn quality as an index of appearance, strength, uniformity, and level of imperfections. However, the spinner is much more concerned about how the yarn user views yarn quality.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. This can be achieved through integration of yarn quality into the overall specification of the end product. This requires establishing appropriate values of fiber attributes and optimum machine settings. In an ideal Fiber-to-Yarn Engineering (FYE) program, the translation of yarn quality into an acceptable end product performance is based on a well-defined design approach in which all phases of FYE are integrated to produce a yarn that is consistent and reflective of the end user requirements. This calls for an in-depth knowledge, not only of the general yarn  haracteristics, but also of the structural features of yarn.

  • Basic Structural Features of Spun Yarn

Before proceeding with the discussion on yarn characteristics, it will be important to discuss the basic structural features of spun yarn. Understanding these features provides an insight into the interpretation of yarn behaviour during processing or in the end product. The basic structural features of spun yarn are: yarn density, bulk integrity, and surface profile. These features are discussed below.

In a yarn structure, fibers represent the main component. The other component is air pockets created by the technology forming the structure. Accordingly, the yarn bulk density should be determined by the packing fraction, 0, as defined by the following equation:



The packing fraction is an indication of the air spaces enclosed by the fibers. For example, a packing fraction of 0.5 indicates that there is as much space taken by air as by fiber. Most spun yarns have packing fraction well above 0.5.

The importance of packing fraction lies in its powerful effects on many yarn and fabric properties. It is indeed one of the major design parameters
of textile fabrics. For a given fiber material, a yarn of very high packing fraction is likely to be stiff and probably weak. On the other hand, a yarn of very low packing fraction is likely to lack the bulk and surface integrity required to hold the yarn structure together during processing. In relation to fabric performance, yarn density plays a major role in determining many of the performance characteristics of fabric. One of the major fabric characteristics influenced by yarn density is fabric comfort. In general, fabric comfort is viewed in terms of two main aspects [El Mogahzy, 1998]: neurophysiological and thermo-physiological comfort. The neuro-physiological aspect deals with the fabric/skin physical interaction, and the thermo-physiological aspect deals with moisture and heat transfer through fabric. A high packing fraction will likely produce a highly compacted yarn that is likely to produce a stiff fabric and result in a greater true contact between the fabric and the human skin. These two features typically result in neuro-physiological discomfort. The thermo-physiological effect can be explained on the ground that air is the best heat insulator of all materials. On average, the thermal conductivity of air is more than eight times less than that of fibers (thermal conductivity of air = 6×10-5 cal.sec -1.cm -1. deg -1 C). The air pockets in the yarn assists in creating an entrapped or still air in the fabric and this can greatly enhance the thermal insulation of the human body against changing environmental conditions. Yarn density also influences other characteristics such as dimensional stability, strength, extensibility, flexibility, fabric cover, air permeability, and absorption characteristics.

Staple fiber yarns and textured yarns normally have lower density than continuous filament yarns made from the same fiber material.  Different spinning techniques produce different degrees of yarn density as a result of the different patterns of fiber compactness imposed by yarn twisting and spinning tension. For instance, a ring-spun yarn will typically exhibit higher degree of compactness than a comparable rotor-spun yarn due to the true twist the high tension used in ring spinning. The extent of fiber compactness can also be altered within the same spinning system. For instance, a higher rotor speed in open-end spinning is likely to produce higher fiber compactness in the yarn due to the higher centrifugal force applied on the fibers inside the rotor.

In theory, yarn density has approximately linear relationship with the product (twist.tex1/4) of spun yarn (Neckar, 1998). Fiber properties that influence this product will also influence fiber compactness or yarn density. These include: fiber diameter, cross-sectional shape, fiber length, fiber resiliency, and fiber density. For a given yarn count, and a given twist level, fine and long fibers will normally result in higher yarn density than coarse and short fibers.

  • Yarn Bulk Integrity

Yarn bulk integrity is determined by the fiber arrangement in the yarn structure. Fiber arrangement is expected to have significant effects on many yarn and fabric characteristics including yarn liveliness, fabric dimensional stability, yarn appearance, yarn strength, and fabric cover. The bulk integrity of a spun yarn largely reflects the impact of the spinning process on yarn structure. In general, different spinning techniques provide different forms of bulk integrity through providing different fiber arrangements. Obviously, the simplest fiber arrangement can be found in a continuous filament yarn where fibers (or continuous filaments) are typically arranged in parallel and straight form. As shown in Figure 1 a slight deviation from this arrangement can be caused by slightly twisting the filaments or through deliberate distortion in the filament orientation as in the texturizing process.


Fig.1 :- fiber arrangement in continues filament yarn

In staple fiber yarns, fiber arrangement is quite different from the simple arrangement discussed above. The discrete nature of staple fibers makes it impossible to fully control the fiber flow in such a way that can produce a well-defined fiber arrangement. For this reason, a spun yarn typically exhibits some irregularities along the yarn axis. In addition, no spun yarn can be free of fiber ends protruding from its surface as shown in Figure 2. Different spinning systems produce different forms of bulk integrity or fiber arrangements. The general features of fiber arrangement produced by four different spinning systems are shown in Figure 3 shows. In chapter 9, we will discuss how these  pinning techniques produce these structural arrangements.


Fig.2;- Fiber arrangement in staple yarn


Fig 3:- different fiber arrangement of different spinning technique

  • Yarn Surface Profile

The surface profile of a spun yarn may be described by three basic parameters: the overall surface appearance of yarn, surface integrity, and surface irregularities. The importance of yarn surface profile lies in the fact that a yarn is initially judged by its surface appearance. As the yarn goes through the weaving or the knitting process, surface integrity (abrasion resistance and hairiness) becomes the most critical factor determining yarn performance. As the yarn is finally woven or knitted into a fabric, surface irregularities (thick and thin places, and yarn neps) are typically the most noticeable defects in the fabric.

As expected, yarn density (or fiber compactness), and bulk integrity (or fiber arrangement) will greatly influence yarn surface profile.Accordingly, different spinning techniques will produce yarns of different surface profiles. Within a given spinning system, the main factors influencing yarn surface profile are:

  • The drafting mechanism (roller drafting or aerodynamic drafting)
  • The consolidation mechanism (twisting or wrapping)
  • The surface roughness of the spinning component (e.g. the traveler/ring contact in ring-spinning, the navel surface in rotor-spinning, and the condensation surface n compact spinning)

Material-related factors that can influence yarn surface profile include:

  • Short fiber content
  • Fiber neps
  • Fiber rigidity (flexural and torsion rigidities)
  • Fiber contaminants

In general, high levels of short fibers can result in excessive surface hairiness particularly in ring-spun yarns. The fact that short fibers flow under minimum or no control in the textile process can result in many surface disturbances of yarns spun on any spinning system. Many of the random thick and thin places in the yarn can be attributed to short fibers. Fiber neps that are not removed by the textile process will be presented in the yarn either in the bulk or on the surface. In both cases, surface disturbances will appear as short thick places or yarn neps. Fibers of high bending or torsion rigidity will not conform to the manipulation process exerted during textile processing. These fibers are likely to act in an unpredictable fashion leading to many surface disturbances (hairiness or irregular fiber wrappers). Many of the long-fiber hairiness can be attributed to high rigidity. On the other hand, fibers of extremely low rigidity may tend to entangle and form neps. Extraneous materials typically exhibit different shapes, colors, and sizes from fibers. The chance of these contaminants to appear on the yarn surface is much greater than to be incorporated in the yarn bulk. In either case, these contaminants, if not removed in the early stage of processing, can alter the yarn surface profile substantially.

  • Yarn Twist

Twisting is the primary binding mechanism of spun yarns. In general, twist is defined as a measure of spiral turns given to a yarn in order to hold the constituent fibers together. In practice, yarn twist is described using three main parameters: (a) twist direction, (b) twist level (turns/unit length), and (c) twist factor.

Twist Direction

Twist may be performed in the following two directions:

S-Direction: A single yarn has “S” twist if, when it is held in the vertical position, the fibers inclined to the axis of the yarn conform in direction of slope to the central portion of the letter S.

Z-Direction: A single yarn has “Z” twist if, when it is held in the vertical position, the fibers inclined to the axis of the yarn conform in direction of slope to the central portion of the letter Z.


fig.:-6 twist direction and twist level in idealised twist geometry

Twist Level

The amount of twist in the yarn is commonly expressed by the number of turns per unit length. In order to understand the meaning of twist and its relation to other yarn parameters, we will use the classical idealized helical geometry of a circular yarn (Hearle et al, 1969) shown in Figure 7.6. In this geometry, the yarn is assumed to be built-up of a series of superimposed concentric layers of different radii in each of which the fibers follow a uniform helical path so that its distance from the center remains constant. Based on this model, the length of one turn of twist, h, is given by:



Where TPC is turns per cm, and TPI is turns per inch.
In practice, equation 7.11 is commonly used to determine the twist multiplier of yarn for a given yarn count and a given twist level. It simply indicates that the twist multiplier is an expression of the twist level adjusted for yarn count. The Importance of Yarn Twist In practice, the importance of twist direction is realized when two single yarns are twisted to form a ply yarn. Ply twist may be Z on Z, or S on Z depending on appearance and strength requirements of the ply yarn. Recall that in determining the yarn count of a plied yarn, we had to account for the possible contraction or increase in length resulting from twisting. Normally, the Z on Z twist will result in a contraction of the plied yarn, while the S on Z twist will result in an increase in length. This amount of contraction or expansion will depend on the amount of twist inserted. When the yarn is woven or knitted into a fabric, the direction of twist influences the appearance of fabric. When a cloth is woven with the warp threads in alternate bands of S and Z twist, a subdued stripe effect is observed in the finished cloth due to the difference in the way the incident light is reflected from the two sets of yarns. In twill fabric, the direction of twist in the yarn largely determines the predominance of twill effect. For right-handed twill, the best contrasting effect will be obtained when a yarn with Z twist is used; on the other hand, a left-handed twist will produce a fabric having a flat appearance. In some cases, yarns with opposite twist directions are used to produce special surface texture effects in crepe fabrics.Twist direction will also have a great influence on fabric stability, which may be described by the amount of skew or “torque” in the fabric. This problem often exists in cotton single jersey knit where knitted wales and courses are angularly displaced from the ideal perpendicular angle. One of the solutions to solve this problem is to coordinate the direction of twist with the direction of machine rotation. With other factors being similar, yarn of Z twist is found to give less skew with machines rotating counter clockwise. Fabrics coming off the needles of a counter clockwise rotating machine have courses with left-hand skew, and yarns with Z twist yield right-hand wale skew. Thus, the two effects offset each other to yield less net skew. Clockwise rotating machines yield less skew with S twist. The amount of twist inserted in the yarn can influence many yarn characteristics. As will be shown in chapter 9, twisting is the primary mechanism to bind fibers in both ring and open-end spinning. Twisting is a unique binding mechanism that many engineers outside the textile field are not familiar with. It is, perhaps, the only binding mechanism that allows the structure to retain a great deal of its flexibility (as compared to glue or adhesive chemicals which result in more stiff structures). The relationship between yarn strength and twist level is well recognized among textile technologists and engineers. This relationship is generally illustrated in Figure 7. Initially, as the twist level (number of turns per unit length) increases, yarn strength will also increase. This effect holds only up to a certain point beyond which further increase in twist causes the yarn to become weaker. Thus, one should expect a point of twist at which yarn strength is at its maximum value. This point is known as the “optimum twist”.


figure 7 Effect of twist on spun yarn strength

Many investigators made various attempts to explain the strength-twist relationship (e.g. Hearle et al, 1969, and Lord, 1981). In practical terms, the strength-twist relationship may be explained on the ground that at zero twist, fibers are more or less oriented along the yarn axis but without any binding forces (except their interfacial contact). As twist slightly increases, the contact between fibers will increase due to the increase in traverse pressure, and the force required to stretch the yarn must first overcome the inter-fiber friction. Further increase in twist will result in further binding between fibers and an increase in the number of cross-linking points between fibers. This provides an opportunity for many fibers to be held at some points along their axis by other fibers. When this happens, the fiber strength begins to play a role in resisting the force required to stretch or rupture the yarn. Eventually, fiber strength will play a greater role than interfiber friction in tensile resistance. However, the discrete nature of fibers will always necessitate inter-fiber cohesion. The trend of increasing strength with twist will continue until some points where the fibers become so inclined away from the yarn axis that the contribution of fiber strength will decrease. This will result in a reduction of yarn strength with the increase in twist. In light of the above interpretation, one can see that there are two effects governing the strength-twist relationship. The first effect is an increase in yarn strength with twist resulting from the increase in the cohesion of fibers as the twist is increased. The second effect is a decrease in yarn strength with twist resulting from a decrease in the effective contribution to the axial loading of the yarn due to fiber obliquity. Thus, the curve shown in Figure 7.7 may be divided into two sections (Figure 8):

(i) a low twist region in which the effect of fiber cohesion outweighs that of obliquity, giving rise to an increase in strength, and

(ii) a high twist region in which further increase in cohesion no longer produces an increase in strength because of the overwhelming effect of fiber obliquity.


figure 8:- interpretation of strength-twist relationship

The twist level used can influence a number of fabric characteristics. These include: fabric hand, and skew. High or low levels of twist may be required depending on the type of fabric produced and its desirable characteristics. Highly twisted yarns are “lively” and tend to untwist (or snarl). Consequently, fabrics made from these yarns will possess a lively handle. This effect is utilized in producing crepe yarns (TM = 5.5- 9.0), which are used to produce crepe surface cloth. When soft fabrics are desirable (e.g. knit shirts), a low level of twist is required. Low twist level is also required to minimize fabric skew. In general, the higher the level of twist in the yarn the greater the tendency for the knit fabric to skew or torque.

  • Yarn Diameter

The use of linear density to express the yarn fineness provides a convenient and a practical approach for characterizing this important characteristic. All machines in the fiber-to-yarn conversion system are set on the basis of the linear density of fiber strands. In certain applications, however, yarn fineness expressed in diameter or thickness provides more useful information. For example, determining the structural features of a fabric (e.g. cover factor, yarn crimp, etc.) requires a prior knowledge of yarn diameter. It is important, therefore, to measure yarn diameter or to provide an estimate of its value. In this section, we discuss methods for estimating yarn diameter.Theoretically, equation 7.8, introduced earlier, provides a general expression of yarn radius as a function of the linear density and the volumetric density of the yarn. For direct count system (say, tex), this general relationship will be as follows:


For indirect systems (say, cotton count), the general expression of yarn diameter is as follows:


The above expressions indicate that the value of yarn diameter mainly depends on the linear density or yarn count, tex or Ne, and the volumetric density of yarn, p. As indicated earlier, volumetric density describes the degree of compactness of fibers in the yarn structure. This means that yarn twist will have a significant effect on yarn diameter.

Yarn Diameter Formula: In practice, yarn diameter is typically estimated using empirical formula. One of the most commonly used expressions for estimating yarn diameter is that developed by Peirce in 1937 (see Table 7.4). In this expression, yarn density was assumed to be 1.1 g/cm3. In a recent study, El Mogahzy et al (1993) developed empirical expressions for estimating the diameters of ring-spun, rotor-spun, and MJS airjet spun yarns. These expressions (also given in Table 7.3) were developed based on extensive microscopical testing of actual yarn thickness of the three yarn types using a wide range of yarn count, and twist levels. The formulae shown in Table 7.3 indicate that yarns made from different spinning systems and of equal nominal count will exhibit different values of yarn diameter. This is a result of the difference in fiber arrangement and fiber compactness of different yarn types. For example, a ring-spun yarn and a rotor-spun yarn of cotton count 20’s will have estimated diameters of 0.253 mm, and 0.275 mm, respectively. The higher value of rotor-spun yarn diameter indicates that it is bulkier than the ring-spun yarn.


We should point out that the formula for ring-spun yarn developed by El Mogahzy et al (1993) tend to produce a value of yarn diameter that is slightly higher than that estimated by Peirce equation. As shown in Figure 7.9, the difference between the two estimates decreases as the yarn becomes finer. The main reason for the difference was due to discrepancy in the value of yarn density, particularly in the coarse to medium range of yarn count. Using a combination of capacitive and optical measures of different yarns, we found that the density of cotton ring-spun yarns can range from 0.85 to 1.2 g/cm3 depending on the spinning system, fiber characteristics, and structural parameters (count and twist).


The Importance of Yarn Diameter :- As indicated above, yarn diameter is used to estimate fabric structural parameters such as width, and cover factor. Since thousands of ends or wales are presented side-by-side in the woven or the knit fabrics, a slight change in yarn diameter can result in a substantial change in the overall cover factor of fabric. The effect of yarn diameter on the geometrical features of fabric structure can be realized through examination of the equations developed by Peirce to determine the cover factor of woven fabric (Peirce, 1937), or the equations developed by Munden (1963, 1967) to determine the tightness factor of plain weft knitted structures. In the context of fiber-to-yarn engineering, yarn diameter is certainly a major design criterion. Factors affecting yarn diameter are essentially those that affect yarn density or fiber compactness. As we indicated earlier, fiber properties that are expected to influence fiber compactness include: fiber fineness, fiber stiffness, fiber length, and fiber crimp. In general, coarse and stiff fibers will result in bulkier or thicker yarn than fine and flexible fibers (Stout, 1958). In other words, as the fiber becomes coarser (higher denier, or millitex), yarn density becomes smaller, leading to an increase in yarn diameter, although the count of yarn remains unchanged. Zurek (1961), one of the leading scientists in yarn structure, explains the above phenomenon on the ground that coarser or more rigid fibers have higher resistance to bending, while twisted into yarns, than finer or more flexible fibers; hence, the radius of their curvature is longer. Only movement of the fiber away from yarn axis can cause the increase of radius. On the same ground, fiber length also affects yarn density and consequently yarn diameter. For a given yarn count and at the same twist factor, the larger the fiber length, the higher the yarn density, and the smaller the yarn diameter. In theory, fiber compactness may be characterized by two main categories of fiber arrangement in the yarn cross-section (Hearle et al, 1969):

(i) the open-packed structure, andimage

(ii) the closed packed
structure. These are illustrated in Figure 7.10. In the opened-packed structure, fibers lie in layers between successive concentric circles. The first layer is a single core fiber around which six fibers are arranged so that all are touching; the third layer has twelve fibers arranged so that the fibers first touch the circle that circumscribes the second layer; additional layers are added between the successive circumscribing circles. In the closed-packed structure, all fibers touch each others which give rise to a hexagonal array of fibers in the yarn cross section. In practice, fiber packing may deviate largely from these idealized forms. This deviation may be attributed to a number of factors including: non-circularity of fibers, dimensional variability, the relaxation and coherence of fibers in the yarn structure, and the effect of twist. The last factor is explained on the ground that twist causes the development of tangential and radial forces, which result in fiber migration and binding of fibers together.

  • Yarn Strength :-

Yarn strength is considered as one of the main criteria characterizing yarn quality. Indeed, no other yarn characteristic has received more investigative attention than yarn strength. Most of the studies dealing with yarn strength focused on developing models characterizing yarn strength as a function of structural parameters and fiber attributes. Many of these models revealed a great deal of information about the complex nature of yarn strength. In fact, the interpretation of the strength-twist relationship discussed earlier stems from existing models describing the effect of twist on yarn strength. In recent years, interest in modeling yarn strength with respect to relevant fiber attributes has increased as a result of the revolutionary development of fiber testing and information technology, and the introduction of new spinning technologies. Despite the numerous studies of yarn strength, no universal model exists today that can fully explore or predict the mechanical behavior of staple-fiber yarn under tensile loading, from the progressive fiber assistance to the rupture mode. This is primarily due to the overwhelming stochastic nature of spun yarns making it very difficult to achieve a complete resolution of the different factors influencing yarn strength. Our interest in modeling yarn strength stems from the fact that fiber-to-yarn modeling is a basic phase of fiber-to-yarn engineering. Empirical models for predicting yarn strength and other yarn characteristics can be developed within the boundaries imposed by a given textile process. These models can be verified not only through a sound database, but also on physical basis.

Practical Parameters Describing Yarn Strength: – In chapter 6, we discussed the concept of load-elongation (or stress-strain) curve and the different parameters that can be derived from it. This concept basically holds for any material subject to tensile loading including textile yarns. Accordingly, the parameters associated with the curve (e.g. breaking stress, toughness, modulus, etc) can be used for characterizing yarn strength. The shape of the curve, however, varies widely depending on many factors including: yarn type (ring, rotor, or airjet), twist level, and yarn texture.
In practice, the strength of staple fiber yarn is commonly described using the following parameters:
· Skein strength
· Count-strength product (CSP)
· Single-end strength
· Strength irregularity (C.V strength%)

Yarn Skein Strength :- The skein strength is typically measured by winding a 120-yard skein on a wrap reel. The yarn is then removed from the reel and tested in the form of several revolutions of parallel threads using a pendulum tester at a constant rate of traverse. When the specimen is subjected to tensile loading, all threads will resist the loading until a break occurs in one of the threads (the weakest point). The remaining unbroken threads will then support the skein until a second thread breaks. This process continues through a succession of thread breaks until a total failure occurs. It is believed, therefore, that the skein strength test provides a combined measure of the strength of a composite specimen of yarns and the inter-yarn friction. The parameter obtained from this test is called the skein or lea strength expressed in pounds. The skein strength test is commonly accompanied by a yarn count test in which the same test specimen is weighted to determine the cotton count. The count-strength product known as the CSP provides a strength measure commonly known as the skein-break factor (Ne.lb). In practice, this measure is used more commonly than the absolute value of skein strength. Typical values of skein break factor for different yarns are given in Table 7.4. These values are based on yarn data corresponding to cotton U.S. crops 1990 and 1991.The wide range of CSP values is, therefore, a result of the wide range of values of fiber characteristics used in the make of the yarns.

Single-End Strength : The single-end strength represents a more fundamental parameter than the skein strength. Using modern tensile testers (e.g. Uster TensoRapid® ), strength parameters can be obtained at a constant rate of extension of 5 m/min and a gauge length of 50 cm. These parameters include: breaking load, breaking elongation, load-elongation (or stress-strain) curve, yarn tenacity, yield stress and strain, specific work of rupture, and tensile modulus. Typical values of strength parameters of different types of cotton yarns and at different values of yarn count are listed in Tables 7.5 through 7.9. These tables are modified from the Uster statistics®, 1997. Another tensile tester, also developed by Uster, is called the TensoJet®. This tester operates at a very high rate of extension (400 m/min). Using this tester, up to 30,000 tests per hour can be performed. This tester allows measuring strength variability from a large number of breaks. Strength Irregularity (C~V~trength %) Similar to count variability, strength irregularity is commonly defined by the coefficient of variation of yarn strength:


The importance of strength irregularity lies in the fact that during processing (warping, dyeing, weaving or knitting), the incident of breakage often occurs at the weakest points of the yarn. Knowledge of the extent of variability in yarn strength will permit estimation of the strength of the weakest points. For example, suppose that the mean strength of a ring-spun yarn of count 20’s is 18 cN/tex, and the C.V% of yarn strength is 8%. From the above equation, the standard deviation of strength is 6 = 8×18/100 = 1.44 cN/tex. Typically, yarn strength as a variable follows a normal distribution. One of the basic features of the normal distribution is that the total relative frequency (or the area under the curve) between μ ± 36 is about 99.74%. As shown in Figure 7.11, it follows that this yarn will have weak points of strength values as low as 13.7 cN/tex, which is only 76% of the mean strength.




The Importance of Yarn Strength :

The importance of yarn strength can be realized in all stages of processing from spinning to finished fabric manufacturing. In any spinning technique, yarn strength represents a crucial parameter, which determines the performance of spinning. For instance, an ends down in ring spinning is often a result of the failure of the yarn to withstand a high peak of spinning tension. This failure results from a weak portion of the yarn. The strength-twist relationship is considered to be a characteristic curve of the spinning performance that must be established to produce a high strength yarn. As indicated earlier, fiber properties such as strength, length, fineness, and friction play a vital role in determining this relationship. During yarn preparation for weaving, the yarn is subject to continuous tension as a result of the repeated winding and unwinding necessary for weaving preparation. This tension should be within the elastic boundaries of the yarn to avoid permanent deformation. During dyeing or sizing, the yarn is subjected to chemical treatments that can alter its mechanical behavior. For example, the sizing process results in an inevitable reduction in yarn elongation and yarn flexibility. It is important, therefore, to examine the modulus and the elongation profiles of yarn during weaving preparation. During the weaving process, thousands of yarns are simultaneously subject to continuous cyclic loading, which is a basic necessity for the interlacing actions required to make cloth. Weaving peak tension may reach levels exceeding 35% of the average breaking force of the yarn. Both tension variation, and yarn strength variation are expected. A single yarn may break when it exhibits a level of strength that is lower than the weaving tension at some points of the yarn. When a maximum tension coincides with a minimum strength point of the yarn, failure of yarn to withstand the tension will occur. This failure may result in an end breakage and a complete stop of the weaving process. During knitting, the yarn is subject to tension, which may reach levels of more than 30% of the average breaking force of the yarn. Again, both knitting tension and yarn strength exhibit variability. Accordingly, the failure of yarn to withstand knitting tension may occur in the same fashion described for weaving. A yarn break during knitting will have an adverse effect not only on the machine efficiency but also on the fabric quality. The stress-strain behavior of yarn is a critical factor in determining the mechanical behavior of fabric under different modes of deformation (e.g. tension, bending, and shear). In general, a strong yarn will make a strong fabric, and a stiff yarn will result in a fabric of poor comfort characteristics. An optimum combination of strength and flexibility can be achieved through many options including a proper level of twist, and a judicious choice of fiber attributes. Yarn Evenness and Imperfections The evenness, or regularity of a fiber strand (e.g. sliver, roving, or yarn) is a measure of the extent of uniformity in the strand thickness along its length. Imperfections represent abnormal incidents exceeding in their forms the expected variation in the thickness of a fiber strand. As shown in Figure 7.12, these include thin places, thick places, and neps. The reference method of evenness and imperfection analysis is obviously the microscopic method. However, the large sample of yarn required to obtain reliable microscopic information makes this method time-consuming, particularly in a practical environment. Alternatively, we may take a long fiber strand, cut it into portions of equal length, and weigh each portion. The thickness variation can then be determined from the variation in the weight per unit length as shown in Figure 7.13. This method is called the “cut and weight” method and it is used as the basis for the more advanced capacitive method commonly used by most textile mills.



  • Methods of Evenness Testing :

There are many methods that can be used for testing the evenness of a fiber strand. These include (Slater, 1986, Walker, 1950,
Townsend et al, 1951):
· The capacitive method
· The optical method
· The pneumatic method
· The acoustic method, and
· The mechanical method
The capacitive method utilizes a capacitor (or an electrode). When a non-conductive material (such as a fiber strand) enters the field of the electrode, a capacitance change occurs. The variability in capacitance is used to indicate the variability in the mass of the fiber strand. The main element in the capacitive method is the detecting electrode. This consists of a pair of metal plates, acting as an air-spaced capacitor. The capacitive method is utilized in the popular Uster® evenness tester. A critical assumption underlying the use of the capacitive method is that the relationship between mass and capacitance change is linear. If the fiber/air ratio is increased beyond a certain limit, the electrode becomes overloaded and this relationship becomes non-linear. In this regard, a fiber/air ratio of 40% or less is recommended. Other limiting features of the capacitive method include the requirement of a rounded fiber strand, the necessity of keeping the strand well away from both plates or be in constant contact with one of them, and the high sensitivity of the method to relative humidity. In the optical method, a light source is directed onto a fiber strand, and the mass per unit length of the strand is detected by either optical extinction or optical reflection. In case of the optical extinction, the shadow cast is taken to be proportional in area to the mass of the fiber strand in the test zone. In case of optical reflection, the fiber strand is directly illuminated; when a normal strand is in the test zone, no reflection is detected; abnormalities such as fluffs, loops and protruding fibers reflect light, which can be measured electrically. Optical principles are utilized in the Uster® tester, and the Zewigle EIB system. The primary limiting factor of the optical method in measuring the evenness of a fiber strand is its sensitivity to the geometrical profile of the strand. Irregular cross sections are likely to be presented to the light source in preferential direction of alignment.In the pneumatic method, the fiber strand is passed through an orifice or a narrow tube, into which an air stream is being forced. The evenness of the fiber strand is then measured by the variation in the rate of airflow resulting from mass variation. Limiting factors of this technique include the non-linear relationship between the airflow rate and the mass of fiber trand, and the high sensitivity to atmospheric conditions (humidity and temperature). This method has been used in association with autolevelling systems (evenness control system) of fiber strands during carding.
In the acoustic method, the fiber strand moves through a sound field between a generator and a pick-up device. The time taken for sound waves to move across the gap is measured electronically. The change in this transit time is believed to correspond to the change in the cross-sectional dimensions of the fiber strand. This method has the advantage of being insensitive to moisture change. Some instrument developers have used this principle for measuring sliver uniformity during carding and drawing.In the mechanical method, the irregularity of a fiber strand is detected using a mechanical feeler, which senses the mass variation of a fiber strand as it passes through a pair of drafting roller. It is normally utilized in conjunction with autoleveling systems.Another important irregularity parameter is the socalled “limiting irregularity”. This parameter theoretically provides an irregularity measure of a fiber strand in which fibers are arranged in a completely random fashion. In practical terms, it implies irregularity under best machine conditions. The limiting irregularity, C.V%limit , is simply defined by:


Equation 7.14 indicates that as the number of fibers per yarn, or strand, cross-section increases, the limiting irregularity decreases. This may be explained on the ground that the increase in the number of fibers creates a compensating or a doubling effect that reduces the irregularity in yarn cross-section.

In practice, the concept of limiting irregularity can be used to estimate the partial effect of process-added variability on the overall irregularity. In this regard, the Uster evenness tester can provide the so-called “irregularity index” defined by the following equation:


The concept underlying the utilization of an irregularity index is that every process will inevitably add variability to the fiber strand. This added variability is a result of the limited capability of existing processes to maintain a perfectly random distribution of fibers in the strand cross-section, and along the strand length. In addition, mechanical defects such as improper fiber control and draft roller eccentricity adds a periodic component to the variability in the fiber strand. The irregularity index, I, compares the limiting variability to the total measured variability of the fiber strand. In the ideal situation where no process-added irregularity exists, both the measured and the limiting irregularities will be theoretically equal; in this case, the irregularity index will be equivalent to unity. In actual processing, however, the measured irregularity will exceed the limiting irregularity, and a value of I greater than one will be expected.

Yarn Imperfections :

Staple-fiber yarns usually exhibit 3 main types of imperfections: thin places, thick places, and neps. In the USTEO evenness tester, thin and thick places refer to imperfections that are within the measuring sensitivity range (f 100% with respect to the mean value of yarn cross-sectional size). Figure 7.15 shows a relative frequency diagram showing the yarn sensitivity range. Typically, thin and thick places can be of up to one-inch length. Neps are classified as the yarn imperfections, which may exceed the f 100% limit. They are typically of 3 to 10 mm length. Typical values of Uster imperfections are listed in Tables 7.12 through 7.14. Thick places exceeding the 100% limit are determined using the so-called Classimat method.




  • Yarn Surface Integrity

The critical importance of yarn surface integrity stems from the fact that despite the advanced spinning technology that we witness today, the yarn as spun can not be woven or knitted without some form of treatment to enhance its surface integrity. Millions of dollars are spent every day to apply chemicals to the yarn surface so that it can flow smoothly through the weaving process. These chemicals provide a temporary function and are later disposed or partially recycled. The cost of these chemicals and their byproduct environmental effects clearly justify extensive research in the area of yarn surface to seek ways to improve the inherent surface structure of spun yarns. In practice, yarn surface integrity is typically characterized by two main parameters: abrasion resistance and hairiness. Abrasion is generally defined as the wearing away of any part of the material by rubbing against another surface. Accordingly, the measuring principle of abrasion resistance is normally based on placing a number of parallel threads under a predetermined initial tension, and subjecting these threads to an abrasive solid surface moving (or rotating) at a constant speed. This will exert a constant abrasive force, which continues to act on the yarn surface until the yarn is finally worn out. The abrasion resistance is commonly expressed by the number of abrasive cycles required to break the yarn. Testing of abrasion resistance of staple fiber yarns is often associated with a lack of repeatability of test results. This is largely attributed to the complex variable nature of yarn surface and to the presence of fiber loops and hairs protruding from the surface. Yarn hairiness may generally be defined as the extent of hairs protruding from the yarn body. Two methods are currently used for measuring yarn hairiness:

(i) the hair count method, and

(ii) the hair length method.

In the first method, fibers protruding from the yarn surface are counted by projecting the fiber shadow onto phototransistors. This method is utilized in the Zweigle® hairiness measuring device, which provides values of the number of hairs per meter; hairs extending over lengths from 1 mm to 25 mm can be counted. Obviously, the maximum number of hairs will be detected at the closest distance to the yarn body (1 mm).In the second method, the measuring field is formed by homogenous rays of parallel light; if a yarn lies in this field, only those rays of light scattered by the fibers protruding from the yarn body are detected. This method is utilized in the USTE~® evenness tester. Hairiness in this case is defined by the index H, which is defined as the total length (in cm) of all protruding hairs with reference to a sensoring length of 1 cm. For example, a hairiness value H = 5 will correspond to a total protruding fiber length of 5 cm per 1 cm sensing length. Typical values of Uster hairiness are shown in Tables 7.15 and 7.16.


The Burn Test to Identify Textile Fibers

The burn test is a simple, somewhat subjective test based on the knowledge of how particular fibers burn. Be prepared to note the following when testing your fibers:
• Do the fibers melt and/or burn?
• Do the fibers shrink from the flame?
• What type of odor do the fumes have?
• What is the characteristic(s) of any smoke?
• What does the residue of the burned fibers look like?

The burn test is normally made on a small sample of yarns or thread which are twisted together. Since the fiber content of yarns used in one direction of a fabric are not always made up of the same fibers used in the other direction, warp and filling yarns should be burned separately to determine the entire fiber content of the fabric. This test is very helpful in determining whether a fabric is made from synthetic or natural fibers, but it is not foolproof and the characteristics observed during the burning test can be affected by several things. If the fabric /yarn contains blends of fibers, identification of individual fibers can be difficult. Two or three different kinds of fibers burned together in one yarn may also be difficult to distinguish. The odor and burning characteristics exhibited may be that of several fibers, thus making your results difficult to analyze. Finishes used on the fabric can also change the observed characteristics.

  • Pull a small sample of at least six to eight yarns from your fabric about 4 inches long, and twist them together into a bundle about 1/8 inch in diameter. You can also use a small snippet of the fabric if you only need to determine whether it is a synthetic or natural fiber fabric and you are not seeking to determine the specific fiber(s) that make up the fabric.
  • Hold one end of the bundle with tweezers over a sink or a sheet of aluminum foil (about 10 to 12 inches square) to protect your working area. If the sample ignites it can be dropped into the sink or on the foil without damage. Use either a candle or a match (automatic lighters work well) as your flame.

Potential Test Results

Natural, Organic & Manmade Fibers

In general, if the ash is soft and the odor is of burning hair or paper, the fabric is a natural fiber. Cellulosic fibers (cotton, linen and rayon) burn rapidly with a yellow flame. When the flame is removed, there is an afterglow, then soft gray ash.

Cotton: Ignites on contact with flames; burns quickly and leaves a yellowish to orange afterglow when put out. Does not melt. It has the odor of burning paper, leaves, or wood. The residue is a fine, feathery, gray ash.
• Hemp: Same as cotton
• Linen: Same as cotton
• Ramie : Same as cotton
• Rayon : Same as cotton, but burns slowly without flame with slight melting; leaves soft black ash.
• Silk: Burns slowly, but does not melt. It shrinks from the flame. It has the odor of charred meat (some say like burned hair). The residue is a black, hollow irregular bead that can be easily to a gritty, grayish-black ash powder. It is self-extinguishing, i.e., it burns itself out.
Tencel : Same as Rayon
• Wool, and other Protein Fibers: Burns with an orange sputtery color, but does not melt. It shrinks from the flame. It has a strong odor of burning hair or feathers. The residue is a black, hollow irregular bead that can be easily crushed into a gritty black powder. It is self-extinguishing, i.e., it burns itself out.

Synthetic Fibers

Most synthetic fibers both burn and melt, and also tend to shrink away from the flame. Synthetics burn with an acrid, chemical or vinegar-like odor and leave a plastic bead.
Other identifying characteristics include:
• Acetate: Flames and burns quickly; has an odor similar to burning paper and hot vinegar. Its residue is a hard, dark, solid bead. If you suspect a fabric is acetate, double-check by placing a scrap of it in a small amount of fingernail polish remover-if you’re correct, the fabric will dissolve
• Acrylic: Flames and burns rapidly with hot, sputtering flame and a black smoke. Has an acrid, fishy odor. The residue is a hard irregularly-shaped black bead.
• Nylon: It will shrink from the flame and burn slowly. Has an odor likened to celery. Its residue is initially a hard, cream-colored bead that becomes darker gray.
• Olefin/Polyolefin: Has a chemical type odor. The residue id a hard, tancolored bead. The flames creates black smoke.
• Polyester: It will shrink from the flame and burn slowly giving off black smoke. Has a somewhat sweet chemical odor. The residue is initially a hard cream-colored bead that becomes darker tan.
Spandex: It burns and melts, but does not shrink from the flame. It has a chemical type odor. Its residue is a soft, sticky black ash.


Yarn Numbering System

Textiles are often sold on a weight basis and consequently it is natural to express the size of “thickness” of a yarn in terms of weight (or mass). There are two basic ways in which this may be done. These are: (a) by saying how much a given length of yarn weighs, or (b) by saying what length of yarn one would have in a given weight. Generally these are known as the direct and indirect systems of yarn numbering, respectively. In other words:

Direct yarn number =  Weight / unit Length
Indirect yarn number = Length / unit weight

It will be noted that one is the inverse of the other. In the first case, the number gets larger as the yarn or strand gets coarser. In the second case, the number gets smaller as the yarn or strand gets coarser.

Each system has its advantages and disadvantages and each has found areas in which, by custom, it is used. It so happens that because long, thin strands are usually involved, the length figures are usually large and the weight figures are small. Consequently, the yarn numbers would get impossibly large or impossibly small unless special units are used. The following paragraphs will explain a selection of the most important sets of units used. A summary is listed in Table 1


The technical name used to describe the yarn size in the direct system is linear density,* and this is always expressed in terms of weight/unit length. In commerce, the technical name is used less frequently than in the fiber industry or the scientific community. Often the name of the particular unit, such as denier or tex is used instead. Sometimes the term “yarn number” is used, but this is confusing unless the system is quoted.

With the usual range of linear densities found in yarns, one pound of yarn if stretched out straight could extend up to 20 miles in length. Clearly if one were to express the linear density in lb/yd, the numbers would be impossibly small and cumbersome to use. Since scientists tend to use the metric system [grams (g) and meters (m) for weight and length, respectively] one could consider g/m as a unit, but in this case, it turns out that the number is too large to be handled conveniently.

In practice there are two major subsections, which refer to yarn. In one case, the logically minded scientists have chosen a length unit of 1000 meters, whereas the technologists have chosen 9000 meters. The reason for this latter choice is obscure.

The scientific subsystem uses the unit “tex,” where 1 tex is the weight in g of 1000 meters (1 km) of yarn and the number gets bigger as the yarn gets fatter. Thus, a 50 tex yarn weighs 50 g for every kilometer of yarn. The normal metric prefixes of kilo, deci, etc., can also be applied to the unit tex. Hence 1 decitex is 1/10 tex and 1 kilotex = 1000 tex.
The fiber industry tends to use the unit “denier” where 1 denier is the weight in g of 9000 meters of yarn. Thus a 450 denier yarn weighs 450 g for every 9000 meters. A moment’s reflection will show that the two examples given refer to the same yarn size. Denier is very often used to describe the size of the fiber; hence, a 1½ denier filament weighs 1½ g per 9000 m of that filament. In passing it might be noted that if the 450 denier yarn is made up of 1½ denier filaments, there will be 450/1½ = 300 filaments making up that yarn.
As will be shown later, there are intermediate products, such as sliver, to which the direct system of measurement can be applied. A sliver is a rope-like material and a typical linear density (or “sliver weight”) is 50 grains/yard. (A grain is 1/7000 lb. and care should be taken when handwriting the units to distinguish clearly between grain and gram.)
In this bulletin, the symbol “n” will be used to denote linear density, and in every case, the appropriate units should be quoted.


It will be remembered that the indirect system is in terms of length per unit weight. Once again, there has to be special units, but there is a large variety of systems which are a legacy of the ancient crafts, and there is no discernible logic in the choice of units. Generally, all the subsystems in this category are referred to as yarn count or yarn number, and it is necessary to specify the subsystem if confusion is to be avoided. It is normal to specify the yarn count in hanks/lb where a hank contains a specified length of yarn.

Unfortunately, each of the subsystems specifies a different length.

In cotton processing technology (and those technologies which have evolved from that technology), the units developed in England during the industrial revolution are still used in the USA. In this case, a hank is specified as containing 840 yds* of yarn. Thus, if the count of a singles yarn is 20 hanks/lb. (usually written as 20s or 20/1), there will be 20 x 840 yards in a pound of yarn. The symbol used in this bulletin will be Ne where the subscript refers to “English” and distinguishes it from Nm, which refers to the metric count (meters/gram). In the case of long staple yarns, whose technology is derived from one of the processes for making yarn out of wool, a hank is often defined as 560 yds. of yarn, and in this case, the symbol NW will be used to describe count. There are many others, and a list of some specified hank lengths is given in Table 1.

With the indirect system, the number gets larger as the yarn gets finer. In the English cotton system, a 4s yarn is very coarse whereas 40s yarn is fine.


In normal practice, it is unnecessary to go through such a calculation each time a conversion is  required, and generally a conversion factor can be used (see Table 2). In the case of converting from one direct subsystem to another, one merely multiplies the known linear density by the conversion factor to get it into different counts, similarly, when converting from one indirect subsystem to another. When converting from indirect to direct, or vice versa, then the factor must be divided by the known quantity.


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Advanced Fibre Information System (AFIS)


Advanced Fibre Information System is based on the single fibre testing. There are two modules, one for testing the number of neps and the size of neps, while the other one is used for testing the length and the diameter. Both modules can be applied separately or together.

Among all physical properties of the cotton, fiber length varies the most within any one sample. There are two sources of variability;

1) Variability that comes from mixing cottons of various lengths

2) Variability that is biological in nature and exists within a sample of the same origin.

The same variety grown under different conditions, with lower or higher fertilizer doses, irrigation, or pest control, can produce various lengths. This is why fibre length is tested as an average of many fibres. Fibres also break during handling and processing thus, emphasizing the need for measurement of magnitude of the length variation. There are many different measurements of fibre length, including staple length, model length, mean length (aver-age length), 2.5% span length, effective length, upper quartile length, upper-half mean length, length uniformity index, length uniformity ratio, span length, short fibre contents and floating fibre length.

The AFIS test provides several length parameters deduced from individual fibre measurements. The main measurements include: the mean length, the length upper percentiles, the length CV%, and the Short Fibre Content (defined as the percentage of fibres less than 12.7 mm in length). Fibre length information is provided as a number or as weight-based data (by number/by weight). The length distribution by weight is determined by the weight-frequency of fibres in the different length categories, that is the proportion of the total weight of fibres in a given length category. The length distribution by number is given by the proportion of the total number of fibres in different length categories. The length parameters by weight and by number are computed from the two distributions accordingly. Once the AFIS machine determines the length distribution, the machine computes the length distribution by weight assuming that all fibres have the same fineness. Samples do not require any preparation and a result is obtained in 2-3 minutes. The results generally show a good correlation with other methods.

With the introduction of AFIS, it is possible to determine the average properties for a sample, and also the variation from the fibre to fibre. The information content in the AFIS is more. The spinning mill is dependent on the AFIS testing method, to achieve the optimum conditions with the available raw material and processing machinery. The AFIS-N module is dealt here and it is basically used for counting the number of neps and the size of neps. The testing time per sample is 3 minutes in AFIS-.N module.

This system is quick, purpose oriented and reproducible counting of neps in raw material and at all process stages of short staple spinning mill. It is thus possible, based on forecasts supervisory measures and early warning information to practically eliminate subsequent complaints with respect to finished product. The lab personnel are freed from the time consuming, delicate and unpopular, proceeding of nep counting. Personnel turnover and job rotation no more affects the results of the nep counting. The personnel responsible for quality can now at least deal with the unpopular neps in a more purpose-oriented manner than ever before.

AFIS -Working principle:-


A fibre sample of approximately 500 mg is inserted between the feed roller and the feed plate of the AFIS-N instrument Opening rollers open the fibre assembly and separate off the fibres, neps, trash and dust. The trash particles and dust are suctioned off to extraction. On their way through the transportation and acceleration channels, the fibres and neps pass through the optical sensor, which determines the number and size of the neps.

The corresponding impulses are converted into electrical signals, which are then transmitted to a microcomputer for evaluation purposes. According to these analyses, a distinction is made between the single fibres and the neps. The statistical data are calculated and printed out through a printer. The measuring process can be controlled through a PC-keyboard and a screen.

Uster AFIS PRO- application report

Various HVI models available in market in present date are:-


Optional Modules:

• Length and Maturity (L&M) Module to measure cotton fiber length and maturity, integrating results into the USTERÒ AFIS PRO 2.

• Trash (T) Module to measure the dust and trash content in cotton, integrating results into the USTERÒ AFIS PRO 2.

• USTERÒ AFIS AUTOJET (AJ) Module to measure up to 30 samples automatically, reducing idle operating time.

UPSUninterrupted Power Supply device to support the computer and monitor



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Uster Technologies
Image via Wikipedia

The testing of fibres was always of importance to the spinner. It has been known for a long time that the fibre characteristics have a decisive impact on the running behaviour of the production machines, as well as on the yarn quality and manufacturing costs. In spite of the fact that fibre characteristics are very important for yarn production, the sample size for testing  fibre characteristics is not big enough. This is due to the following

  • The labour and time involvement for the testing of a representative sample was too expensive. The results were often available  much too late to  take corrective action.
  • The results often depended on the operator and / or the  instrument, and could therefore not be considered objective
  • One failed in trying to rationally administer the flood of the raw material data, to evaluate such data and to introduce the necessary corrective measures.

Only recently technical achievements have made possible the development of automatic computer-controlled testing equipment. With their use, it is possible to quickly determine the more important fibre characteristics.


Recent developments in HVI technology are the result of requests made by textile manufacturers for additional and more precise fibre property  information. Worldwide competitive pressure on product price and product quality dictates close control of all resources used in the manufacturing process.

Historical Development of HVI:-

Conventionally measurement of the fibre properties was mainly carried out using manual method and it included the maximum chance of getting errors involved in it due to manual errors and was also a time consuming job. Thus there was a need for development of an instrument capable of measuring all properties in minimum time for better cotton classification.

PCCA (plans cotton cooperative association) played a key role in the development of High Volume Instrument (HVI) testing to determine the fibre properties of cotton which revolutionized the cotton and textile industries. As its name implies, HVI determines the fibre properties of a bale of cotton more quickly and more accurately than the previous method of evaluating some of those properties by hand classing. The HVI system provides more information about a bale of cotton than the subjective hand classing method.

In 1960, PCCA and Motion Control, Inc., an instrument manufacturer in Dallas, Texas, began pioneering the development of a system to eliminate the potential for human error that existed with hand classing and expand the number of fibre properties that could rapidly be determined for each bale of cotton. The goal was to be able to provide seven fibre quality characteristics for every bale produced by PCCA’s farmer-owners. Laboratory instruments were available for determining most of the fibre properties, but they required up to 15 minutes or longer to determine each of the properties. The PCCA theory was based on economics: the faster cotton could be classed, the faster it could be marketed; and, the more accurate measurements of quality could result in a more adequate supply of cotton with fibre properties to meet the specific needs of textile mills.


fig1 :- Present day USDA cotton classing system.image

By the mid-1960s, the United States Department of Agricultural (USDA) and the Cotton Producers Institute (now called Cotton, Incorporated) also became involved in the research required to bring this concept to the marketplace.

In 1968 three of the first five HVI lines were in operation in Lubbock, Texas. One line was at Texas Tech University’s International Textile Center and two at PCCA. These lines were the very earliest versions to have all seven-fibre properties combined into a single testing line and measure them in less than 20 seconds per test.

In 1980, USDA built a new classing office in Lamesa, Texas, (about 60 miles south of Lubbock) specifically designed only for instrument testing all of the cotton samples received at that office using the latest version of the HVI equipment. This was a daring step but was based on data collected and analysed and improvements made in the HVI system during the previous 20 years. Although met with scepticism in the initial years by many in the cotton and textile industries, the HVI system prevailed, and USDA continued to install the instrument testing lines in all government cotton classing offices. In 1991, USDA used the HVI system on all the cotton provided to the department for classing. Today, HVI class data is accepted throughout the world and is the foundation on which cotton is traded.


In total, there are five companies manufacturing rapid instrument testing machines in the world,

i. Uster technologies, Inc.,

ii. Premier Evolvics Pvt. Ltd.,

iii. Lintronics (China, Mainland)

iv. Changing Technologies (China, Mainland)

v. Statex Engineering (India).

High volume instrument (HVI) is the most common rapid instrument testing machine made by Uster Technologies, Inc. The only other company that has over 100 machines installed in the world, mostly in Asia, is Premier Evolvics Pvt. Ltd. based in India. It is estimated that close to 2,000 rapid instruments testing machines have already been stalled in the world, mostly from Uster Technologies, Inc. Not only do the machines from each company differ, but various models from each company also differ among themselves. The full fledge models of both the manufacturers are capable of measuring measure micronaire, length, length uniformity, strength, colour, trash, maturity, sugar content etc.


High volume instrument systems are based on the fibre bundle testing, i.e., many fibres are checked at the same time and their average values determined. Traditional testing using micronaire, pressley, stelometre, and fibro graph are designed to determine average value for a large number of fibres, the so called fibre bundle tests. In HVI, the bundle testing method is automated.


This is based on the categorising of cotton bales according to their fibre quality characteristics. It includes the measurement of the fibre characteristics with reference to each individual bale, separation of bales into classes and lying down of balanced bale mixes based on these classes. The reason for undertaking this work lies in the fact that there is sometimes a considerable variation in the fibre characteristics from one bale to another, even within the same delivery. This variation will result in the yarn quality variation if the bales are mixed in an uncontrolled manner.

The bale management software, normally embedded with an HVI, helps in selection of bales for a particular mix from the available stock. Once the data are received from HVI in the software, classification of bales in groups are done with user defined criteria.image

· Manual calculation errors and the tedious task of day to day manual planning of mix are avoided.

· The storage of large number of data enables for tracking long period records or results thereby helping in clear analysis.

· More cost effective mix can be made since cost factor is also included. It also helps in planning for further requirements or purchase.

· Additional details such as party name, weighment details, and rejection details can be printed along with the test results which will be useful for the mill personnel for better analysis.

· Separate range criteria shall be selected for basic samples , lot samples and mixing

· Flexible intervals in grouping of bales with reference to the selected category.

· Basic sample results and results checked after lot arrival shall be compared graphically or numerically for easy decision making of approval or rejection.

Ø Information

The instruments are calibrated to read in staple length. Length measurements obtained from the instrument are considerably more repeatable than the staple length determination by the classer.  In one experiment the instrument repeated the same staple length determination 44% of the time while the classer repeated this determination only 29% of the time.  Similarly, the instrument repeated to 1/32″ on 76% of the samples, while the classer agreed on 71% of the samples to within 1/31″.

The precision of the HVI length measurement has been improved over the last few years. If we take the same bale of cotton used in the earlier example and repeatedly measure length with  an HVI system, over two-thirds of measurements will be  in a range of only about 1/32 nd of an inch: 95% of the individual readings will be within 1/32nd of an inch of the bale average. In the 77000 bales tested, the length readings were repeated within 0.02″ on 71% of the bales between laboratories.

Ø Length uniformity

The HVI system gives an indication of the fibre length distribution in the bale by use of a length uniformity index. This uniformity index is obtained by dividing the mean fibre length by the upper-half-mean length and expressing the ratio as a percent.  A reading of 80% is considered average length uniformity. Higher numbers mean better length uniformity and lower numbers poorer length uniformity. Cotton with a length uniformity index of 83 and above is considered to have good length uniformity, a length uniformity index below 78 is considered to show poor length uniformity.

Ø Short fibre index

The measure of short-fibre content (SFC) in Motion Control’s HVI systems is based on the fibre length distribution throughout the test specimen. It is not the staple length that is so important but the short fibre content which is important. It is better to prefer a lower commercial staple, but with much lower short-fibre content.

The following data were taken on yarns produced under identical conditions and whose cotton fibres were identical in all properties except for short-fibre content. The effects on ends down and several aspects of yarn quality are shown below.

LOT -A, (8.6% SFC) LOT-B (11.6% SFC)
Ends down / 1000 hrs 7.9 12.8
Skein strength (lb) 108.1 97.4
Single end strength g/tex 15 14.5
apperance index 106 89
Evenness (CV%) 16 17.3
Thin places 15 36
Thick places 229 364
Minor Defects 312 389

These results show that an increase of short-fibre content in cotton is detrimental to process efficiency and product quality. HVI systems measure length parameters of cotton samples by the fibrogram technique. The following assumptions describe the fibro gram sampling process: image

· The fibrogram sample is taken from some population of fibres.

· The probability of sampling a particular fibre is proportional to its length

· A sampled fibre will be held at a random point along its length

· A sampled fibre will project two ends away from the holding point, such that all of the ends will be parallel and aligned at the holding point.

· All fibres have the same uniform density

The High Volume Instruments also provide empirical equations of short fibre content based on the results of cotton produced in the United States in a particular year.

Short Fibre Index = 122.56 – (12.87 x UHM) – (1.22 x UI)

where UHM – Upper Half Mean Length (inches)
UI – Uniformity Index

Short Fibre Index = 90.34 – (37.47 x SL2) – (0.90 x UR)

Where SL2 – 2.5% Span length (inches)
UR – Uniformity Ratio

In typical fibrogram curve, the horizontal axis represents the lengths of the ends of sampled fibres. The vertical axis represents the percent of fibre ends in the fibrogram having that length or greater.

1. Strength and elongation:-

Ø Principle of measurement

HVI uses the “Constant rate of elongation” principle while testing the fibre sample. The available conventional methods of strength measurement are slow and are not compatible to be used with the HVI. The main hindering factor is the measurement of weight of the test specimen, which is necessary to estimate the tenacity of the sample. Expression of the breaking strength in terms of tenacity is important to make easy comparison between specimens of varying fineness.

Ø Method

The strength measurement made by the HVI systems is unlike the traditional laboratory measurements of Pressley and Stelometer in several important ways. First of all the test specimens are prepared in a very different manner. In the laboratory method the fibres are selected, combed and carefully prepared to align them in the jaw clamps. Each and every fibre spans the entire distance across the jaw surfaces and the space between the jaws.

Strength is measured physically by clamping a fibre bundle between 2 pairs of clamps at known distance. The second pair of clamps pulls away from the first pair at a constant speed until the fibre bundle breaks. The distance it travels, extending the fibre bundle before breakage, is reported as elongation.

In the HVI instruments the fibres are randomly selected and automatically prepared for testing. They are combed to remove loose fibres and to straighten the clamped fibres, also brushed to remove crimp before testing. The mechanization of the specimen preparation techniques has resulted in a “tapered” specimen where fibre ends are found in the jaw clamp surfaces as well as in the space between the jaws.

A second important difference between traditional laboratory strength measurements and HVI strength measurements is that in the laboratory measurements the mass of the broken fibres is determined by weighing the test specimen. In the HVI systems the mass is determined by the less direct methods of light absorption and resistance to air flow. The HVI strength mass measurement is further complicated by having to measure the mass at the exact point of breaks on the tapered specimen.

A third significant difference between laboratory and HVI strength measurements is the rate or speed at which the fibres are broken. The HVI systems break the fibres about 10 times faster than the laboratory methods.

Ø Information

Generally HVI grams per Tex readings are 1 to 2 units (3 to 5%) higher in numerical value. In some individual cases that seem to be related to variety, the differences can be as much as 6 to 8% higher. This has not caused a great deal of problems in the US, perhaps because a precedent was set many years ago when we began adjusting our Stelometer strength values about 27% to put them on Presley level.

Relative to the other HVI measurements, the strength measurement is less precise. Going back to our single bale of cotton and doing repeated measurements on the bale we shall find that 68% of the readings will be within 1 g/Tex of the bale average. So if the bale has an average strength of 25 g.tex, 68% of the individual readings will be between 24 and 26 g/Tex, and 95% between 23 and 27 g/Tex

Because of this range in the readings within a single bale, almost all HVI users make either 2 or 4 tests per bale and average the readings. When the average readings are repeated within a laboratory, the averages are repeated to within one strength unit about 80% of  the time. However, when comparisons are made between laboratories the agreement on individual bales to within plus or minus 1 g/tex decreases to 55%.

This decrease in strength agreement between laboratories is probably related to the difficulty of holding a constant relative humidity in the test labs. Test data indicate that 1% shift in relative humidity will shift the strength level about 1%. For example, if the relative humidity in the laboratory changes 3% (from 63 to 66%), the strength would change about 1 g/tex (from 24 to 25 g/Tex)

2. Fibre fineness:-image

Ø Principle of measurement

Fibre fineness is normally expressed as a micronaire value (microgram per inch). It is measured by relating airflow resistance to the specific surface of fibres and maturity ration is calculated using a sophisticated algorithm based on several HVI™ measurements.

Ø Method

The micronaire reading given by the HVI systems is the same as has been used in the commercial marketing of cotton for almost 25 years.  The repeatability of the data and the operator ease of performing the test have been improved slightly in the HVI micronaire measurement over the original instruments by elimination of the requirement of exactly weighing the test specimen. The micronaire instruments available today use microcomputers to adjust the reading for a range of test specimen sizes.

Ø Information

The micronaire reading is considered both precise and referable. For example, if we have a bale of cotton that has an average micronaire of 4.2 and repeatedly test samples from that bale, over two-thirds of that micronaire readings will be between 4.1 and 4.3 and 95 %of the readings between and 4.0 and 4.4. Thus, with only one or two tests per bale we can get a very precise measure of the average micronaire of the bale.

This reading is also very repeatable from laboratory to laboratory.  In USDA approx. 77000 bales were tested per day in each laboratory, micronaire measurements made in different laboratories agreed with each other within 0.1 micronaire units on 77% of the bales.

The reading is influenced by both fibre maturity and fibre fineness. For a given growing area, the cotton variety generally sets the fibre fineness, and the environmental factors control or influence the fibre maturity. Thus, within a growing area the micronaire value is usually highly related to the maturity value.  However, on an international scale, it cannot be known from the micronaire readings alone if cottons with different micronaire are of different fineness or if they have different maturity levels.

3. Moisture image

Ø Principle of measurement

Moisture content of the cotton sample at the time of testing, using conductive moisture probe and the main principle involved in the measurement is based on the measurement of the dielectric constant of a material.

4. Colour

Ø Principle of measurement

Rd (Whiteness), +b (Yellowness), Colour Grade

Measured optically by different colour filters, converted to USDA Upland or Pima Colour Grades or regional customized colour chart.

Ø Other information

The measurement of cotton colour predates the measurement of micronaire, but because colour has always been an important component of classer’s grade it has not received attention as an independent fibre property. However the measurement of colour was incorporated into the very early HVI systems as one of the primary fibre properties.

Determination of cotton colour requires the measurement of two properties, the grayness and yellowness of the fibres. The grayness is a measure of the amount of light reflected from the mass of the fibre. We call this the reflectance or Rd value. The yellowness is measured on what we call Hunter’s +b scale after the man who developed it. The other scales  that describe colour space (blue, red, green) are not measured becasue they are considered relatively constant for cotton.

Returning once again to the measurements  on our single bale, we see that repeated measurements of colour are in good agreement. For greyness or reflectance readings, 68% of the readings will be within 0.5 Rd units of the bale average, and 95% within one Rd unit for the average.

As for yellowness, over two-thirds of these readings will be within one-fourth of one +b unit of the average, and 95% within one-half of one +b unit. The greyness (Rd) and yellowness (+b) measurements are related to grade through a colour chart which was developed by a USDA researcher. The USDA test of 77000 bales showed the colour readings to be the most repeatable of all data between  laboratories; 87% of the bales repeated within one greyness(Rd) unit, and 85% repeated within one-half of one yellowness(+b) unit.

5. Trash content

Ø Principle of measurement

Particle Count, % Surface Area Covered by Trash, Trash Code

Measured optically by utilizing a digital camera, and converted to USDA trash grades or customized regional trash standards.

Ø Other information

The HVI systems measure trash or non-lint content by use of video camera to determine the amount of surface area of the sample that is covered with dark spots.  As the camera scans the surface of the sample, the video output drops when a dark spot (presumed to be trash) is encountered. The video signal is processed by a microcomputer to determine the number of dark spots encountered (COUNT) and the per cent of the surface area covered by the dark spots (AREA). The area and count data are used in an equation to predict the amount of visible non-lint content as measured on the Shirley Analyser. The HVI trash data output is a two-digit number which gives the predicted non-lint content for that bale. For example, a trash reading of 28 would mean that the predicted Shirley Analyser visible non-lint content of that bale would be 2.8%.

While the video trash instruments have been around for several years, but the data suggest that the prediction of non-lint content is accurate to about 0.75% non-lint, and that the measurements are repeatable 95% of the time to within 1% non-lint content.

6. Maturity and stickiness

Ø Principle of measurement

Calculated using a sophisticated algorithm based on several HVI™ measurements.

Ø Other information

Near infrared analysis provides a fast, safe and easy means to measure cotton maturity, fineness and sugar content at HVI speed without the need for time consuming sample preparation or fiber blending.

This technology is based on the near infrared reflectance spectroscopy principle in the wavelength range of 750 to 2500 nanometres. Differences of maturity in cotton fibres are recognized through distinctly different NIR absorbance spectra. NIR technology also allows for the measurement of sugar content by separating the absorbance characteristics of various sugars from the absorbance of cotton material.

Cotton maturity is the best indicator of potential dyeing problems in cotton products. Immature fibres do not absorb dye as well as mature fibres. This results in a variety of dye-related appearance problems such as barre, reduced colour yield, and white specks. Barre is an unwanted striped appearance in fabric, and is often a result of using yarns containing fibres of different maturity levels.  For dyed yarn, colour yield is diminished when immature fibres are used. White specks are small spots in the yarn or fabric which do not dye at all. These specks are usually attributed to neps (tangled clusters of very immature fibres)

NIR maturity and dye uptake in cotton yarns have been shown to correlate highly with maturity as measured by NIR.  A correlation of R=0.96 was obtained for a set of 15 cottons.

In a joint study by ITT and a European research organization, 45 cottons from four continents were tested for maturity using the NIR method and the SHIRLEY Development Fineness/ Maturity tester (FMT). For these samples, NIR and FMT maturity correlated very highly (R=0.94).

On 15 cottons from different growth areas of the USA, NIR maturity was found to correlate with r2 = 0.9 through a method developed by the United States Department of Agriculture (USDA).  In this method, fibres are cross-sectioned and microscopically evaluated.

Sugar Content is a valid indicator of potential processing problems. Near infrared analysis, because of its adaptability to HVI, allows for screening of bales prior to use. The information serves to selected bales to avoid preparation of cotton mixes of bales with excessive sugar content. Cotton stickiness consists of two major causes- honeydew form white flies and aphids and high level of natural plant sugars. Both are periodic problems which cause efficiency losses in yarn manufacturing.

The problems  with the randomly distributed honeydew contamination often results in costly production interruptions and requires immediate action often as severe as discontinuing the use of contaminated cottons.

Natural plant sugars are more evenly distributed and cause problems of residue build-up, lint accumulation and roll laps. Quality problems created by plant sugar stickiness are often more critical in the spinning process than the honeydew stickiness. Lint residues which accumulate on machine parts in various processes will break loose and become part of the fibre mass resulting in yarn imperfections. An effective way to control cotton stickiness in processing is to blend sticky and non-stick cottons. Knowing the sugar content of each bale of cotton used in each mix minimizes day-to-day variations in processing efficiency and products more consistent yarn quality. Screening the bale inventory for sugar content prior to processing will allow the selection of mixes with good processing characteristics while also utilizing the entire bale inventory.

The relationship between percent sugar content by NIR analysis and the Perkins method shows an excellent correlation of r2=0.95. The amount of reducing material on cotton fibre in the Perkins method is determined by comparing the reducing ability of the water extract of the fibre to that of a standard reducing substance. Using the NIR method, the amount of reducing sugar in cotton is measured.

Merits of HVI testing:-

· The results are practically independent of the operator.

· The results are based on large volume samples, and are therefore more significant.

· The time for testing per sample is 0.3 minutes. The respective fibre data are immediately available.

· About 180 samples per hour can be tested and that too with only 2 operators.

· The data are clearly arranged in summarised reports.

· They make possible the best utilisation of raw material data.

· It is best applied to instituting optimum condition for raw material.

· Problems as a result of fibre material can be predicted, and corrective measures instituted before such problems can occur.

· The classing of cotton and the laying down of a mix in the spinning mill. This HVI testing is suitable for the extensive quality control of all the bales processed in a spinning mill.

· The mill is in a position to determine its own quality level within a certain operating range.

Standardized process for hvi testing:-


· Pre-season precision and accuracy tests for all HVIs:-

All offices are required to select known-value cotton samples and perform stringent and consistent performance evaluations, before machines can be placed into production.

· Instrument calibration

Strict calibration procedures used by all offices and Quality Assurance Branch Known-value cottons and tiles used for calibration, Periodic calibration checks, Data is collected, analysed and corrective actions taken when necessary

· Quality Assurance Branch, Check lot Program

Approximately 1% of entire crop is selected from each field office for retest in “QA” as Check lots. Check lot data is returned to classing offices quickly for review. Check lot system assists in monitoring office performance and ensuring proper testing levels.

· Laboratory Atmospheric Conditions:-

Testing laboratories are required to maintain conditions of 70°±1° F and 65%±2% RH. All cotton must stabilize at moisture content level of 6.75%-8.25% prior to HVI testing.

Various HVI models available in market in present date are:-

· USTER® HVI 1000

· Available Options

• Barcode Reader (M700)

• UPS – Uninterrupted Power Supply device

• UV Module

• NEP Module

· ART 2-high volume fibre tester premier

Digg This



Raw material represents about 50 to 70% of the production cost of a short-staple yarn. This fact is sufficient to indicate the significance of the raw material for the yarn producer. It is not possible to use a problem-free raw material always, because cotton is a natural fibre and there are many properties which will affect the performance. If all the properties have to be good for the cotton, the raw material would be too expensive. To produce a good yarn with these difficulties, an intimate knowledge of the raw material and its behaviour in processing is a must.

Fibre characteristics must be classified according to a certain sequence of importance with respect to the end product and the spinning process. Moreover, such quantified characteristics must also be assessed with reference to the following

  • what is the ideal value?
  • what amount of variation is acceptable in the bale material?
  • what amount of variation is acceptable in the final blend

Such valuable experience, which allows one to determine the most suitable use for the raw material, can only be obtained by means of a long, intensified and direct association with the raw material, the spinning process and the end product.

Low cost yarn manufacture, fulfilling of all quality requirements and a controlled fibre feed with known fibre properties are necessary in order to compete on the world’s textile markets. Yarn production begins with the rawmaterial in bales, whereby success or failure is determined by the fibre quality, its price and availability. Successful yarn producers optimise profits by a process oriented selection and mixing of the rawmaterial, followed by optimization of the machine settings, production rates, operating elements, etc. Simultaneously, quality is ensured
by means of a closed loop control system, which requires the application of supervisory system at spinning and spinning preparation, as well as a means of selecting the most suitable bale mix.

A textile fibre is a peculiar object. It has not truly fixed length, width, thickness, shape and cross-section. Growth of natural fibres or production factors of manmade fibres are responsible for this situation. An individual fibre, if examined carefully, will be seen to vary in cross-sectional area along it length. This may be the result of variations in growth rate, caused by dietary, metabolic, nutrient-supply, seasonal, weather, or other factors influencing the rate of cell development in natural fibres. Surface characteristics also play some part in increasing the variability of fibre shape. The scales of wool, the twisted arrangement of cotton, the nodes appearing at intervals along the cellulosic natural fibres etc.

Following are the basic characteristics of cotton fibre

  • fibre length
  • fineness
  • strength
  • maturity
  • Rigidity
  • fibre friction
  • structural features

The atmosphere in which physical tests on textile materials are performed. It has a relative humidity of 65 + 2 per cent and a temperature of 20 + 2° C. In tropical and sub-tropical countries, an alternative standard atmosphere for testing with a relative humidity of 65 + 2 per cent and a temperature of 27 + 2° C
may be used.

The “length” of cotton fibres is a property of commercial value as the price is generally based on this character. To some extent it is true, as other factors being equal, longer cottons give better spinning performance than shorter ones. But the length of a cotton is an indefinite quantity, as the fibres, even in a small random bunch of a cotton, vary enormously in length. Following are the various measures of length in use in different countries

  • mean length
  • upper quartile
  • effective length
  • Modal length
  • 2.5% span length
  • 50% span length

Mean length:
It is the estimated quantity which theoretically signifies the arithmetic mean of the length of all the fibres present in a small but representative sample of the cotton. This quantity can be an average according to either number or weight.

Upper quartile length:
It is that value of length for which 75% of all the observed values are lower, and 25% higher.

Effective length:
It is difficult to give a clear scientific definition. It may be defined as the upper quartile of a
numerical length distribution
eliminated by an arbitrary construction. The fibres eliminated are shorter than half the effective length.

Modal length:
It is the most frequently occurring length of the fibres in the sample and it is related to mean and median for skew distributions, as exhibited by fibre length, in the following way.

(Mode-Mean) = 3(Median-Mean)

Median is the particular value of length above and below which exactly 50% of the fibres lie.

2.5% Span length:
It is defined as the distance spanned by 2.5% of fibres in the specimen being tested when the fibres are parallelized and randomly distributed and where the initial starting point of the scanning in the test is considered 100%. This length is measured using “DIGITAL FIBROGRAPH”.

50% Span length:
It is defined as the distance spanned by 50% of fibres in the specimen being tested when the fibres are parallelized and randomly distributed and where the initial starting point of the scanning in the test is considered 100%. This length is measured using “DIGITAL FIBROGRAPH”.

The South India Textile Research Association (SITRA) gives the following empirical relationships to estimate the Effective Length and Mean Length from the Span Lengths.

Effective length = 1.013 x 2.5% Span length + 4.39
Mean length = 1.242 x 50% Span length + 9.78

Even though, the long and short fibres both contribute towards the length irregularity of cotton, the short fibres are particularly responsible for increasing the waste losses, and cause unevenness and reduction in strength in the yarn spun. The relative proportions of short fibres are usually different in cottons having different mean lengths; they may even differ in two cottons having nearly the same mean fibre length, rendering one cotton more irregular than the other.It is therefore important that in addition to the fibre length of a cotton, the degree of irregularity of its length should also be known. Variability is denoted by any one of the following attributes

  1. Co-efficient of variation of length (by weight or number)
  2. irregularity percentage
  3. Dispersion percentage and percentage of short fibres
  4. Uniformity ratio

Uniformity ratio is defined as the ratio of 50% span length to 2.5% span length expressed as a percentage. Several instruments and methods are available for determination of length. Following are some

  • Shirley comb sorter
  • Baer sorter
  • A.N. Stapling apparatus
  • Fibrograph

uniformity ration = (50% span length / 2.5% span length) x 100
uniformity index = (mean length / upper half mean length) x 100

The negative effects of the presence of a high proportion of short fibres is well known. A high percentage of short fibres is usually associated with,
– Increased yarn irregularity and ends down which reduce quality and increase processing costs
– Increased number of neps and slubs which is detrimental to the yarn appearance
– Higher fly liberation and machine contamination in spinning, weaving and knitting operations.
– Higher wastage in combing and other operations.
While the detrimental effects of short fibres have been well established, there is still considerable debate on what constitutes a ‘short fibre’. In the simplest way, short fibres are defined as those fibres which are less than 12 mm long. Initially, an estimate of the short fibres was made from the staple diagram obtained in the Baer Sorter method

Short fibre content = (UB/OB) x 100

While such a simple definition of short fibres is perhaps adequate for characterising raw cotton samples, it is too simple a definition to use with regard to the spinning process. The setting of all spinning machines is based on either the staple length of fibres or its equivalent which does not take into account the effect of short fibres. In this regard, the concept of ‘Floating Fibre Index’ defined by Hertel (1962) can be considered to be a better parameter to consider the effect of short fibres on spinning performance. Floating fibres are defined as those fibres which are not clamped by either pair of rollers in a drafting zone.

Floating Fibre Index (FFI) was defined as

FFI = ((2.5% span length/mean length)-1)x(100)

The proportion of short fibres has an extremely great impact on yarn quality and production. The proportion of short fibres has increased substantially in recent years due to mechanical picking and hard ginning. In most of the cases the absolute short fibre proportion is specified today as the percentage of fibres shorter than 12mm. Fibrograph is the most widely used instrument in the textile industry , some information regarding fibrograph is given below.

Fibrograph measurements provide a relatively fast method for determining the length uniformity of the fibres in a sample of cotton in a reproducible manner.

Results of fibrograph length test do not necessarily agree with those obtained by other methods for measuring lengths of cotton fibres because of the effect of fibre crimp and other factors.

Fibrograph tests are more objective than commercial staple length classifications and also provide additional information on fibre length uniformity of cotton fibres. The cotton quality information provided by these results is used in research studies and quality surveys, in checking commercial staple length classifications, in assembling bales of cotton into uniform lots, and for other purposes.

Fibrograph measurements are based on the assumptions that a fibre is caught on the comb in proportion to its length as compared to toal length of all fibres in the sample and that the point of catch for a fibre is at random along its length.


Fibre fineness is another important quality characteristic which plays a prominent part in determining the spinning value of cottons. If the same count of yarn is spun from two varieties of cotton, the yarn spun from the variety having finer fibres will have a larger number of fibres in its cross-section and hence it will be more even and strong than that spun from the sample with coarser fibres.

Fineness denotes the size of the cross-section dimensions of the fibre. AS the cross-sectional features of cotton fibres are irregular, direct determination of the area of croo-section is difficult and laborious. The Index of fineness which is more commonly used is the linear density or weight per unit length of the fibre. The unit in which this quantity is expressed varies in different parts of the world. The common unit used by many countries for cotton is micrograms per inch and the various air-flow instruments developed for measuring fibre fineness are calibrated in this unit.

Following are some methods of determining fibre fineness.

  • gravimetric or dimensional measurements
  • air-flow method
  • vibrating string method

Some of the above methods are applicable to single fibres while the majority of them deal with a mass of fibres. As there is considerable variation in the linear density from fibre to fibre, even amongst fibres of the same seed, single fibre methods are time-consuming and laborious as a large number of fibres have to be tested to get a fairly reliable average value.

It should be pointed out here that most of the fineness determinations are likely to be affected by fibre maturity, which is an another important characteristic of cotton fibres.

The resistance offered to the flow of air through a plug of fibres is dependent upon the specific surface area of the fibres. Fineness tester have been evolved on this principle for determining fineness of cotton. The specific surface area which determines the flow of air through a cotton plug, is dependent not only upon the linear density of the fibres in the sample but also upon their maturity. Hence the micronaire readings have to be treated with caution particularly when testing samples varying widely in maturity.

In the micronaire instrument, a weighed quantity of 3.24 gms of well opened cotton sample is compressed into a cylindrical container of fixed dimensions. Compressed air is forced through the sample, at a definite pressure and the volume-rate of flow of air is measured by a rotometer type flowmeter. The sample for Micronaire test should be well opened cleaned and thoroughly mixed( by hand fluffing and opening method). Out of the various air-flow instruments, the Micronaire is robust in construction, easy to operate and presents little difficulty as regards its maintenance.


Fibre maturity is another important characteristic of cotton and is an index of the extent of
development of the fibres. As is the case with other fibre properties, the maturity of cotton fibres varies not only between fibres of different samples but also between fibres of the same seed. The causes for the differences observed in maturity, is due to variations in the degree of the secondary thickening or deposition of cellulose in a fibre.

A cotton fibre consists of a cuticle, a primary layer and secondary layers of cellulose surrounding the lumen or central canal. In the case of mature fibres, the secondary thickening is very high, and in some cases, the lumen is not visible. In the case of immature fibres, due to some physiological causes, the secondary deposition of cellulose has not taken sufficiently and in extreme cases the secondary thickening is practically absent, leaving a wide lumen throughout the fibre. Hence to a cotton breeder, the presence of excessive immature
fibres in a sample would indicate some defect in the plant growth. To a technologist, the presence of excessive percentage of immature fibres in a sample is undesirable as this causes excessive waste losses in processing lowering of the yarn appearance grade due to formation of neps, uneven dyeing, etc.

An immature fibre will show a lower weight per unit length than a mature fibre of the same cotton, as the former will have less deposition of cellulose inside the fibre. This analogy can be extended in some cases to fibres belonging to different samples of cotton also. Hence it is essential to measure the maturity of a cotton sample in addition to determining its fineness, to check whether the observed fineness is an inherent characteristic or is a result of the maturity.


The fibres after being swollen with 18% caustic soda are examined under the microscope with suitable magnification. The fibres are classified into different maturity groups depending upon the relative dimensions of wall-thickness and lumen. However the procedures followed in different countries for sampling and classification differ in certain respects. The swollen fibres are classed into three groups as follows

  1. Normal : rod like fibres with no convolution and no continuous lumen are classed as “normal”
  2. Dead : convoluted fibres with wall thickness one-fifth or less of the maximum ribbon width are classed as “Dead”
  3. Thin-walled: The intermediate ones are classed as “thin-walled”

A combined index known as maturity ratio is used to express the results.

Maturity ratio = ((Normal – Dead)/200) + 0.70
N – % of Normal fibres
D – % of Dead fibres

Around 100 fibres from Baer sorter combs are spread across the glass slide(maturity slide) and the overlapping fibres are again separated with the help of a teasing needle. The free ends of the fibres are then held in the clamp on the second strip of the maturity slide which is adjustable to keep the fibres stretched to the desired extent. The fibres are then irrigated with 18% caustic soda solution and covered with a suitable slip. The slide is then placed on the microscope and examined. Fibres are classed into the following three categories

  1. Mature : (Lumen width “L”)/(wall thickness”W”) is less than 1
  2. Half mature : (Lumen width “L”)/(wall thickness “W”) is less than 2 and more than 1
  3. Immature : (Lumen width “L”)/(wall thickness “W”) is more than 2

About four to eight slides are prepared from each sample and examined. The results are presented as percentage of mature, half-mature and immature fibres in a sample. The results are also expressed in terms of “Maturity Coefficient”

Maturity Coefficient = (M + 0.6H + 0.4 I)/100 Where,

M is percentage of Mature fibres
H is percentage of Half mature fibres
I is percentage of Immature fibres

If maturity coefficient is

  • less than 0.7, it is called as immature cotton
  • between 0.7 to 0.9, it is called as medium mature cotton
  • above 0.9, it is called as mature cotton


There are other techniques for measuring maturity using Micronaire instrument. As the fineness value determined by the Micronaire is dependent both on the intrinsic fineness(perimeter of the fibre) and the maturity, it may be assumed that if the intrinsic fineness is constant then the Micronaire value is a measure of the maturity

Mature and immature fibers differ in their behaviour towards various dyes. Certain dyes are preferentially taken up by the mature fibres while some dyes are preferentially absorbed by the immature fibres. Based on this observation, a differential dyeing technique was developed in the United States of America for estimating the maturity of cotton. In this technique, the sample is dyed in a bath containing a mixture of two dyes, namely Diphenyl Fast Red 5 BL and Chlorantine Fast Green BLL. The mature fibres take up the red dye preferentially, while the thin walled immature fibres take up the green dye. An estimate of the average of the sample can be visually assessed by the amount of red and green fibres.

The different measures available for reporting fibre strength are

  1. breaking strength
  2. tensile strength and
  3. tenacity or intrinsic strength

Coarse cottons generally give higher values for fibre strength than finer ones. In order, to compare strength of two cottons differing in fineness, it is necessary to eliminate the effect of the difference in cross-sectional area by dividing the observed fibre strength by the fibre weight per unit length. The value so obtained is known as “INTRINSIC STRENGTH or TENACITY”. Tenacity is found to be better related to spinning than the breaking strength.

The strength characteristics can be determined either on individual fibres or on bundle of fibres.

The tenacity of fibre is dependent upon the following factorsclip_image004

chain length of molecules in the fibre orientation of molecules size of the crystallites distribution of the crystallites gauge length used the rate of loading type of instrument used and atmospheric conditions

The mean single fibre strength determined is expressed in units of “grams/tex”. As it is seen the the unit for tenacity has the dimension of length only, and hence this property is also expressed as the “BREAKING LENGTH”, which can be considered as the length of the specimen equivalent in weight to the breaking load. Since tex is the mass in grams of one kilometer of the specimen, the tenacity values expressed in grams/tex will correspond to the breaking length in kilometers.

In practice, fibres are not used individually but in groups, such as in yarns or fabrics. Thus, bundles or groups of fibres come into play during the tensile break of yarns or fabrics. Further,the correlation between spinning performance and bundle strength is atleast as high as that between spinning performance and intrinsic strength determined by testing individual fibres. The testing of bundles of fibres takes less time and involves less strain than testing individual fibres. In view of these  considerations, determination of breaking strength  of fibre bundles has assumed greater importance than single fibre strength tests.


There are three types of elongation

  • Permanent elongation: the length which extended during loading did not recover during relaxation
  • Elastic elongation:The extensions through which the fibres does return
  • Breaking elongation:the maximum extension at which the yarn breaks i.e.permanent and elastic elongation together Elongation is specified as a percentage of the starting length. The elastic elongation is of deceisive importance, since textile products without elasticity would hardly be usable. They must be able to deforme, In order to withstand high loading, but they must also return to shatpe. The greater resistance to crease
    for wool compared to cotton arises, from the difference in their elongation. For cotton it is 6 -10% and for wool it is aroun 25 – 45%. For normal textile goods, higher elongation are neither necessary nor desirable. They make processing in the spinning mill more difficult, especially in drawing operations.


The Torsional rigidity of a fibre may be defined as the torque or twisting force required to twist 1 cm length of the fibre through 360 degrees and is proportional to the product of the modulus of rigidity and square of the area of cross-section, the constant of proportionality being dependent upon the shape of the cross-section of the fibre. The torsional rigidity of cotton has therefore been found to be very much dependent upon the gravimetric fineness of the fibres. As the rigidity of fibres is sensitive to the relative humidity of the surrounding atmosphere, it is essential that the tests are carried out in a conditional room where the relative
humidity is kept constant.

Fibre stiffness plays a significant role mainly when rolling, revolving, twisting movements are involved. A fibre which is too stiff has difficulty adapting to the movements. It is difficult to get bound into the yarn, which results in higher hairiness. Fibres which are not stiff enough have too little springiness. They do not return to shape after deformation. They have no longitudinal resistance. In most cases this leads to formation of neps. Fibre stiffness is dependent upon fibre substance and also upon the relationship between fibre length and fibre fineness. Fibres having the same structure will be stiffer, the shorter they are. The slenderness ratio can serve as a measure of stiffness,

slender ratio = fibre length /fibre diameter

Since the fibres must wind as they are bound-in during yarn formation in the ring spinning machine, the slenderness ratio also determines to some extent where the fibres will finish up.fine and/or long fibres in the middle coarse and/or short fibres at the yarn periphery.

In addition to useable fibres, cotton stock contains foreign matter of various kinds. This foreign material can lead to extreme disturbances during processing. Trash affects yarn and fabric quality. Cottons with two different trash contents should not be mixed together, as it will lead to processing difficulties. Optimising process parameters will be of great difficulty under this situation, therefore it is a must to know the amount of trash and the type of trash before deciding the mixing.

A popular trash measuring device is the Shirley Analyser, which separates trash and foreign matter from lint by mechanical methods. The result is an expression of trash as a percentage of the combined weight of trash and lint of a sample. This instrument is used

  • to give the exact value of waste figures and also the proportion of clean cotton and trash in the material
  • to select the proper processing sequence based upon the trash content
  • to assess the cleaning efficiency of each machine
  • to determine the loss of good fibre in the sequence of opening and cleaning.

Stricter sliver quality requirements led to the gradual evolution of opening and cleaning machinery leading to a situation where blow room and carding machinery were designed to remove exclusively certain specific types of trash particles. This necessitated the segregation of the trash in the cotton sample to different grades determined by their size. This was achieved in the instruments like the Trash Separator and the Micro Dust Trash Analyser which could be considered as modified versions of the Shirley Analyser.

The high volume instruments introduced the concept of optical methods of trash measurement which utilised video scanning trash-meters to identify areas darker than normal on a cotton sample surface. Here, the trash content was expressed as the percentage area covered by the trash particles. However in such methods, comparability with the conventional method could not be established in view of the non-uniform distribution of trash in a given cotton sample and the relatively smaller sample size to determine such a parameter. Consequently, it is yet to establish any significant name in the industry.

Fineness determines how many fibres are present in the cross-section of a yarn of particular linear density. 30 to 50 fibres are needed minimum to produce a yarn fibre fineness influences

  1. spinning limit
  2. yarn strength
  3. yarn evenness
  4. yarn fullness
  5. drape of the fabric
  6. lustre
  7. handle
  8. productivity

productivity is influenced by the end breakage rate and twist per inch required in the yarn

Immature fibres(unripe fibres) have neither adequate strength nor adequate longitudinal siffness. They therefore lead to the following,

  1. loss of yarn strength
  2. neppiness
  3. high proportion of short fibres
  4. varying dyeability
  5. processing difficulties at the card and blowroom

Fibre length is one among the most important characteristics. It influnces

  1. spinning limit
  2. yarn strength
  3. handle of the product
  4. lustre of the product
  5. yarn hairiness
  6. productivity

It can be assumed that fibres of under 4 – 5 mm will be lost in processing(as waste and fly). fibres upto about 12 – 15 mm do not contribute to strength but only to fullness of the yarn. But fibres above these lengths produce the other positive characteristics in the yarn.

The proportion of short fibres has extremely great influence on the following parameters

  1. spinning limit
  2. yarn strength
  3. handle of the product
  4. lustre of the product
  5. yarn hairiness
  6. productivity

A large proportion of short fibre leads to strong fly contamination, strain on personnel, on the machines, on the work room and on the air-conditioning, and also to extreme drafting difficulties.

A uniform yarn would have the same no of fibres in the cross-section, at all points along it. If the fibres themeselves have variations within themselves, then the yarn will be more irregular.

If 2.5% span length of the fibre increases, the yarn strength also icreases due to the fact that
there is a greater contribution by the fibre strength for the yarn strength in the case of longer fibres.

Neps are small entanglements or knots of fibres. There are two types of neps. They are 1.fibre neps and 2.seed-coat neps.In general fibre neps predominate, the core of the nep consists of unripe and dead fibres. Thus it is clear that there is a relationship between neppiness and maturity index. Neppiness is also dependent on the fibre fineness, because fine fibres have less longitudinal stiffness than coarser fibres.

Nature produces countless fibres, most of which are not usable for textiles because of inadequate strength.

The minimum strength for a textile fibre is approximately 6gms/tex ( about 6 kn breaking length).

Since blending of the fibres into the yarn is achieved mainly by twisting, and can exploit 30 to 70% of the strength of the material, a lower limit of about 3 gms/tex is finally obtained for the yarn strength, which varies linearly with the fibre strength.

Low micronaire value of cotton results in higher yarn tenacity.In coarser counts the influence of micronaire to increase yarn tenacity is not as significant as fine count.

Fibre strength is moisture dependent. i.e. It depends strongly upon the climatic conditions and upon the time of exposure. Strength of cotton,linen etc. increases with increasing moisture content.

The most important property inflencing yarn elongation is fibre elongation.Fibre strength ranks seconds in importance as a contributor to yarn elongation. Fibre fineness influences yarn elongation only after fibre elongation and strength. Other characters such as span length, uniformity ratio, maturity etc, do not contribute significantly to the yarn elongation.Yarn elongation increases with increasing twist. Coarser yarn has higher elongation than finer yarn. Yarn elongation decreases with increasing spinning tension. Yarn elongation is also influenced
by traveller weight and high variation in twist insertion.

For ring yarns the number of thin places increases, as the trash content and uniformity ratio increased For rotor yarns 50%span length and bundle strength has an influence on thin places.

Thick places in ringyarn is mainly affected by 50%span length, trash content and shor fibre content.

The following expression helps to obtain the yarn CSP achievable at optimum twist multiplier with the available fibre properties.

Lea CSP for Karded count = 280 x SQRT(FQI) + 700 – 13C
Lea CSP for combed count = (280 x SQRT(FQI) + 700 – 13C)x(1+W)/100
L = 50% span length(mm)
S = bundle strength (g/tex)
M = Maturity ratio measured by shirly FMT
F = Fibre fineness (micrograms/inch)
C = yarn count
W = comber waste%

Higher FQI values are associated with higher yarn strength in the case of carded counts but in combed count such a relationship is not noticed due to the effect of combing

Higher 2.5 % span length, uniformity ratio, maturity ratio and lower trash content results in lower imperfection. FQI does not show any significant influence on the imperfection.

The unevenness of carded hosiery yarn does not show any significant relationships with any of the fibre properties except the micronaire value. As the micronaire value increases, U% also increases. Increase in FQI however shows a reduction in U%.

Honey-dew is the best known sticky substance on cotton fibres. This is a secretion of the cotton louse. There are other types of sticky substances also. They are given below.

  • honey dew – secretions
  • fungus and bacteria – decomposition products
  • vegetable substances – sugars from plant juices, leaf nectar, over production of wax,
  • fats, oils – seed oil from ginning
  • pathogens
  • synthetic substances – defoliants, insecticides, fertilizers, oil from harvesting machines

In the great majority of cases, the substance is one of a group of sugars of the most variable composition, primarily but not exclusively, fructose, glucose, saccharose, melezitose, as found, for example on sudan cotton. These saccharides are mostly, but not always, prodced by insects or the plants themselves, depending upon the influence on the plants prior to plucking. Whether or not a fibre will stick depends, not only on the quantity of the sticky coating and it composition, but also on the degree of saturation as a solution. Sugars are broken down by fermentation and by microorganisms during storage of the cotton. This occurs more quickly the higher the moisture content. During spinning of sticky cotton, the R.H.% of the air in the production are should be held as low as possible.

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