Contents NEW. Fiber Quality Roving Quality Yarn Quality. Contents 1

Transcription

1 Contents Fiber Quality Roving Quality Yarn Quality Contents 1 1 About the Origin and the Significance of the USTER STATISTICS Introduction USTER STATISTICS as Benchmarks USTER STATISTICS for Yarn Contracts and Product Specifications USTER STATISTICS for Textile Machinery Manufacturers Users Contributions Towards Improving the USTER STATISTICS 6 2 Quality Characteristics of the USTER STATISTICS 2007 and Their Significance 7 3 Restrictions Restrictions Imposed by the Raw Material Restrictions Imposed by the Final Product Restrictions Imposed by the Yarn Design Missing Correlation Between Different Quality Characteristics Outliers and Frequent Defects in a Spinning Mill Restrictions in Guarantee Agreements Reproducibility and Variability of Measurements 6 4 The Making of the USTER STATISTICS 18 5 Interpreting and Applying the USTER STATISTICS Elements of the USTER STATISTICS Comparability of Practical Measurements and Data Provided in the USTER STATISTICS 20 NEW 6 Changes and Improvements New Fiber Quality Characteristics Distinction Between Knitting and Weaving Yarns New Yarn Quality Characteristics New: Yarn Twist Characteristics The USTER CLASSIMAT QUANTUM System 22 7 Validity 24 8 Disclaimer 25 9 Testing Conditions and Sample Sizes 26

2 10 Appendix Fiber Properties Fiber Bundle Testing Single Fiber Testing Ambient Laboratory Conditions for Fiber Testing Fiber Processing Roving Testing Yarn Testing Count Variation Testing Mass Variation Testing Yarn Hairiness Testing Imperfections Testing Yarn Diameter, Cross-sectional Shape and Density Testing Yarn Trash and Yarn Dust Testing Twist Testing Tensile Properties Testing HV Tensile Properties Testing Ambient Laboratory Conditions for Yarn Testing Useful Conversions English/Metric Conversions Count Conversions Staple Conversion Chart Special Conversions 44 2

3 Slivers NEW Contents 1 1 Introduction 2 2 Restrictions 4 3 The Making of the USTER STATISTICS 6 4 Interpreting and Applying the USTER STATISTICS 7 5 Sliver Quality Mass Variations Testing Conditions 8 6 Validity 9 7 Disclaimer 10 Yarns Made Out of Man- Made Cellulosic Fibers NEW Introduction 1 Fiber to Yarn Introduction 1 3

4 1 About the Origin and the Significance of the USTER STATISTICS 1.1 Introduction The USTER STATISTICS are quality reference figures which permit a classification of fibers, slivers, rovings and yarns with regard to world production. The last USTER STATISTICS for cotton fibers and yarns were published in The USTER STATISTICS 2007 again address cotton fibers, rovings and yarns. We will later turn to the restrictions regarding the use of the USTER STATISTICS. We recommend to read these restrictions carefully and adhere to them. When used properly the USTER STATISTICS will continue to be appreciated as reference figures by all groups of interested people. The USTER STATISTICS are first and foremost a practical guide to «good textile practices» in the field of yarn manufacturing. The evidence of specific defects or shortcomings in overall yarn quality, which may become apparent through using the STATISTICS as a comparative standard, can be translated into immediate corrective action in the manufacturing process. Reliable and unequivocal cause/ effect relationships have been established over the years and documented in the application literature. Legions of textile technologists and USTER instrument users in mills around the world put that experience into action in their daily routine. In the previous edition of the USTER STATISTICS, we introduced a graph which illustrated the improvement in yarn evenness between 1957 and Now, six years later, we publish the same diagram again (Fig. 1). Two additional data points were added to the curves, i.e. the evenness values of the 50% line of the USTER STATISTICS A further improvement in yarn evenness can be recognized in Fig. 1 for combed cotton yarns. Fig. 1 Improvement in Yarn Evenness between

5 As described in the USTER STATISTICS 2001, the USTER STATISTICS 2007 also distinguish between knitting yarns and weaving yarns for ring-spun yarns. Of course, quality is multi-faceted, and while evenness has improved, other parameters have deteriorated to some degree. However, more than other quality parameters, yarn evenness is closely associated with both the design and management of the entire manufacturing process. Thus, besides being a result of technological advancements, evenness has also improved as a result of more elaborate quality control and quality management practices. It is of paramount importance for the spinning industry to closely monitor these trends and to prepare for a timely and appropriate response. Once lagging behind, a mill will have to invest heavily to move on and catch up and to eventually keep pace with the global development of yarn quality. 1.2 USTER STATISTICS as Benchmarks The USTER STATISTICS have been made for quality benchmarking on the corporate level. Benchmarking is a total quality management tool and denotes the procedure of identifying and quantifying topnotch or world-class performance (benchmarks) in a particular business or product category and comparing the data with the performance of the own company or product. Established benchmarks and quality standards substantiate the feasibility of attaining greater proficiency and of narrowing the performance gap. They legitimize the implementation of strategies to enhance the manufacturing process as a result of hard facts rather than management intuition. In other industries, the availability of reliable competitor information for comparative analyses in benchmarking is a major obstacle. Thanks to the USTER STATISTICS, data on the quality levels achieved by the top manufacturers in the textile industry are public domain and easily accessible. 1.3 USTER STATISTICS for Yarn Contracts and Product Specifications The USTER STATISTICS regularly serve as the platform for yarn contracts and product specifications in the framework of commercial transactions. This practice is commonly accepted by the manufacturers, merchants, and processors of yarns. Many sales yarn spinners, weavers, knitters, and retailers have formulated quality requirements based on the USTER STATISTICS. By experience they have determined what quality levels are appropriate for what application. As a more general guideline to the prevailing quality requirements, literature is available which addresses the subject of yarn specifications for an array of applications and end uses in both knitting and weaving. Much of the experience disclosed through these publications emanated from applying the USTER STATISTICS. Buyers and salesmen involved in the traditional commodity type trade or in direct purchasing and sales are certainly among the most enthusiastic users of the USTER STATISTICS. They appreciate the STATISTICS as a means of categorizing many different qualities by face value. An indistinct yet popular belief prevails in the international markets for reasonably priced yarns that largely correspond to the 25 th percentile of the USTER STATISTICS to be in high demand. Every now and then, such a belief manifests an utter quality overkill with regard to the actual processing and end use requirements; in other cases, such specifications may well be justified. In the long run, however, the market as a whole is and will continue to be driven by the rule of supply and demand, irrespective of where, when, and by whom the STATISTICS are referred to in order to advertise or bargain. Good grades on the overall quality, though, will always serve as a passport to both the domestic and international markets. 5

6 1.4 USTER STATISTICS for Textile Machinery Manufacturers Textile machinery manufacturers as well as manufacturers of accessories for textile machines have frequently been using the USTER STATISTICS to appraise the impact on quality of their new developments in the field of machine technology or monitoring and control systems. While machine performance in terms of productivity or efficiency is easily expressed in absolute numbers, the STATISTICS are frequently referred to when it comes to quality aspects. The other side of the coin is that the machinery manufacturers have also been forced into the routine of giving performance guarantees based on the USTER STATISTICS. Again, this particular issue falls into the category of restrictive uses and will be addressed later. 1.5 Users Contributions Towards Improving the USTER STATISTICS Because of the constructive criticism that we received from among the industry, the USTER STATISTICS for fiber and yarn quality have substantially improved over the years. We are invariably grateful for constructive contributions. 6

7 2 Quality Characteristics of the USTER STATISTICS 2007 and Their Significance The USTER STATISTICS 2007 include all the quality characteristics which were published already in the USTER STATISTICS In addition to this, we were able to contribute with some more quality characteristics of fibers and yarns in the USTER STATISTICS For the first time we publish Foreign Fiber STATISTICS for the USTER CLASSIMAT QUANTUM. The following list encompasses all quality characteristics featured in the USTER STATISTICS It is subdivided into tables for fibers and tables for yarns. All definitions of fiber quality characteristics which require an explanation are described in detail in Fig. 2 through 5. Description of cotton fiber quality characteristics (USTER HVI) Quality Abbreviation Description Unit characteristics Micronaire Mic Indicates fiber fineness - Upper Half UHML Corresponds to the classer's staple. mm Mean Length Definition according to Fig. 2 Uniformity Index UI Measure for variations of % fiber length, length uniformity Bundle tenacity Strength Breaking tenacity g/tex measured on fiber bundle Reflexion Rd Degree of reflexion of the cotton. % The higher this value, the better the cotton is rated. Yellowness +b Assessment of color, % degree of yellowness Trash CNT Number of trash particles - per defined area Trash Area Percentage of trash % per defined area Short Fiber Index SFI Amount of short fibers % calculated from the fibrogram Spinning Consistency SCI Calculated value based on - Index a regression equation that takes into account all HVI properties Maturity Index Mat Maturity of the cotton fibers - (HVI method) 7

8 Description of cotton fiber quality characteristics (USTER AFIS) Quality Abbreviation Description Unit characteristics Neps Neps/g Number of neps /g per gram Seed-coat neps SCN/g Number of seed-coat neps /g per gram Short fiber content SFC(n) Short fiber content % SFC(w) by number (n) and by weight (w). Definition according to Fig. 3 Upper Quartile UQL(w) Corresponds to the classer's staple. mm Length Definition according to Fig. 3 Fiber fineness Fine Fineness of fibers mtex Immature fibers IFC Immature fiber content. % Percentage of immature fibers. Definition according to Fig. 4, Fig. 5 Maturity Mat Ratio of mature to immature fibers. - Definition according to Fig. 5 Trash particles Trash/g Number of trash particles /g per gram Dust particles Dust/g Number of dust particles /g per gram Visible foreign matter VFM Visible foreign matter % 8

9 The fiber length diagram determined by means of the USTER HVI instrument is not an end-aligned staple diagram and is called fibrogram. Fig. 2 is a schematic fibrogram of cotton. Fig. 2 Fibrogram The USTER AFIS instrument measures each fiber separately and, therefore, all the information for an end-aligned staple diagram is available. Fig. 3 illustrates how the «Upper Quartile Length» (UQL) and the short fiber content are determined using the USTER AFIS. The UQL is the fiber length at 25%. The term «upper quartile» indicates that the value is calculated at the upper quarter of the staple diagram. Fig. 3 Staple diagram 9

10 Fig. 4 and Fig. 5 show the definition of the measured values in relation to the maturity characteristics. The respective parameters can be explained using Fig. 4. Fig. 4 shows the cross-section of a cotton fiber. Fig. 4 Cotton fiber, cross-section To compute the mean degree of thickening theta, a circular cross-section of the measured fiber having a perimeter P is calculated, and subsequently area A 1 is divided by area A2. Fig. 5 shows a maturity measurement using the USTER AFIS as well as the values computed for theta. Fig. 5 Maturity Histogram For this example, the following apply: Mature fiber content R = 37.6% Immature fiber content IFC = 10.3% Maturity (according to Lord): M = R - IFC = =

11 Description of yarn quality characteristics (USTER TESTER) Quality Abbreviation Description Unit characteristics Count variations CV c b Count variations between packages % Mass variations CV m Coefficient of variation of mass % Mass variations CV m b Coefficient of variation of mass % between packages Imperfections Thin Number of thin places, /1000 m Thick thick places and neps Neps Hairiness H Absolute value of hairiness. - Measurement of the entire fiber length. Standard deviation s H Standard deviation of hairiness - of hairiness within a package Coefficient of variation CV H b Variation of hairiness % of hairiness between packages Trash Dust Dust and trash in yarns. /1000 m Trash Counts refer to 1000 m of yarn. Coefficient of variation CV d Variation of the yarn diameter % of the diameter Shape Shape Shape of the yarn cross-section. - Ratio of the axes of an ellipse. Density D Density of the yarn g/cm 3 Description of yarn quality characteristics of rovings (USTER TESTER) Quality Abbreviation Description Unit characteristics Count variation CV c b Count variations between % roving bobbins Mass variation CV m Coefficient of variation of mass, % cut length 1 cm Mass variation CV m3m Coefficient of variation of mass, % cut length 3 m 11

12 Description of yarn quality characteristics (USTER TENSORAPID) Quality Abbreviation Description Unit characteristics Strength F H Breaking force cn Tenacity R H Breaking force referred cn/tex to the yarn count Coefficient of variation CV R H Variation of the individual values % of tenacity of the tenacity Elongation ε H Yarn elongation at breaking force % Coefficient of variation CVε H Variation of the individual % of elongation elongation values Work done to break W H Work performed during tensile cncm testing of yarns at breaking force Coefficient of variation CV W H Variation of the individual values % of work done of work done to break 12

13 Description of yarn quality characteristics (USTER TENSOJET) Quality Abbreviation Description Unit characteristics Strength (Force) F H Breaking force cn Tenacity R H Breaking force referred cn/tex to the yarn count Coefficient of variation CV R H Variation of the individual values % of tenacity of the tenacity Elongation ε H Yarn elongation at breaking force % Coefficient of variation CVε H Variation of the individual % of elongation elongation values Work done to break W H Work performed during tensile cncm testing of yarns at breaking force Coefficient of variation CV W H Variation of the individual values % of work done of work done to break Weak places F H P= % of all tests cn in the yarn/strength have a strength below this value Weak places ε H P=0.1 in the yarn/elongation 0.1% of all tests % have an elongation below this value Weak places F H P= % of all tests cn in the yarn/strength have a strength below this value Weak places ε H P=0.01 in the yarn/elongation 0.01% of all tests % have an elongation below this value 13

14 3 Restrictions This section addresses the restrictions that apply to the use of the USTER STATISTICS and we would like to repeat our advice that this be read carefully and adhered to. Both deliberate and unintentional misuse of the STATISTICS have in some instances in the past resulted in lengthy and costly disputes all of which could have been avoided if all parties involved would have had the same clear understanding of the concept underlying the STATISTICS. The reading of this section is a must for those who are not familiar with that concept, with the STATISTICS as such, or with the proper interpretation of the data. 3.1 Restrictions Imposed by the Raw Material Four primary variables have a decisive impact on corporate success in our textile environment as well as in any other industrial venture: man, machine, material, and know-how or information in general. Among these four key elements, the raw material is the crucial component which largely dictates quality but also productivity and cost in yarn manufacturing. By virtue of their design, the USTER STATISTICS for spun yarns do not provide direct access to information about the raw material used for spinning. However, those differences in raw material usage are indirectly reflected in the data. A high-quality yarn can only be spun from high-quality raw materials and since the raw material frequently accounts for more than 50% of the total manufacturing costs in the medium to fine count range, the utilization of high-quality, high-priced raw materials will be proportionally reflected in the yarn price. Any measures taken in the field of raw materials will not only have a considerable impact on quality but also on a mill s competitiveness and bottom-line profitability. In those rare cases where the STATISTICS have been corrupted, the motives have always been related to what evidently is the single most important driving force in the global textile scenario: price. The USTER STATISTICS, however, provide a dependable indication of quality, exclusively. Although quality is a somewhat elusive term, it is nevertheless a result of tangible assets and thus to a certain degree interrelated with the sales price of a product. The USTER STATISTICS should not be interpreted as saying 5% is «good». In contrary, the 5% line might be indicative of high cost, high price, luxuriousness even a tendency to price oneself out of the market. By the same token, 95% should not imply «poor» it might be indicative of a very attractive price and just the right quality for the target markets. A «good» spinner is actually one who is in a position to achieve an acceptable quality level from a less expensive fiber the genuine mastery of spinning. The trouble starts when the USTER STATISTICS are referred to in order to corroborate complaints about a low rating in certain quality categories. This complaint may be directed at the «good» spinner who produces a reasonably priced yarn from a reasonably priced fiber. Yarn price, however, is directly proportional to fiber quality and fiber quality in turn dictates yarn quality to a great extent. Consequently, pushing yarn quality towards better values would simply cannibalize the price advantage. The USTER STATISTICS should be employed as what they really are: a global survey of yarn quality as produced in every part of the world. Whether or not these qualities are produced economically from adequate raw materials and offered at a legitimate price is certainly beyond the scope of the STATISTICS. 14

15 3.2 Restrictions Imposed by the Final Product It lies in the nature of the matter that end uses remain somewhat vague when yarns are marketed via merchants or importers. It is rare for any merchant to have firm orders before entering into a contract. Consequently, the focus is on obtaining qualities that are likely to meet the requirements of any potential customer and which can be successfully marketed in many places and at any given point in time. In the current buyer s market, merchants have a large number of alternative sources to choose from. Yet, to minimize risk, commodity type yarns with high volume of trade are preferred. Under these circumstances, specified and actual quality requirements seem to have very little in common. 3.3 Restrictions Imposed by the Yarn Design When properly tailored to the anticipated end use, yarns will exhibit inherent strengths and weaknesses: As opposed to weaving yarns, for instance, knitting yarns produced from cotton, man-made fibers, or blends thereof are spun at low twist multipliers. They will rarely display a high breaking tenacity. If they did, they would probably result in stiff, harsh fabrics. A somewhat lower breaking tenacity must also be expected from knitting yarns spun from low-tenacity or pillresistant man-made fibers which are specifically designed for that purpose. Such low-tenacity fibers, however, usually result in excellent yarn elongation. Knitting yarns also possess a higher hairiness. While this would be detrimental to weaving yarns, the knitted fabric enjoys a greater cover and a softer hand. To make it clear: It is technically impossible and fatal with respect to the end use to demand that a yarn be perfect in all categories, say above the 25% line of the USTER STATISTICS. The proper way out of this dilemma is for the yarn producer and the yarn processor to jointly develop detailed specifications or requirement profiles for specific end uses. Many good examples of this partnership approach have become known and the USTER STATISTICS can be of tremendous help in realizing such projects. 3.4 Missing Correlation Between Different Quality Characteristics Unfortunately, the USTER STATISTICS still mislead some people into thinking in causal relationships that do not exist in reality. Several quality parameters displayed in the STATISTICS are believed to be highly correlated but the fact is that they are not. High breaking tenacity, for instance, is not necessarily linked to high breaking elongation; rather, yarn elongation is determined by spinning speed, spinning geometry, and the resultant specific spinning tension. Likewise, a very even yarn may well have a high nep count. End uses calling for a relative freedom of neps cannot be satisfied by using yarns with a good USTER CV. The opposite is sometimes the case: Few neps in a very uniform yarn tend to visually stick out like a black sheep. Yarns with a little higher CV m or greater hairiness tend to conceal neps in the overall irregularity, much like the often quoted needle in a haystack. If there is a problem with neppy appearance and no way to reduce nep counts, try to go a little higher with the CV m. 15

16 3.5 Outliers and Frequent Defects in a Spinning Mill It is a popular illusion that yarns with a high rating according to the USTER STATISTICS are always above and beyond suspicion. A good overall quality does not only encompass excellent mean values but also low variability of the quality attributes as well as unconditional consistency. Only one bad package in the creel of a knitting machine or in warping is bound to ruin several hundred yards of greige fabric. We have come a long way in gaining control over sporadic yarn defects by on-line quality monitoring and over scattered weak places by applying the USTER TENSOJET. Every now and then, however, various off-quality situations tend to recur with malicious persistence in spite of the blind faith often put in the USTER STATISTICS ratings. These include outliers, mix-ups, overlength/ underlength or damaged packages, problems with package unwinding behavior, missing transfer tails, improper waxing, shedding and fly, dye streaks (barré), white specks, contamination with foreign fibers just to name a few. Quality in a broader sense has many dimensions: A truckload of 5% USTER STATISTICS yarn that arrives too late at the weaver s loading ramp will not be considered a quality product. Timing is vital due to the seasonal characteristic of the textile business with its frequent peak demands and, of course, due to the increasing popularity of just-in-time and quick response production. 3.6 Restrictions in Guarantee Agreements The issue of performance guarantees negotiated between yarn producers and machinery manufacturers has already been briefly touched upon. Such performance guarantees based on the USTER STATISTICS must be considered a dubious practice when the effect of raw material, machine settings, maintenance, ambient conditions, and operator proficiency is neglected. A legitimate performance guarantee should include references to in-depth technological trials conducted prior to preparing such a document. It should also embrace technically sound prohibitive clauses that serve to preclude misunderstandings or even worse litigation between machinery manufacturers and yarn producers. In the majority of all cases, it is not the machine that produces poor quality. If it would not have to process a capricious material like textile fibers, the average textile machine would probably run uninterruptedly for ten, fifteen years or more without any major problems at all. Before making claims against machinery manufacturers, the potential source of the quality problem as well as its true nature and extent should be investigated thoroughly and objectively. 3.7 Reproducibility and Variability of Measurements Last but not least, a few comments on reproducibility and variability of measurements. No matter what measuring instrument is used from yardstick to atomic clock there will always be a certain measurement error. This is also true for textile testing. There are three types of measurement errors: avoidable error, systematic error (bias), and random error. Avoidable error encompasses the failure to choose an appropriate measurement method or to properly operate a measuring instrument. In the textile laboratory, this is of little significance but selecting instrument settings and sample conditioning present a potential source of avoidable error. Systematic error includes calibration error, instrument tolerances, and the fluctuation of ambient conditions. This type of error can be quantified fairly accurately. Random error is the most critical component in textile testing. It is predominantly caused by the variability of the tested material itself. Its magnitude can be approximated by statistical calculations the confidence interval of the mean. The absolute error of a measurement is the total of all three types of errors. A measurement should therefore always be reported as x±dx, i.e. the mean value plus/minus the total error to indicate that the true measure- 16

17 ment value is located somewhere within that interval. All USTER instruments calculate the confidence intervals automatically and they are part of the test report. The confidence interval covers the random error component; information on the systematic error, i.e. instrument tolerances, is provided in our application handbooks. When comparing actual measurements with the data illustrated in the USTER STATISTICS, it is of utmost importance that the total measurement error is kept to an absolute minimum to warrant compatibility. If this is not the case, false conclusions may be drawn from such a comparison. There are four items that can be done to minimize the measurement error: proper conditioning under constant standard atmospheric conditions exact calibration of the instrument correct settings of the instrument adequate sample size When actual measurements are then compared with the USTER STATISTICS, they would appear in the nomogram as a short vertical line not as a dot. The top and bottom ends of that line represent the upper and lower limits of the confidence interval with the mean exactly in the middle. We cannot eliminate the random error; however, the confidence interval quickly becomes smaller when the sample size is increased. For detailed information on recommended sample sizes and testing conditions, please refer to section 9. In the context of commercial agreements via yarn contracts and product specifications, it frequently transpires that disputes result from discrepancies between measurements performed by the purchaser and by the supplier and from the subsequent comparison of disparate measurements with the USTER STATISTICS. When such incidents are examined more closely, the result often is that the basic conditions listed above have been ignored or have simply not been identical in both testing locations. In other cases, the problem could be quickly resolved by applying the t-test procedure. It proved that the differences were not statistically significant but strictly random due to a pronounced sample variability. The t-test procedure along with further detailed explanations is outlined in our application handbooks. A simplified t-test can be performed by comparing the confidence intervals: If the confidence intervals of two means overlap, then the observed difference between the two means is random or statistically insignificant; if they are separated, the difference is considered statistically significant. Applying the concept of the confidence interval can be both very helpful and revealing. It pinpoints the highly variable characteristic of textile materials which should always be taken into consideration. 17

18 4 The Making of the USTER STATISTICS The USTER STATISTICS are not established by merely collecting data. They are established by testing actual yarn and fiber samples that we procure on a truly global scale via our agents, overseas partners, or direct contacts with our international clientele. Several thousand samples have been tested in our ISO 9001 certified textile laboratory in Uster, Switzerland. The geographical distribution of the origin of all samples procured for the USTER STATISTICS is illustrated in Fig. 6. The total volume of samples was tested between spring 2002 and North & South America 17% Europe 20% Africa 12% Asia & Oceania 51% Fig. 6 Geographical distribution of the origin of all samples procured for the USTER STATISTICS 2007 All data were entered into a databank and application software specifically developed for this purpose was employed to compute the percentile curves and to plot the graphical representations. The lion s share of the total time spent was definitely devoted to thoroughly testing the samples in the laboratory. Our databank has grown to an enormous size and consists of far more quality parameters than have been published in this edition of the USTER STATISTICS. 18

19 5 Interpreting and Applying the USTER STATISTICS 5.1 Elements of the USTER STATISTICS The USTER STATISTICS manual consists of several parts, each addressing a specific quality aspect in the sequence from fiber to yarn. The different sections are arranged according to spinning system and raw material composition or yarn style. Each section is subdivided into distinct quality attributes (e.g. mass variation, tensile properties, etc.) which are measured with different USTER instruments. A measurement can consist of several individual parameters. Mass variation, for instance, includes CVm and the between-sample variation CVmb. These parameters are presented in graphical form. The origin of the samples processed to establish the raw data is illustrated by a pie chart. These pie charts are provided with each quality attribute but not with each parameter because the measurements were performed simultaneously on the same samples. The most important element of the USTER STATISTICS are the nomograms with the percentile curves. The width of the percentile curves intentionally imposes certain restrictions on accuracy a subtle reminder of the pronounced variability of most textile measurements. Depending on the quality parameter displayed on the ordinate (vertical or y-axis), the curves are plotted over staple length, process stage, yarn count, or defect category and the abscissa (horizontal or x-axis) is calibrated accordingly. The x-axis should be the starting point of any analysis. The percentile curves refer to the percentage of the total world production which equals or exceeds the measurement value given for a particular yarn or fiber description. An example: The coefficient of variation of the yarn mass of an Ne 30 (Nm 50, 20 tex) 100% combed cotton ring-spun yarn for knitted fabrics has an evenness of CVm = 13%. A vertical line drawn from the x-axis at Ne 30 intersects with the horizontal line drawn from the y-axis at 13% right at the 75 th percentile line. Hence, 75% of all Ne 30 combed cotton ring-spun yarns produced worldwide have a CVm of 13.0% or better. Vice versa, 25% of the total world production of comparable Ne 30 yarns exhibit a CVm higher than 13%. The 50 th percentile curve, commonly referred to as the 50% line, corresponds to the median. In general terms, the median is the middle number when the measurements in a data set are arranged in ascending (or descending) order, i.e. 50% of all observations exceed this value and the other 50% lie below. Depending on whether the frequency distribution of a given quality parameter is symmetric or skewed, the median may or may not be different from the mean. In some instances, adjacent percentile curves fell very close together. To avoid the formation of a solid red block, both the 25% line and 75% line were omitted, thus maintaining the clarity of the illustration. The nomograms in the fiber properties section as well as the ones in the fiber-toyarn and yarn quality sections for combed cotton ring-spun yarns comprise two independent sets of percentile curves. The two sets of curves each characterize a distinct cluster or isolated population within the same graph. We will look at the cotton fiber properties first to explain the reasons for this differentiation: The horizontal position of the split point at a staple length of mm marks the approximate center of the transition zone from both short and medium-staple cottons on one hand to long and extra long-staple cottons on the other. With that transition, several factors change fundamentally. These factors include genetic, botanical, and physiological differences, agricultural methods, environmental influences, harvesting and ginning practices, all of which have a decisive impact on fiber properties. On the yarn side, things are much simpler. Here, the division between Ne 41 (Nm 70, 14 tex) and Ne 47 (Nm 80, 12.5 tex) indicates the yarn count threshold for using longer staple, high-grade cottons with an overall superior fiber quality, for increasing comber noil extraction, and for modifying the overall processing conditions accordingly. Selecting higher quality cotton fibers and adjusting the processing conditions is necessary to raise the spin limit towards the finer counts. Naturally, in the fiber-to-yarn nomograms for combed roving, the two clusters occur as well. The curves had to be split at exactly the same position on the yarn count axis. The graphs provide an opportunity to study these effects of raw material selection and processing. 19

20 5.2 Comparability of Practical Measurements and Data Provided in the USTER STATISTICS When comparisons are made between practical measurements and the data provided in the USTER STATISTICS, it is important to consider all aspects that may impair compatibility. Please make sure that the instruments are in proper technical condition and calibrated correctly. Periodic maintenance through authorized Uster Technologies service personnel is a guarantee for trouble-free performance and accurate measurement results. Instrument settings and testing speeds should be identical to those used for testing in the framework of the USTER STATISTICS. These settings and speeds are listed in the appendix along with recommendations concerning an adequate sample size, which is equally important. Please refer to the operating instructions of the instruments for further technical details. Testing must be carried out under constant standard atmospheric conditions. The standard atmosphere for textile testing involves a temperature of 20±2 C (68±4 F) and 65±2% relative humidity (ISO 139). Prior to testing, samples must be conditioned to moisture equilibrium under constant standard atmospheric conditions. To attain the moisture equilibrium, a conditioning time of at least 24 hours is required, 48 hours is preferred. For samples with a high moisture content, conditioning time should be at least 48 hours unless the samples are preconditioned, so that the moisture equilibrium is later approached from the dry side. 20

21 6 Changes and Improvements 6.1 New Fiber Quality Characteristics Three new quality characteristics were introduced with the USTER STATISTICS 2007: The Short Fiber Index, the Spinning Consistency Index for USTER HVI Systems, and the Fiber Fineness for USTER AFIS Systems. 6.2 Distinction Between Knitting and Weaving Yarns In the USTER STATISTICS 2007 a distinction was made again between weaving and knitting yarns. The threshold between weaving and knitting yarn has been determined to be the following twist multipliers: Combed cotton yarn ae = 3.7 (am = 112) Carded cotton yarn ae = 3.9 (am = 119) Yarns with twist multipliers below these values have been classified as knitting yarns. 6.3 New Yarn Quality Characteristics The two optical sensors OM and OI were used in the tests using the USTER TESTER 4. They record the following quality characteristics: Variation of the yarn diameter, shape of the yarn cross-section, yarn density and the number of dust and trash particles in the yarn. When the first USTER STATISTICS for imperfections were published in 1957, a decision was taken after prolonged testing to define the following thresholds: thins 50%, thicks +50%, neps +200%. These values refer to the mean number of fibers in a cross-section of a yarn. As explained in Fig. 1, the mass unevenness improved to such an extent in the past 40 years that often no imperfection counts can be found in combed cotton yarns in the middle and coarse range. Therefore, a decision was taken to include the next lower thresholds, i.e. the settings: thins 40%, thicks +35%, neps +140% and for rotor yarns and airjet yarns +200%. In addition, not only the tenacity but also the strength of yarns were determined during the tensile tests for the USTER STATISTICS. Nowadays, variations of quality characteristics are increasingly determined using the coefficient of variation CV. Therefore, the unevenness U is not published in the USTER STATISTICS 2007 anymore. The conversion factor CV = 1.25 U can be used here for mass variations with normal distribution. 21

22 6.4 New: Yarn Twist Characteristics The amount of twist placed in a staple spun yarn is important from a technical viewpoint because of its effect on physical properties and performance and on finished product appearance. It is of course also important from a production standpoint because with every turn of twist there is an accompanying loss in productivity and an increase in cost. Twist also impacts fabric appearance, fullness, hand, weight, and strength. With the integration of a twist tester in the product range of Uster Technologies, we are now able to provide USTER STATISTICS also for the important quality parameter of the twist. Besides the absolute twist of the yarn, which is usually given by the end use, the variation of the twist plays a more important role in the evaluation of the yarn quality. Therefore, the absolute twist should not be interpreted as a quality parameter of the yarn, but as a guideline, which twist levels are used in the textile industry. In this first edition of the USTER STATISTICS for twist, we can present benchmarks for 14 different materials: 100% CO, ring yarn, combed & carded, knitting and weaving, bobbins 50/50%, PES/CO, ring yarn, bobbins 50/50%, 67/33%, 65/35% PES/CO, ring yarn, carded & combed, bobbins 100% PES, ring yarn, bobbins 100% WO, ring yarns, worsted, bobbins 55/45% PES/WO, worsted, bobbins 100% CV, ring yarn, bobbins 50/50%, 70/30%, PES/CV, ring yarn, bobbins 6.5 The USTER CLASSIMAT QUANTUM System The appearance of a fault in the finished product, i.e. a woven or knitted fabric, is largely determined by its size. A yarn fault classification according to crosssection and length is therefore the basis for the assessment of yarn faults. By classification we understand the arrangement of yarn faults within a schematic (CLASSIMAT matrix) according to the fault data. Tried and tested for many years, the classification matrix consists of 23 classes for the classification of "normal" thick and thin places. For a better assessment of yarn types with different structures, such as ply yarns or compact yarns, the classification matrix was extended by 4 additional classes. Of course, the extended classes can also be used for conventional yarns and can even provide additional helpful information. Seldom-occurring yarn faults are categorized in the classification matrix of the USTER CLASSIMAT QUANTUM (Fig. 7). The classification begins at a length of 0.1 cm and is basically open in length. Thick places are counted if the mean mass of a yarn is exceeded by at least 100% in the case of short faults or by 45% in the case of faults over 8 cm. With thin places, however, the actual value must be at least 30% below the mean value. The positive and the negative range of the top and bottom classes are open as well. In the yarn fault classification, the yarn faults are entered in the CLASSIMAT matrix according to the fault length and fault cross-section. The faults are identified with a letter and a number. The letters stand for the fault length and the number indicates the deviation of the cross-section in comparison to the perfect yarn. Fig. 7 shows the standard matrix with 23 classes. For ply yarns and compact yarns there exist classes between +75% and +100%. 22

23 Fig. 7 Classification matrix for disturbing thick and thin places Disturbing thick and thin places up to Ne 60 were measured with the capacitive clearer USTER QUANTUM C20. The thick and thin places from Ne 61 to Ne 170 were measured with the clearer USTER QUANTUM C15. However, it is not required that the CLASSIMAT operator has to switch over to a different measuring head at Ne 60. The USTER CLASSIMAT QUANTUM is also in a position to classify foreign fibers. Therefore, this instrument cannot only detect the remaining and disturbing thick and thin places but also the remaining foreign fibers. Fig. 8 Classification matrix for disturbing foreign fibers 23

24 7 Validity The information provided with this edition supersedes all the descriptions pertaining to yarn quality published in previous editions of the USTER STATISTICS. The quality of industrially manufactured goods is a moving target. It depends on a multitude of factors, most of which are an intrinsic function of time. The dependence on time is predominantly related to the state of technology of the productive assets and the technological know-how prevalent in the industry. Time is also a factor in determining the overall economic environment, the supply and demand situation, as well as general consumer attitudes and behavior. All of the above, acting jointly or separately, may have an effect on the quality of raw materials, semi-processed, or finished textile goods. Consequently, the validity of the information provided in the USTER STATISTICS 2007 is confined to the period of time actually covered by the data. The data are essentially of historical nature by the time this document is published. Naturally, such information will not sustain its initial significance as time progresses and eventually become obsolete unless it is updated at some point in the future. Therefore, the information presented in this document in either verbal, numerical, or graphical form is subject to change at any time without prior or public notice. Conventional wisdom proves, however, that the USTER STATISTICS maintain their significance over an extended period of five years or more. With no exceptions, all the information provided in the USTER STATISTICS 2007 relates to data which have been established using USTER products. USTER products are designed, manufactured, and distributed by Uster Technologies, Switzerland, and Uster Technologies Inc., USA, or authorized licensees, exclusively. Any attempt to utilize the information provided in this document in conjunction with data originating from sources other than USTER instruments may result in some form of failure or damage. The USTER STATISTICS are intended for use as a manual of comparative STATISTICS complementing the operational installations of USTER products at the customer site. For technical details on how to ensure proper agreement between the data presented in this document and data established with other USTER instruments, please refer to the appendix. 24

25 8 Disclaimer This publication and the information provided therein is for intended use only and subject to change at any time without prior or public notice. Uster Technologies will not assume liability for any direct or indirect damage resulting from unintended use of this publication or the information provided therein. The use of this information for product specifications in commercial contracts is discouraged unless clear reference is made to this publication or parts thereof and clear numerical specifications and tolerances are provided in the contract. The use of this information for arbitration purposes is discouraged unless clear reference is made to this publication or specified parts thereof and clear numerical specifications and tolerances are provided in legally valid contractual documents pertaining to the characteristics of the goods in question. The use of this information for performance guarantees relating to textile plants, textile machines, or parts or accessories thereof is discouraged unless clear reference is made to this publication or parts thereof and clear numerical specifications, tolerances, and restrictive clauses pertaining to other known influences on the specified performance are provided in the guarantee documents. 25

26 9 Testing Conditions and Sample Sizes All tests in relation to the USTER STATISTICS 2007 were carried out under constant climatic conditions. The temperature was 20 C, the relative humidity 65%. The following table lists the testing conditions and the sample sizes. Fiber Testing Parameter Abbreviation Unit Instrument No. of Tests samples within Micronaire Mic --- USTER HVI 0 Upper Half UHML mm USTER HVI 0 Mean Length UI % 0 Bundle tenacity Strength g/tex USTER HVI 0 Color Rd % USTER HVI 0 +b Trash CNT --- USTER HVI 0 Area % 0 Short Fiber Index SFI % USTER HVI 0 Spinning Consistency SCI --- USTER HVI 0 Index Maturity Index Mat --- USTER HVI 0 Neps Neps/g /g USTER AFIS 0 SCN/g /g 0 Length SFC(n) % USTER AFIS 0 SFC(w) % 0 UQL(w) mm 0 Maturity Fine mtex USTER AFIS 0 IFC % 0 Mat Trash Trash/g /g USTER AFIS 0 Dust/g /g 0 VFM % 0 26

27 Yarn Testing Parameter Abbrevia- Unit Instrument No. of Tests tion samples within Count CV c b % USTER 0 1 variations TESTER 4 FA Sensor Mass CV m % USTER 0 1 variations CV m b % TESTER CS Sensor Testing speed: Duration of test: 400 m/min 2.5 min Hairiness H --- USTER 0 1 s H --- TESTER CV H b % OH Sensor 10 1 Testing speed: Duration of test: 400 m/min 2.5 min Imper- Thin places 1/1000 m USTER 0 1 fections Thick places 1/1000 m TESTER Neps /1000 m CS Sensor 10 1 Testing speed: Duration of test: 400 m/min 2.5 min Trash Dust /1000 m USTER 0 1 Trash /1000 m TESTER OI Sensor Testing speed: Duration of test: 400 m/min 2.5 min Diameter CV d % USTER 0 1 variation Shape --- TESTER Density g/cm 3 OM Sensor 10 1 Testing speed: Duration of test: 400 m/min 2.5 min Twist T /m USTER ZWEIGLE CV T % TWIST TESTER Test method: 1 Tensile F H cn USTER 0 20 properties R H cn/tex TENSORAPID CV R H % 0 20 ε H % 0 20 CVε H % 0 20 W H cncm CV W H % 0 20 Testing speed: 5 m/min 27

28 Parameter Abbrevia- Unit Instrument No. of Tests tion samples within HV tensile F H cn USTER properties R H cn/tex TENSOJET CV R H % ε H % CVε H % W H cncm CV W H % F H P=0.1 cn ε H P=0.1 % F H P=0.01 cn 0 10,000 ε H P=0.01 % 0 10,000 Testing speed: 400 m/min Testing of Rovings Parameter Abbreviation Unit Instrument No. of Tests samples within Count variation CV c b % USTER 0 TESTER 4 Length 10 m FA Sensor Count variation CV m % USTER 0 TESTER 4 CS Sensor Testing speed: Duration of test: 50 m/min 5 min. Count variation CV m3m % USTER 10 TESTER 4 CS Sensor Testing speed: Duration of test: 50 m/min 5 min. 28

29 10 Appendix The following paragraphs provide useful background information on the different measurements. It is not our intention to give detailed explanations of the instruments, measurement methods, or the technological significance of each measurement, since they have been described in chapter 2. Many instrument users are well acquainted with these aspects to begin with and specialized literature which focuses on these topics is readily available. This appendix primarily serves to clarify certain questions that may arise when studying the USTER STATISTICS and it gives valuable, practical hints as to the origin, interpretation, and use of certain data. Needless to say that if you have any specific needs, please do not hesitate to contact us or your nearest Uster Technologies representative office Fiber Properties The USTER STATISTICS on raw cotton fiber properties have been established with USTER HVI and USTER AFIS instruments. The corresponding nomograms have been developed from a representative cross-section of nearly 1,200 different international cottons. All percentile curves are plotted over staple length. Staple length is the fundamental characteristic of cotton as a textile fiber. In the USTER STATISTICS nomograms, HVI and AFIS parameters or the percentiles indicating a certain share of the world cotton production can be determined for a given staple length. Staple length is usually specified in the contract as classer s or trade staple. Upper half mean length (UHML) describes the equivalent staple length of cottons classified by HVI. An alternative is to use the 25% staple length by weight (UQL(w)) measured with AFIS. This measurement also closely corresponds to the classer s staple. The pie charts indicating the distribution of sample origins are missing in the fiber properties section. The reason for that is very simple: The source of each sample is known to us, of course, but in many cases, the true geographic origin of the cottons was not. A sample may have been furnished by a German mill, for instance, but the respective cotton bale may have come from Central Asia or somewhere else and these details have not always been disclosed to us. Please note that the data in the USTER STATISTICS cover several crop years. The average fiber quality of cottons from a certain growing region changes from one year to another as a result of the prevalent environmental conditions during the growing season. With the consideration of more than one crop year, however, these differences are leveled out Fiber Bundle Testing The USTER HVI (High-Volume Instrument) system is designed to measure large quantities of bale cotton samples within a minimum time frame. This exclusive feature offers the possibility of classing entire cotton crops on an annual basis, the activities of the US Department of Agriculture (USDA) being an outstanding example for such an immense project. HVI systems are also utilized to class complete warehouse inventories or commercial bale shipments at either the cotton producer s, merchant s, or spinner s end of the business. Determining cotton fiber properties on a per-bale basis is a necessary prerequisite for computerized bale management in the spinning mill. Some 1,950 HVI systems are installed in over 65 countries worldwide, serving the purposes outlined above. Typical HVI measurements include Micronaire, fibrogram length and length uniformity, 1 /8 inch gauge length bundle tenacity, reflectance and yellowness on Hunter s scale as well as optical trash particle counts and trash area. 29

30 There is still some confusion about the use of calibration cottons. However, since 1998 only HVI Calibration Cotton is available from the US Department of Agriculture, Agricultural Marketing Service (USDA-AMS) in Memphis, Tennessee, USA. The USDA discontinued the provision of ICC. Using HVI-CC and ICC for calibration results in different test results which are not comparable with each other and do not correlate with each other in any way. If the system is calibrated using HVI-CC, the upper half mean length (UHML), the mean length (ML) and the uniformity index (UI) are obtained. Strength results with this calibration are on a higher level than with ICC calibration cotton. Nowadays, Uster Technologies recommends to use only HVI-CC for calibration, and all tests within the framework of the USTER STATISTICS were conducted using an HVI-CC calibrated system. The USDA supplies special cottons for Micronaire calibration, since the Micronaire range provided by HVI-CC cottons is not nearly large enough. Special calibration tiles are available to calibrate the colorimeter and the grade boxes along with a dot matrix tile are used for trash meter calibration (USTER HVI SPEC- TRUM only dot matrix tile and self-defined cottons). The calibration tiles mentioned are part of a USTER HVI SPECTRUM shipment. Both the United States Department of Agriculture, Agricultural Marketing Services in Memphis, Tennessee, and the Fiber Institute in Bremen, Germany, conduct regular HVI round tests on an international basis. Participation in such programs is highly recommended for the monitoring of service personnel and instrument performance, i.e. the consistency of the measurements and the compatibility with other laboratories. Cotton fiber testing with USTER HVI systems is a standardized procedure and is described in detail in ASTM D Further explanations of the individual functional elements of the system, the significance of the measurements, and the proper calibration and operation of the instrument are given in the operating instructions. Adequate sample conditioning and maintaining constant standard atmospheric conditions in the laboratory during testing is of extreme importance because of the hygroscopic nature of cotton fibers. Please refer to section of this appendix for more information on ambient laboratory conditions for fiber testing. References to fiber testing standards: ISO 2403, ASTM D-1448: ASTM D-1447: ASTM D-1445: ASTM D-2253: ASTM D-2812: ASTM D-4605: Micronaire reading of cotton fibers Fibrograph measurement of length and length uniformity Breaking strength and elongation (flat bundle method) Nickerson/Hunter colorimeter Non-lint content of cotton High-volume instrument testing (SPINLAB system) Single Fiber Testing The USTER AFIS (Advanced Fiber Information System) is a sophisticated and versatile laboratory instrument for single fiber testing. A pair of pin-type opening rollers, partially surrounded by carding segments, individualize the fibers and separate non-fibrous components. The fiber individualizer unit utilizes the principle of aero-mechanical separation to extract trash particles, large seed coat fragments, and other types of foreign matter from the original fiber specimen. These objects are conveyed through the trash channel. Individual fibers, neps, and small seed coat fragments (seed coat neps) pass through the fiber channel. Electro-optical sensors are installed in both the trash and the fiber channel and advanced signal processing technology is applied to identify and characterize several thousand individual cotton fibers, fiber entanglements, and foreign matter. The modular concept of the USTER AFIS system provides comprehensive information on the frequency distribution of pertinent dimensional parameters: single fiber length 30

31 and the size of neps, trash, and dust particles. The novel features of the AFIS instrument comprise the assessment of single fiber fineness and maturity distributions as well as the discriminative detection of seed coat fragments. The USTER AFIS has gained international recognition as the most sensible answer to process control and quality monitoring needs in yarn manufacturing. Some 800 USTER AFIS units are installed in over 50 countries. The abundance of information provided by the USTER AFIS is a result of determining the complete frequency distribution of each measurement. Such distributions include information on the mean values, standard deviations, the number of observations, and several other parameters that can be calculated using these few basic characteristics of a frequency distribution. However, in the USTER STATISTICS on fiber quality of cotton in bale form, only the mean values of the following measurements are considered: The number of neps and of seed coat neps per gram of cotton, the percentage of fibers shorter than ½ inch (12.7 mm) by number and by weight (short fiber content, SFC(n),(w)), trash and dust particle counts per gram, visible foreign matter (VFM), the number of immature fibers, fiber count and maturity. Proper calibration of the instrument is a necessary prerequisite to make correct comparisons between the actual USTER AFIS measurements and the USTER STATISTICS. The calibration of an USTER AFIS should be left to authorized Uster Technologies service personnel. We recommend that reference samples, e.g. round test samples, be used to monitor the consistency of the measurements and to contact the nearest Uster Technologies service station if unexpected changes or long-term drift should occur. The Fiber Institute in Bremen, Germany, conducts AFIS round tests on an international basis. Participation in such programs is highly recommended for closely monitoring the performance of service personnel and of the instrument, i.e. the consistency of the measurements and the compatibility with other laboratories. This, of course, includes compatibility with the USTER STATISTICS as well. Nep testing with the USTER AFIS system is a standardized procedure and is described in detail in ASTM D Further explanations of the individual functional elements of the system, the significance of the measurements, and the proper calibration and operation of the instrument are given in the operating instructions. Adequate sample conditioning and maintaining constant standard atmospheric conditions in the laboratory during testing is important. Please refer to section of this appendix for more information on ambient laboratory conditions for fiber testing. References to fiber testing standards: ASTM D-5866: AFIS nep testing Ambient Laboratory Conditions for Fiber Testing Cotton fibers are highly hygroscopic and their properties change notably as a function of the moisture content. This is particularly critical in the case of dynamometric properties, e.g. cotton fiber strength. As a result, conditioning and testing must be carried out under constant standard atmospheric conditions. The standard temperate atmosphere for textile testing involves a temperature of 20±2 C (68±4 F) and 65±2% relative humidity. In tropical regions, maintaining a temperature of 27±2 C (81±4 F) at 65±2% relative humidity is legitimate, but then the absolute moisture content of the conditioned air is different. Modern air conditioning systems, however, are capable of achieving 20±2 C (68±4 F) and 65±2% relative humidity in most any location in the world and in the interest of international harmonization, these ambient conditions should be realized whenever possible. Prior to testing, the samples must be conditioned under constant standard atmospheric conditions until in moisture equilibrium with the surrounding air. To attain the moisture equilibrium, a conditioning time of at least 24 hours is required, 48 hours is preferred. For samples with a high moisture content, 31

32 conditioning time should be at least 48 hours unless the samples are preconditioned, so that the moisture equilibrium is later approached from the dry side. During conditioning, samples should be arranged in single layers in perforated trays to allow conditioned air to circulate freely. The moisture content of the samples to be tested should not differ from that of the cottons used for calibrating the measuring instrument. Therefore, calibration cottons should be subjected to the same conditioning procedures or, alternatively, stored permanently inside the conditioned laboratory. Laboratory conditions should be monitored by appropriate devices that record both short-term fluctuation and long-term drift. References to fiber testing standards: ISO 139, EN , DIN : Standard atmosphere for conditioning and testing 10.2 Fiber Processing In cotton yarn manufacturing, the AFIS length, nep, and trash modules have been successfully employed to determine raw material properties, to monitor and optimize production machinery, and to replace static, periodic overhaul schedules by flexible, targeted maintenance. The performance of the opening and cleaning line, of cards, and combers can be substantially enhanced by analyzing the input/ output relationship of fiber length and short fiber content, neps, and trash. This is accomplished by a modification of the corresponding machine configurations, settings, and speeds. Statistical process control techniques provide an opportunity for the proper timing of maintenance interventions when the parameters monitored by the AFIS exceed the established control limits. The effects of these measures include a substantial improvement of the yarn and fabric quality and a concurrent reduction of operating cost and waste. By identifying and selecting the most suitable cottons for the processing into yarns with the desired quality levels, further savings in the field of raw materials can be generated. The cotton fiber processing section of the USTER STATISTICS represents a statistical analysis of in-process AFIS measurements which have been performed on a large number of samples drawn at important intermediate processing stages: Bale, card mat, card sliver, comber sliver, finisher drawing, and roving. The through-the-mill processing sequences in carded and combed ring spinning are labeled A...G and A...H, in carded open-end spinning A...F and A...H. They are identified by a legend. At trash/g and dust/g the values for yarns, measured with the OI sensor of the USTER TESTER 4, are indicated as well. Since the samples came from specific mills, a distribution of the sample sources is provided in the form of a pie chart. This distribution does not relate to fiber origin, i.e. cotton growing area, but to the locations of the mills that furnished the samples. The cotton growing area is unknown. The following is of utmost importance when making a comparison between the results obtained in actual mill processing and the USTER STATISTICS: The percentile curves in the fiber processing nomograms connect independent data points. Each data point represents one of the five percentiles (5 th, 25 th, 50 th, 75 th, and 95 th percentile) which have been calculated from all samples from the same processing stage. Therefore, the 50% curve, for instance, does not represent the typical behavior of an average spinning process; rather, it indicates the theoretical process curve that would be obtained if the parameters measured at each processing stage would always correspond to the 50 th percentile. In practice, we will rarely encounter a spinning process that will exactly track one of the percentile curves. In addition, the confidence intervals must be taken into consideration. An example relating to AFIS neps: A mill processes a raw material with an average of 175± x neps/g. This would correspond to the 50 th percentile. After opening and cleaning, we find 230± x neps/g in the card mat, which represents a point between the 25 th and 50 th percentile curve. Carding removes 78% of the neps and leaves 50± x neps/g in the card sliver. Again, this nep count is positioned in close vicinity to the 50 th percentile curve. Our mill ends up with 32

33 28± x neps/g in the combed sliver and is back on the 50% curve. The USTER STATISTICS on through-the-mill nep levels can also be used in conjunction with a USTER LVI 720 stand-alone nep tester. When making an assessment of the manufacturing process, it is equally important to consider the overriding influence of the raw material. Machine performance is not independent of the raw material. Experience proves that in the majority of all cases, poor processing results are to some extent related to the fibrous material processed. Textile machines are meticulously engineered products. If they are well maintained, operated at moderate speeds and with appropriate settings, they will deliver excellent quality provided sufficient know-how has also been put into the selection of adequate raw materials. The effect of raw materials is also indirectly represented in the USTER STATISTICS nomograms on fiber processing. It is a well-known fact, for example, that some cottons or cotton mixes are more prone to nep formation in opening and cleaning than others. The tendency towards nep formation is particularly critical with very fine or immature fibers, i.e. fibers with lower bending rigidity. Likewise, there are cottons which have a tendency to more strongly resist nep removal in carding. Less mature cottons will also suffer more pronounced fiber damage during mechanical processing and exhibit a higher short fiber content. The absolute breaking strength of such fibers is much lower due to the lack of cellulose in the fiber cell wall. The actual reduction of the short fiber content in combing is clearly dependent on the percentage of short fibers present in the raw material and thus in the lap prior to combing. Furthermore, trash removal efficiency in mill processing is not only a function of the absolute amount of trash in the raw material but also of the general cleanability of a cotton mix, which is related to both the fiber properties and the post-harvest processing history of the cottons. These factors should be thoroughly investigated before making adjustments in the process or at individual machines. Proper calibration of the instrument is a necessary prerequisite to make correct comparisons between the actual AFIS measurements and the USTER STATIS- TICS on fiber processing. The calibration of an AFIS should be left to authorized Uster Technologies service personnel. We recommend that reference samples, e.g. round test samples, be used to monitor the consistency of the measurements and to contact the nearest Uster Technologies service station if unexpected changes or long-term drift should occur. The Fiber Institute in Bremen, Germany, conducts AFIS round tests on an international basis. Participation in such programs is highly recommended for closely monitoring the performance of the instrument, i.e. the consistency of the measurements and the compatibility with other laboratories. This, of course, includes compatibility with the USTER STATISTICS as well. Nep testing with the USTER AFIS system is a standardized procedure and is described in detail in ASTM D Further explanations of the individual functional elements of the system, the significance of the measurements, and the proper calibration and operation of the instrument are given in the operating instructions. Adequate sample conditioning and maintaining constant standard atmospheric conditions in the laboratory during testing is important. References to fiber testing standards: ASTM D-5866: AFIS nep testing 10.3 Roving Testing The USTER STATISTICS 2007 again include measurements of rovings from cotton and worsted mills which were made in our textile laboratory using the USTER TESTER 4. 33

34 10.4 Yarn Testing A new aspect which frequently led to disagreements and uncertainties concerns different quality requirements in relation to subsequent use of yarns in processing, which are manufactured and traded world wide. Hitherto, no distinction has been made in the USTER STATISTICS. This deficiency has been remedied in the USTER STATISTICS 2001 edition. Therefore, yarns are shown in different nomograms according to their subsequent processing purpose, i.e. weaving yarn or knitting yarn. As in the USTER STATISTICS 1997 edition, a distinction has been made between cotton qualities on bobbins and on packages. Again, reference measurements of yarn mass variations, hairiness and imperfections on bobbins and on crosswound packages are available for 100% carded and combed ring-spun cotton yarns. Hereinafter, you will find the considerations at that time that led to this distinction particularly in the cotton segment. Practical experience has proven time and time again that winding alters the yarn surface structure. The impact on yarn evenness (CV m ) is very limited but changes in imperfection counts (thin places, thick places, and neps), hairiness (H), and standard deviation of hairiness (sh) are much more pronounced. Under normal circumstances, the tensile properties, i.e. tenacity, elongation, and workto-break are not affected unless yarns are subjected to excessive winding tension, which is very rarely the case and certainly not a prudent practice. A clear statement must be made concerning the role of the winding machine: Changes in the yarn surface structure due to winding cannot be avoided. Nobody would honestly expect a yarn to become better after it has been accelerated from zero to 1200 m/min or more in a few milliseconds while being pulled off the bobbin, dragged across several deflection bars and eyelets, forced into a traverse motion at speeds that make it invisible, and finally rolled up into a firm construction called package or cone. The factors that affect the yarn structure during winding include the frictional properties of the yarn itself, the bobbin geometry and the bobbin unwinding behavior, winding speed, winding geometry as well as the number and design of the yarn/machine contact points. However, much as the bobbin unwinding behavior today is the limiting factor for winding speed, it is also the main reason for these changes in yarn structure. Most of the damage occurs at the moment when the end is detached and removed from the tight assembly of yarn layers on the bobbin and dragged along the tube at very high speeds. High-speed, automatic winders have frequently been blamed for causing higher nep counts but this is not a correct statement. Typical nep-type imperfections, i.e. short mass defects, can be identified as tight fiber entanglements, clumps of immature or dead cotton fibers, or seed coat fragments. Naturally, such defects are not produced by the winding machine. The increase in nep counts after winding is related to the formation of loose fiber accumulations. These fiber accumulations represent a true mass defect, yet their appearance in the yarn and in the final fabric is clearly different from that of typical fiber entanglements or seed coat fragments. When testing 100% cotton yarns in package form for evenness, imperfections, and hairiness with the USTER TESTER, some very fine and delicate yarns will again respond with marginal structural changes. This is not a result of mechanical stress like in winding but a natural reaction caused by the reversal of the yarn running direction. Directional influences are omnipresent; they become apparent in all subsequent processing stages. The evidence of changes in the yarn surface structure due to the winding process or as a result of reversing the yarn running direction is confined to a few very delicate 100% man-made fiber yarns, core yarns, and 100% cotton yarns finer than Ne 60 (Nm 100, 10 tex). We recommend, however, that the USTER STATISTICS on 100% carded and combed cotton ring-spun yarns on cross-wound packages be referred to whenever mass variation, hairiness, and imperfections of cotton yarns in package form are of interest. Since the tensile properties are not affected by the phenomena described above, the USTER STATISTICS on ring-spun bobbins should be used for packages as well. The STATISTICS on count variation and the between-sample 34

35 coefficients of variation of evenness and hairiness are only useful when testing bobbins. Testing packages of ring-spun yarns always involves the risk of catching the top end of one bobbin and the bottom end of another (plus the splice in between), which may distort the measurements. Incorrect comparisons with the USTER STATISTICS may also result from testing actively conditioned yarns. Active thermal conditioning is performed at the very end of the manufacturing process to suppress the twist liveliness or the yarn torque. This is normally accomplished by treating bobbins or packages with high-temperature water vapor in a conditioning chamber or in a vacuum environment with low-temperature saturated steam in the gaseous phase. In any case, the moisture regain of the fibers may alter their physical properties and affect capacitive yarn testing. In addition, the moisture is not always homogeneously distributed within a thermally conditioned bobbin or package. Therefore, changes in tenacity, elongation, and work-to-break as well as evenness, imperfections, and defect levels must be expected. The bobbin and package samples tested within the framework of the USTER STATISTICS have been cleared of all packing material upon receipt, preconditioned in a dry atmosphere for several days or weeks, and conditioned to moisture equilibrium under constant standard atmospheric conditions. By doing so, any adverse effects on testing caused by thermal conditioning are completely eliminated. Please refer to section of this appendix for more information on proper sample conditioning and ambient laboratory conditions for yarn testing. The influence of the raw material on the quality of spun yarns has been extensively covered on the first pages of these USTER STATISTICS. It is a true fact of life that nobody can spin a world-class yarn from coarse wool or short and weak cotton fibers even if the latest and best machinery is employed. The quality status achieved by a spinner always represents the compound effect of the skills of the work force and the management, the performance of the machines, the quality of the raw material, and the know-how in processing technology Count Variation Testing The term count variation (CVcb) denotes the between-sample coefficient of variation of yarn count in percent. Count variation can be determined semi-automatically with the USTER AUTOSORTER by reeling 100 m or 120 yards of yarn off each bobbin or package and placing each skein on the balance. The calculation is performed by the instrument. The F/A module of the USTER TESTER 4 provides a fully automatic determination of the yarn count and count variation. Count variation is no longer as critical as it used to be some years ago. It is a welldocumented fact that a count variation of CVcb>3.0% can impair fabric appearance, primarily in knitting. However, the application of feed control systems from the bale opener to the card, short-term and long-term card autoleveling, and drawframe autoleveling at ever shorter lengths, in particular, has improved the situation appreciably. Proper calibration of the instrument is a necessary prerequisite to make correct comparisons between the actual AUTOSORTER or USTER TESTER 4 measurements and the USTER STATISTICS on count variation. The calibration of an AUTOSORTER or USTER TESTER should be left to authorized Uster Technologies service personnel. Please contact the nearest Uster Technologies service station if unexpected changes or long-term drift should occur. TESTEX AG in Zurich, Switzerland, conducts yarn quality round tests on an international basis. Participation in such a program is highly recommended for closely monitoring the performance of the serivce personnel and of the instrument, i.e. the consistency of the measurements and the compatibility with other laboratories. This, of course, includes compatibility with the USTER STATISTICS as well. The determination of the yarn count is a standardized procedure and is described in detail in ISO Further explanations of the individual functional elements of the USTER AUTOSORTER or the USTER TESTER 4, the significance of the 35

36 measurements, and the proper calibration and operation of the instruments are given in the operating instructions. Adequate sample conditioning and maintaining constant standard atmospheric conditions in the laboratory during testing is important. Please refer to section of this appendix for more information on ambient laboratory conditions for yarn testing. References to count variation testing: ISO 2060, DIN : Determination of yarn count Mass Variation Testing The assessment of mass variation with the USTER TESTER needs no introduction. The USTER STATISTICS on mass variation include nomograms on the coefficient of variation of yarn mass (CVm) and the between-sample coefficient of variation of the CVm (CVmb). A USTER TESTER 4 has been used for testing of all yarn samples that have been procured for the USTER STATISTICS However, the STATISTICS on mass variation are fully compatible with the data provided by the preceding product generations, i.e. USTER TESTER 1, USTER TESTER 2, and USTER TESTER 3. Proper calibration of the instrument is a necessary prerequisite to make correct comparisons between the actual USTER TESTER measurements and the USTER STATISTICS on mass variation. The calibration of a USTER TESTER should be left to authorized Uster Technologies service personnel. Please contact the nearest Uster Technologies service station if unexpected changes or long-term drift should occur. TESTEX AG in Zurich, Switzerland, conducts yarn quality round tests on an international basis. Participation in such a program is highly recommended for closely monitoring the performance of the service personnel and of the instrument, i.e. the consistency of the measurements and the compatibility with other laboratories. This, of course, includes compatibility with the USTER STATISTICS as well. The determination of yarn unevenness by electronic yarn testing instruments with capacitive sensors is a standardized procedure and is described in detail in ISO Further explanations of the individual functional elements of the USTER TESTER, the significance of the measurements, and the proper calibration and operation of the instrument are given in the operating instructions and in the application handbook on evenness testing. Adequate sample conditioning and maintaining constant standard atmospheric conditions in the laboratory during testing is important. Please refer to section of this appendix for more information on ambient laboratory conditions for yarn testing. References to yarn mass variation standards: ISO 2649, DIN : Determination of yarn evenness Yarn Hairiness Testing The first statistical information on yarn hairiness was presented in the 1989 edition of the USTER STATISTICS. In the following years, the hairiness measurement has become firmly established in the industry. The hairiness module of the USTER TESTER 4 consists of an electro-optical sensor which converts the scattered light reflections of the peripheral fibers into a corresponding electrical signal while the solid yarn body is eclipsed. The hairiness measurement is performed simultaneously with the measurement of yarn evenness and imperfections. Yarn hairiness is expressed in the form of the hairiness value H, which is an indirect measure for the number and the cumulative length of all fibers protruding from the yarn surface. This value, along with the within-sample standard deviation of hairiness (s H ) and the between-sample coefficient of variation of hairiness (CVHb), is covered by the USTER STATISTICS. 36

37 High or low hairiness, even when going to the extremes, is not necessarily a quality deficiency. The yarn hairiness requirements are strictly governed by the end use. Yarns with higher hairiness are usually produced for end uses in knitting, such as underwear, knitted outerwear, and sportswear. Most weaving applications call for a smooth yarn surface, especially with warp yarns. A typical exception are pile yarns for terry fabrics, which often exhibit a high hairiness. Greater hairiness can also improve the filling insertion behavior (air friendliness) of certain yarns processed on high-speed air-jet weaving machines. One aspect that is not reflected in the USTER STATISTICS on yarn hairiness is the occurrence of periodic hairiness defects. While modern yarn monitoring systems detect mass periodicities with a high degree of accuracy and reliability, there is no on-line monitoring system for hairiness. Consequently, knowledge of the average hairiness of a yarn does not preclude the existence of periodic hairiness defects, which adversely affect fabric appearance. In some cases, a high standard deviation of hairiness is at least an indication of the presence of hairiness periodicities. Proper calibration of the instrument is a necessary prerequisite to make correct comparisons between the actual USTER TESTER 4 measurements and the USTER STATISTICS on yarn hairiness. The calibration of a USTER TESTER 4 hairiness module should be left to authorized Uster Technologies service personnel. Please contact the nearest Uster Technologies service station if unexpected changes or long-term drift should occur. TESTEX AG in Zurich, Switzerland, conducts yarn quality round tests on an international basis. Participation in such a program is highly recommended for closely monitoring the performance of the service personnel and of the instrument, i.e. the consistency of the measurements and the compatibility with other laboratories. This, of course, includes compatibility with the USTER STATISTICS as well. Further explanations of the individual functional elements of the hairiness module of the USTER TESTER 4, the significance of the measurements, and the proper calibration and operation of the module are given in the operating instructions and in the application handbook on hairiness testing. Adequate sample conditioning and maintaining constant standard atmospheric conditions in the laboratory during testing is important. Please refer to section of this appendix for more information on ambient laboratory conditions for yarn testing Imperfections Testing The USTER STATISTICS on imperfections include nomograms on the number of thick places, thin places, and neps per 1,000 m of yarn as determined with the USTER TESTER. The sensitivity settings for the detection of imperfections are 50% for thin places, +50% for thick places, and +200% for neps. As mentioned under 6.3, the next lower thresholds 40%, +35% and +140% have been included in USTER STATISTICS for the first time. These settings are commonly used for all yarn types except rotor-spun yarns. The structure of rotor-spun yarns is intrinsically different from that of conventional ring-spun yarns. Neps in rotor-spun yarns tend to be spun into the solid yarn body rather than remaining on the yarn surface, which is typical for ring-spun yarns. Although embedded in the yarn core, these neps still represent a short mass defect and they will therefore trigger the imperfection counter upon exceeding the preset threshold value. However, compared to neps that are attached to the yarn surface, fully embedded neps are barely perceptible for the human eye. In order to balance the typical visual appearance of rotor-spun yarns with the imperfection counts of the USTER TESTER, the +280% sensitivity setting for neps has become a common convention for the testing of rotor-spun yarns. In addition to the 280% neps, nep class +200% has been included for the first time as an additional nomogram for OE rotor-spun yarns and airjet yarns. A USTER TESTER 4 has been used for the testing of all yarn samples that have been procured for the USTER STATISTICS However, the STATISTICS on yarn imperfections are compatible with the data provided by the preceding product 37

38 generations, i.e. USTER TESTER 1, USTER TESTER 2, and USTER TESTER 3. Proper calibration of the instrument is a necessary prerequisite to make correct comparisons between the actual USTER TESTER measurements and the USTER STATISTICS on yarn imperfections. The calibration of a USTER TESTER should be left to authorized Uster Technologies service personnel. Please contact the nearest Uster Technologies service station if unexpected changes or long-term drift should occur. TESTEX AG in Zurich, Switzerland, conducts yarn quality round tests on an international basis. Participation in such a program is highly recommended for closely monitoring the performance of the service personnel and of the instrument, i.e. the consistency of the measurements and the compatibility with other laboratories. This, of course, includes compatibility with the USTER STATISTICS as well. Further explanations of the individual functional elements of the imperfection counter of the USTER TESTER, the significance of the measurements, and the proper calibration and operation of the instrument are given in the operating instructions and in the application handbook on evenness testing. Adequate sample conditioning and maintaining constant standard atmospheric conditions in the laboratory during testing is important. Please refer to section of this appendix for more information on ambient laboratory conditions for yarn testing Yarn Diameter, Cross-sectional Shape and Density Testing The USTER STATISTICS 2007 include the coefficient of variation of the yarn diameter, the cross-sectional shape and density. Increasing experience in using textile measuring instruments resulted in ever-growing demands on yarns and the appearance of woven and knitted fabrics. Time and again it was noticed that textile measuring sensors which have been known for a long time can explain a great deal, but there are still defects in textile formations which are difficult to interpret. Moreover, quality losses occur during process control which are invariably difficult to explain. Therefore, Uster Technologies decided some years ago to develop two more sensors in addition to the well-known sensors used to determine mass variation and the sensors used to analyze hairiness: Optical sensor to measure yarn diameter, cross-sectional shape of yarns, density and surface structure. Optical sensor to determine any remaining yarn trash and yarn dust. The optical sensor to measure the yarn diameter uses two light sources arranged at a 90 degree angle to examine the yarn. This arrangement guarantees a high stability of the measurement, and at the same time it is possible to measure the roundness of the yarns, since the roundness of yarns also influences the appearance of textile fabrics Yarn Trash and Yarn Dust Testing The sensor to determine yarn trash and yarn dust is used to detect remaining trash and dust in the yarn. It is therefore possible to monitor the reduction of the trash and dust content during the entire spinning process. Trash and dust contained in the yarn is of particular significance for processing yarns on weaving looms and knitting machines. The two quality characteristics, trash and dust in yarns, have also been included in the USTER STATISTICS

39 Twist Testing The twist of a yarn can be described by the twist per unit length (per meter or per inch) and by the twist multiplier. For the twist character of a yarn only the twist multiplier is decisive, as it describes the angle of the twist in the yarn. A fine yarn needs more twist than a coarse yarn in order to have the same twist character. Therefore, the twist of a yarn is usually given as the coefficient of twist, also called twist multiplier in order to be able to compare different yarn counts. The twist measuring method used is the untwist-retwist method. This method is based on the premise that the contraction of a specified length of singles yarns is the same for any amount of twist. A 50-cm length is untwisted under pretension, and then is retwisted in the same direction. The retwisting is continued until the contracted length is the same as the original specimen length. The total twist is the sum of the untwisted and retwisted turns. Since the specimen length is 0.5 m, the number of rotations with the untwist-retwist method is equivalent to the yarn twist per meter. The measurement of the twist for the USTER STATISTICS is done according to the standard ISO 17202: Tensile Properties Testing The USTER STATISTICS on tensile properties are valid for measurements performed with the USTER TENSORAPID single-end tensile testing instrument. Nomograms are available for breaking force (F H ), breaking tenacity (RH), breaking elongation (εh) and work-to-break (WH) as well as for the total coefficients of variation of each one of these parameters (CVRH, CVεH, CVWH). The total coefficient of variation describes the overall variability of a tested lot, i.e. the withinsample variation plus the between-sample variation. If 20 individual single-end tensile tests are performed on each of ten bobbins or packages in a sample lot, the total coefficient of variation is calculated from the pooled data of the total number of tests (200 in this example) that were carried out. The terminology used for describing the tensile properties may raise some questions. In the USTER STATISTICS, we have applied the same terminology that is used in the international standards on textile testing. However, these standardized denominations are not always clear. The following must be carefully considered: The breaking tenacity is calculated from the peak force which occurs anywhere between the beginning of the test and the final rupture of the specimen. The peak force or maximum force is not identical with the force measured at the very moment of rupture (force at rupture). The breaking elongation is calculated from the clamp displacement at the point of peak force. The elongation at peak force is not identical with the elongation at the very moment of rupture (elongation at rupture). The work-to-break is defined as the area below the stress/strain curve drawn to the point of peak force and the corresponding elongation at peak force. The work at the point of peak force is not identical with the work at the very moment of rupture (work-to-rupture). In the USTER STATISTICS on tensile properties, all parameters are derived from the true peak force measurement. However, as long as the stress/strain curve of a yarn exhibits a linear or progressive characteristic, these differences are irrelevant because the maximum force is very much the same as the force at the point of rupture. This is the case, for instance, with 100% cotton yarns. But: When the stress/strain curve shows a degressive characteristic, the peak force may be higher than the force at rupture and the elongation at peak force is lower than the elongation at rupture. This is the case with worsted yarns or yarns which are spun from certain man-made fibers. When comparing data on tensile yarn properties with the USTER STATISTICS, the true meaning of these measurements must be known. Some number which happens to be declared as yarn strength, for instance, must not necessarily be compatible with the USTER STATISTICS. The application handbook on tensile 39

40 testing with the USTER TENSORAPID is highly recommended to those who may wish to obtain further information on these topics. The USTER TENSORAPID applies the CRE principle of tensile testing. The term CRE serves as an abbreviation for constant rate of extension. CRE describes the simple fact that the moving clamp is displaced at a constant velocity. As a result, the specimen between the stationary and the moving clamp is extended by a constant distance per unit of time and the force required to do so is measured. The following details are of utmost importance in ensuring compatibility between the data presented in the USTER STATISTICS and the data on tensile properties obtained in practice: To be compatible, a measurement must be performed according to the CRE principle. The velocity of the moving clamp, also referred to as the testing speed, must be exactly 5 m/min. The gauge length, i.e. the length of the specimen or the distance between the stationary and the moving clamp should be 500 mm and a pretension of 0.5 cn/tex must be applied. Testing conditions that deviate from this description will most certainly result in different measurement values. CRE single-end testing at 5 m/min is the most widely accepted practice in the international textile industry and it has therefore been chosen as the testing mode for the USTER STATISTICS on tensile properties. However, other methods are still being applied but their significance is deteriorating rapidly. These methods include CRE single-end testing with 20 s time-to-break. Textile materials exhibit a partially viscoelastic behavior and their tensile properties change notably as a function of the time during which mechanical forces and deformations are acting upon a fiber, yarn, or fabric. Therefore, the tensile properties of yarns also change with the testing speed. The difference between a time-to-break of 20 s and the s required to break a specimen made of fiber-spun yarns at 5 m/min causes significant differences between the respective measurement values. Similar discrepancies may occur when comparing CRL (constant rate of load) single-end measurements from the USTER DYNAMAT with the CRE 5 m/min TENSORAPID data provided in the USTER STATISTICS. In general, there are two fundamental criteria which affect the compatibility between different measurements of tensile yarn properties: Criterion number one is the testing conditions, i.e. the testing principle (CRE, CRL), testing speed, gauge length, and pretensioning. The second criterion, which also affects the magnitude of the differences, relates to the specific stress/strain characteristic of the yarn itself, which is determined by the fibrous materials, the blend ratio, and the yarn construction. A detailed appraisal of the various tensile testing systems and the reasons for the differences between the measurements is provided in the application handbook on tensile testing with the USTER TENSORAPID. Proper calibration of the instrument is a necessary prerequisite to make correct comparisons between the actual USTER TENSORAPID measurements and the USTER STATISTICS on tensile properties. The calibration of a USTER TENSORAPID should be left to authorized Uster Technologies service personnel. Please contact the nearest Uster Technologies service station if unexpected changes or long-term drift should occur. TESTEX AG in Zurich, Switzerland, conducts yarn quality round tests on an international basis. Participation in such a program is highly recommended for closely monitoring the performance of the service personnel and of the instrument, i.e. the consistency of the measurements and the compatibility with other laboratories. This, of course, includes compatibility with the USTER STATISTICS as well. The determination of the CRE tensile properties of yarns by means of electronic yarn testing instruments is a standardized procedure and is described in detail in ISO However: While the basic procedures of automatic CRE single-end tensile testing are outlined in all applicable national and international standards, the testing speed of 5 m/min much to our regret has not yet been considered. In spite of this shortcoming, it is definitely the preferred mode of tensile testing from a global point of view. Further explanations of the individual functional elements of the USTER TENSORAPID, the significance of the measurements, and the proper calibration and operation of the instrument are given in the operating instructions and in the 40

41 application handbook on tensile testing. Adequate sample conditioning and maintaining constant standard atmospheric conditions in the laboratory during testing is important. Please refer to section of this appendix for more information on ambient laboratory conditions for yarn testing. References to tensile testing standards: ISO 2062, ASTM D-1578, DIN : Single-end tensile testing HV Tensile Properties Testing The term HV tensile properties is used for describing a novel method of tensile testing. HV stands for high-volume and high-velocity. The USTER TENSOJET is a laboratory instrument which for the first time provides true high-volume and highvelocity features in tensile testing. With the USTER TENSOJET, the mechanism which is used for applying a tensile force, to extend, and ultimately break a specimen consists of two pairs of cam-type rollers, arranged at a distance of 500 mm. The top and bottom cam-type rollers are designed to allow an end to be inserted between the rollers, to be clamped at the nip point, and to be extended just a fraction of a second later. A force sensor is installed in the yarn channel which connects the two pairs of rollers. The curvature of the yarn channel causes a flat angle deflection of the yarn at the tip of the sensor so that the radial component of the tensile force can be measured. The entire measurement cycle consists of four phases: continuous yarn take-up and intermediate storage, insertion of the end by a compressed air nozzle, clamping and extension to rupture by the rollers, and removal of the broken end into the waste bin via an air flow. The USTER TENSOJET operates according to the CRE principle at a testing speed of 400 m/ min. The actual time-to-break is in the neighborhood of 3 ms for a 100% cotton yarn. As a result, the instrument is capable of performing 30,000 individual breaks per hour and offers the possibility of testing an enormous amount of yarn within a very reasonable time frame. Such dramatic increases in sample size provide a suitable means for the detection and assessment of sporadic weak places in the yarn, which dictate the yarn breakage frequency and machine efficiencies in subsequent processing. High-performance tensile testing with the USTER TENSOJET is also an almost perfect simulation of the dynamic loads which affect a yarn during filling insertion on high-speed weaving machines. In the USTER STATISTICS on HV tensile properties, nomograms are available for breaking force (F H ), breaking tenacity (RH), breaking elongation (εh), and workto-break (WH) as well as for the total coefficients of variation of these parameters (CV R H, CVεH, CVWH). In general terms, the TENSOJET measurements correspond to those provided in the USTER STATISTICS on tensile properties as determined with the USTER TENSORAPID and the previous paragraph can be referred to for more detailed explanations. However, due to the significant difference in testing speed, TENSOJET compared to TENSORAPID measurements show generally higher force values. The nomograms on the percentile values of breaking force (F P=0.1 ) and breaking elongation (εp=0.1) relate to the occurrence of weak places in spun yarns. The percentile value 0.1% of the breaking force (FP=0.1) signifies that 0.1% of all measurements exhibit a breaking force that is equal to or lower than the specified value. For the USTER STATISTICS, ten samples of each lot have been selected and 1,000 individual tensile tests have been performed on each bobbin or package. This is a total of 10,000 measurements per lot. The percentile value 0.1% of the breaking force indicates that ten measurements (0.1% of 10,000 breaks) lie below that value. An example: The percentile value 0.1% of the breaking force of an Ne 20 (Nm 34, 29.5 tex), 100% carded cotton ring-spun yarn was measured at FP=0.1 = 400 cn, which can be converted into RP=0.1 = 13.6 cn/tex. Consequently, 0.1% of all measurements represent weak places with a breaking force of less than 400 cn or a breaking tenacity of less than 13.6 cn/tex. If ten bobbins have been tested, each with 1,000 breaks, this equates to a total of ten such weak places. The percentile 41

42 value 0.1% of the breaking force FP=0.1 = 400 cn corresponds to the 50 th percentile of the USTER STATISTICS. In this context, it is very important to keep in mind that a comparison with the USTER STATISTICS on weak places is only permissible if the total number of breaks performed on a sample lot is exactly 10,000. Percentile values of both the breaking force and the breaking elongation that have been determined with fewer or more than 10,000 breaks cannot be compared with the data provided in the USTER STATISTICS. Proper calibration of the instrument is a necessary prerequisite to make correct comparisons between the actual USTER TENSOJET measurements and the USTER STATISTICS on HV tensile properties. The calibration of a USTER TENSOJET should be left to authorized Uster Technologies service personnel. Please contact the nearest Uster Technologies service station if unexpected changes or long-term drift should occur. TESTEX AG in Zurich, Switzerland, conducts yarn quality round tests on an international basis. Participation in such a program is highly recommended for closely monitoring the performance of the service personnel and of the instrument, i.e. the consistency of the measurements and the compatibility with other laboratories. This, of course, includes compatibility with the USTER STATISTICS as well. Further explanations of the individual elements of the USTER TENSOJET, the significance of the measurements, and the proper calibration and operation of the instrument are given in the operating instructions. Adequate sample conditioning and maintaining constant standard atmospheric conditions in the laboratory during testing is important. Please refer to section of this appendix for more information on ambient laboratory conditions for yarn testing Ambient Laboratory Conditions for Yarn Testing Some textile fibers are highly hygroscopic and their properties change notably as a function of the moisture content. Typical hygroscopic fibers are cotton, wool, rayon, silk, flax, etc. Moisture content is particularly critical in the case of dynamometric properties, i.e. yarn tenacity, elongation, and work-to-break, but yarn evenness, imperfections, and defect levels are also affected. As a result, conditioning and testing must be carried out under constant standard atmospheric conditions. The standard temperate atmosphere for textile testing involves a temperature of 20±2 C (68±4 F) and 65±2 % relative humidity. In tropical regions, maintaining a temperature of 27±2 C (81±4 F) at 65±2% relative humidity is legitimate, but then the absolute moisture content of the conditioned air is different. Modern air conditioning systems, however, are capable of achieving 20±2 C (68±4 F) and 65±2 % relative humidity in most any location in the world and in the interest of international harmonization, these ambient conditions should be realized whenever possible. Prior to testing, the samples must be conditioned under constant standard atmospheric conditions until in moisture equilibrium with the surrounding air. To attain the moisture equilibrium, a conditioning time of at least 24 hours is required, 48 hours is preferred. For samples with a high moisture content (thermally conditioned yarns), conditioning time should be at least 48 hours. The best practice is to precondition such samples in a dry atmosphere, so that the moisture equilibrium is later approached from the dry side. During conditioning, the samples must be removed from any boxes or containers used for transportation, cleared from all packing material, placed in an upright position to expose the entire bobbin or package surface to the conditioned air, and arranged in such a fashion that ample space is left between the samples to allow conditioned air to circulate freely. Laboratory conditions should be monitored by appropriate devices that record both short-term fluctuation and long-term drift. References to standards defining the standard atmosphere for conditioning and testing: ISO 139, EN , DIN : Standard atmosphere for conditioning and testing 42

43 10.5 Useful Conversions English/Metric Conversions English Unit Abbreviation Metric Unit Metric Unit Abbreviation English Unit (US) (US) Length Length inch in 2.54 cm centimeter cm in foot (=12 in) ft cm meter m 3.28 ft yard (=3 ft) yd m meter m.0936 yd mile mile m kilometer km mile Area Area square inch in cm 2 square centimeter cm in 2 square foot ft cm 2 square meter m ft 2 square yard yd m 2 square meter m yd 2 acre ac ha hectare ha 2.47 ac square mile mile m 2 square kilometer km mile 2 Volume Volume cubic inch in cm 3 cubic centimeter cm in 3 cubic foot ft m 3 cubic meter m ft 3 cubic yard yd m 3 cubic meter m yd 3 fluid ounce fl oz 28.4 ml milliliter ml fl oz pint pt l liter l 2.11 pt gallon gal 3.79 l liter l gal Mass Mass grain gr g gram g gr ounce oz g gram g oz pound lb kg kilogram kg lb Force Force gram-force gf cn centi-newton cn.02 gf pound-force lbf N Newton N lbf Pressure Pressure pound-force/in 2 p.s.i Pa bar (=10 5 Pa) bar 4.5 p.s.i. pound-force/ft 2 p.s.f Pa Pascal (N/m 2 ) Pa p.s.f. Tenacity Tenacity gram-force/den gf/den cn/tex centi-newton/tex cn/tex gf/den gram-force/tex gf/tex cn/tex centi-newton/tex cn/tex.02 gf/tex 43

44 Count Conversions tex = dtex = tex 10 den = tex 9 dtex 0.9 Nm = Ne C = Ne W = Ne L = grains/yd = tex dtex den Nm Ne C Ne W Ne L grains/yd dtex den Nm Ne C Ne W Ne L den Nm Ne C Ne W Ne L Nm Ne C Ne W Ne L Ne C Ne W 1.13 Ne L tex dtex den gr/yd Ne W Ne L 8.33 tex dtex den Nm gr/yd Ne L 12.5 Nm Ne tex dtex den C gr/yd Nm Ne tex dtex den C 2.8 Ne W 1.87 gr/yd tex tex den Nm Ne C Ne W Ne L gr/yd gr/yd gr/yd Nm = metric count Ne C = cotton count Ne W = worsted count Ne L = linen count Staple Conversion Chart Special Conversions Category inches 32nds decimals mm short 13 / / / / / medium 31 / / / / medium to long 1 1 / / / / / Rkm = cn/tex cn/tex = Rkm Twist Multiplier α e = α m Twist Multiplier α m = α e Turns per inch t.p.i. = T/m Turns per meter T/m = t.p.i. Fahrenheit F = 1.8 ( C+32) Centigrade C = ( F 32) long 1 9 / / / / / extra long 1 7 / / / / / / /

45 USTER STATISTICS for Yarns Made Out of Man-Made Cellulosic Fibers Introduction The most recent edition of the USTER STATISTICS was published in This edition was the most substantial compilation of benchmarks for the textile industry in the history of the USTER STATISTICS which goes back more than 50 years. Additional yarn parameters, the relationship between fiber and yarn data as well as the new fiber parameters were presented in the USTER STATISTICS We have come to realise in recent years that the chapters of the USTER STATISTICS for man-made cellulosic fibers would have to be radically revised in view of our focus to continuously adjust the USTER STATISTICS to the requirements of the textile industry. This conclusion can be attributed to the rapid developments made in the cellulose production on the one hand, and to the diversification of cellulose fibers in various products with different characteristics on the other hand. The market share of man-made cellulose amounted to 5% of the global fiber production in the year Cellulosics Filament 1% Synthetics Staple 22% Cellulosics Staple 4% Cotton 36% Synthetics Filament 35% Wool 2% Fig. 1 Global production, fibers and filament yarns, a total of 74 million tons [The International Rayon & Synthetic Fibers Committee, The growth seen in man-made cellulose fibers in recent years is particularly impressive. Production of these fibers grew by 9% from 2005 to 2007, which can be attributed primarily to the increase in staple fibers. Copyright 2009 Uster Technologies AG 1'000 tons Fig. 2 Cellulosic Fiber Production (Staple) [Oerlikon Textile, The Fiber Year 2007/2008]

46 Uster Technologies has decided to break down the different product groups as a result of the economic developments in man-made cellulose fibers and their diversification. The present USTER STATISTICS for man-made cellulosic fibers have been divided into the following chapters: 100% viscose, ring-spun, bobbin and cone 100% modal, ring-spun, bobbin and cone 100% micromodal, ring-spun yarn, bobbin and cone Various blends of cotton and modal, bobbin and cone 100% lyocell, ring-spun yarn, bobbin and cone Various polyester/viscose blends, ring-spun yarn, bobbin and cone 100% viscose, OE-rotor yarn, cone 100% viscose, airjet-spun yarn, cone 100% micromodal, airjet-spun yarn, cone This division reflects the fact that the different cellulosic materials have varying characteristics and therefore, have to be treated separately. The samples were requested specially for the USTER STATISTICS and were collected globally. They were then tested in the technology centers in Uster, Switzerland, and in Suzhou, China. The distribution of the origin of the samples is illustrated in the following graph: Asia Pacific 42% Africa 4% Near & Middle East 15% Western & Eastern Europe 39% Fig. 3 Distribution of sample origin [data base USTER STATISTICS 2007 Version 2.0] The USTER STATISTICS 2007 Version 2.0 replaces all chapters of the USTER STATISTICS 2007 Version 1.0 where the raw material is either viscose or viscose blends. These chapters become void and will be replaced by the USTER STATISTICS 2007 Version 2.0. We would like to take the opportunity to thank all customers for having made available their yarns which enabled us to compile the benchmarks at hand. We would also like to extend our thanks to our colleagues from Marketing and Textile Technology who also contributed to the success of the USTER STATISTICS 2007 Version 2.0. Copyright 2009 Uster Technologies AG 2