RING SPINNING VARIABLES - EGYPTIAN COTTON

OPTIMIZING RING SPINNING VARIABLES AND A PROPOSED PROCEDURE TO
DETERMINE THE EGYPTIAN COTTON SPINNING POTENTIAL
EL-SAYED M. A. M.
negmmohamed@yahoo.com
Head of Spinning Research Dept.
Cotton Research Institute,
Agricultural Research Center,
Giza, Egypt
ABSTRACT
In this study, many approaches were examined such as spindle defects and yarn bobbin position along with successively varying spindle speed to select the optimum processing parameters for standard testing of the Egyptian cotton, and hence suggesting a spinning procedure for the CRI 96-spindle-hour spinning test. Giza 80 was used to test the spindle error and yarn bobbin position also, to study the varying spindle speed, while, Giza 80 as well as Giza 86 and Giza 70 were used to reveal the spinning limit technique.
The coefficient of variation in lea count strength product (introduced between the spindles of the ring frame) was considerable, the variance was very small (1.01 %) in extreme cases and could be neglected. The lea count strength product at different positions on the bobbin spun on the ring frame between the pigtail to full bobbin was insignificant. The increase in spindle speed from 1000 to 17500 rpm did not affect single yarn strength, yarn evenness and yarn hairiness. The total imperfections are at 10,000 rpm minimum of spindle, and beyond this speed the imperfections increase gradually with the increase in spindle speed.
The proposed procedure of accelerated spinning technique appears promising in indicating the relative level of end breakage and optimum yarn quality parameters for different cotton varieties. A series of 96- spindle-hour spinning tests proved to be reliable in exploring practical spinning limits of any cotton to find out the finest count for a particular cotton; taking into consideration ends-down and yarn quality parameters.
Keywords: Egyptian cotton, cotton spinning, bobbins

INTRODUCTION
As a result of the technological advances in spinning industry, The Cotton Research Institute, in its effort to continuously improve the Egyptian cotton competitiveness in the world markets has modernized the experimental spinning mill. It was established in 1935 and expanded in 1965, and is running according to a system using very small samples of lint (60 grams). A completely new spinning mill working under a semi-industrial condition using a
bulk sample of lint (5 Kg minimum) has been added more recently (2006).
A standard testing system is required to make the best use of the new machinery. To define the new system, several spinning variables, especially spindle speed and spindle defects, yarn bobbin position and spinning potential.
The effect of spindle speed on yarn properties was observed by many workers, Anbarasan (1996) reported that the benefit available with the advanced speed system was subsequently extended future with the introduction of variable speed system such as inverter drive system. This system offers the possibility of arranging a selective and continuous speed adjustment for the complete cop build. In this way, optimum conditions of spindle speed can be obtained such that, throughout the cop build, a practically constant spinning tension is available. Chaudhuri (2003) in his work on acrylic spun yarn observed that, increase of spindle speed results in the increase of yarn tenacity, initial modulus, work of rupture, packing coefficient and total imperfections up to spindle speed of 18000 rpm whereas mass irregularity remains unchanged. Hairiness Index does not show any relationship with the increase in spindle speed. Nasir et al. (2004) and Shamuganandam et al (2005) indicated that the spindle speed is the most important parameter deciding the ring frame production per spindle. From quality point of view, it was observed that lower spindle speed was better for yarn quality parameters viz. yarn count, yarn lea strength. From production point of view higher spindle speed was the best but it deteriorates yarn quality. The three key factors which determine spindle speeds are the technological capability of ring frame, end breakage rate and yarn quality.
The spinning performance of cotton is evaluated mainly by its rate of end breakage per 1000 spindle hours. For a valid evaluation of cotton, experience has shown that a minimum of 25000 spindle-hour mill scale test, the conventional 5000 spindle-hour pilot plant scale test, the SRRL "Southern Regional Research Laboratory" 720 spindle-hour scale spinning performance test and the 84 spindle-hour small laboratory scale spinning performance are needed, (ASTM 1991). These many spindle hours need much material and time, and necessarily limit the extent of the possible evaluations. As a result, research laboratories find it difficult to conduct such types of "spinnability" tests routinely, since experimental samples are generally small and processing equipment is limited, (Louis 1961). In Cotton Research Institute "CRI", increase emphasis are placed on comparing the new promising varieties with commercial ones and evaluate the new hybrid in isolated filed. Thus it appears that there is a real need for a procedure to rapidly evaluate the spinning performance in terms of yarn quality and end breakage rate.
Through several investigations, different studies to determine the spinning potential yarn number or spinning limit by proposed approaches depend on; a) use of accelerated tests by increasing the yarn tension or reducing its twist during the spinning trails; b) measurement of the "spinning end strength", which was defined as the maximum stress sustained by the yarn during the end-breakage sequence; and c) using neural network based on the fiber and machine interaction, (Krifa and Ethridge 2004).
Rouse (1965) proposed an equation for predicting the spinning potential yarn number "SPY."
The equation used to compute the SPY is given as follows:
SPY = 2(Na) - (Nn) - 0.2B
= Na - e - 0.2B
Where;
SPY: Spinning potential yarn number (expressed as English yarn count, Ne)
Na: Actual yarn count
Nn: Nominal yarn count
B: Number of spindles with end breakage e: Nn — Na: error in actual yarn count
The formula was criticized by Zhu and Ethridge (1996) as follows;
1. Neither the formal nor the informal record on development and application of the ring SPY test contains explanation or justification of the term -0.2B in the equation. Since there is no theoretical justification, it must be surmised that it was determined by empirical testing done during the 1950's. Therefore, prudence would demand that its empirical validity be verified on modern ring spinning frames.

2. It is also not explained in the literature why the actual yarn count (Na) is doubled while the nominal yarn count (Nn) is not. The second line of the equation was added to indicate that the formulation results in an adjustment for the failure to always spin the exact yarn count targeted in the test procedure.
It could be added that the range of 4 to 20 end breakages is an absolute number i.e. number of end breakages for coarse counts "up to 24 Ne," were even with the same range of the extra fme counts "up to 160 Ne." in this respect, Ratnam and Chellamani (1999) decided that in ring spinning, the norms for end breaks per 100 spindle hours for a good working are: 25 in 20s and 30s, 16 in 40s, 12 in 60s, 80s and finer counts.
In this study, for a rapid spinning technique, many approaches were examined such as (a) spindle defects and yarn bobbin position; (b) successively varying spindle speed to select of optimum process parameters for standard testing of the Egyptian cotton, and (c) suggesting a spinning procedure for the CRI 96-spindle­hour spinning test.
MATERIALS AND METHODS
Giza 80 was spun at 40s carded yarn to test the spindle error and yarn bobbin position and also, to study the varying spindle speeds, while, Giza 80 as well as Giza 86 and Giza 70, were spun into successive fine carded yarn counts 40, 50 and 60s for Giza 80, while Giza 86 and Giza 70 were spun into 70, 80, 90 and 100's carded counts to reveal the spinning limit technique. Data on the properties of the cotton varieties are illustrated in Table 1.
Yarn Preparation
The new spinning machinery
included: Compact Bale Opener "BO-C"; compact Opener "TO-C" with needle beater fitted with Chute feed and "DK-780" carding machine working with short and long term Auto leveler; HSR 1000 draw-frame machine, working with short and long term Auto leveler. Marzoli, High-speed frame "PCX 16-A 36 spindles; Marzoli, RST1 ring and compact spinning" Olfil System" of one frame consisting of 96 spindles, was used sequentially for the preparation of the samples. Six different samples of yarns having nominal linear density of 14.8 tex (40 Ne) with ae 4.0 were prepared by varying spindle speeds from 10 000 rpm to 18 000 rpm.

End breakage
96 hours runs were made for each yarn count and the number of end breakages was recorded at 30-minute intervals during which all broken ends were pieced up. According to Louis (1961) end breakage data were sorted into two categories, one is based on the initial end breakages and the other is based on the initial and repeated end breakages, thus giving justification for not piecing the end after breakage. Furthermore, another advantage of this method is that it avoids the danger of counting repeated breakages caused by mechanical defects.
Tensile testing
Statimat ME with a testing speed of 5000 mm/min with a test length of 50 cm was used for the testing of tensile properties. An average of 120 tests for breaking load and elongation value was taken for the calculation of tenacity and breaking extension of the samples. Lea product (lea count strength product) was measured by using the Good-Brand Lea Tester.
Evenness, imperfections and hairiness testing
The Uster Evenness Tester (UT-3) was used for testing yarn evenness, number of imperfections and hairiness index with a testing speed of 400 m/min for a period of one minute. Average of three tests was taken for final results.
RESULTS AND DISCUSSION
Spindle defect
In order to study the "spindle defects" i.e. the inherent variability between machine spindles, the ring frame was divided into different six parts of the spindles. Giza 80 samples were spun on each of the 96 spindles for the machine giving 24 lea count strength per spindle/sample as shown in Table 2. The experiment revealed that the coefficient of variation in lea strength (introduced between the spindles of the ring frame) were considerable, and a C.V. % was very small (1.01 %) in extreme cases and could be neglected.
Yarn bobbin position
The first problem was to decide the position at which yarn should be spun and tested on the bobbin. With the aid of a Good-Brand Lea Tester, it was found that the lea count strength product at different positions on the bobbin spun on a frame between the pigtail to full bobbin showed insignificant differences, (Table 2). The concept of continuous development of ring spinning technology, is that the inverter drive controls and provides constancy of the yarn tension along the bobbin by smoothness of transition from the slow speed to the maximum speed at every phase of bobbin build up during start-up and vise versa during the end of the bobbin build. The following speed can be modified during the bobbin build up, according to Marzoli, RST1 report (2001):

Effect of spindle speed on end breaks
A major factor which limits the maximum spindle speed is the end breakage rate. An end break occurs whenever the spinning tension exceeds the yarn breaking force. End breakage rates of yarn produced from Giza 80 with various spindle speeds is given in Table 3. The data showed no effect of spindle speed on end breakage of 100 spindle/hour. Considering the above aspects, a clear understanding of the yam tension condition prevailing during a bobbin build up becomes necessary in any attempt to increase the spindle speed by reducing the end breakage rate.
With inverter motor drives, end breaks are fewer by about 30 percent at the beginning of the doff compared to constant drive motors. End breaks are usually more at the bobbin bottom stage and so, inverter motor drives help in reducing the work load of the tension at the beginning of the doff, (Ratnam and Chellamani 1999).

Effect of spindle speed on yarn tenacity and elongation
The statistical analysis of variance supporting by least significant difference of the data pertaining to yarn lea strength is given in Table 3. While increasing spindle speeds, all possible care should be taken to ensure that yarn quality is not affected. With the increase in spindle speed, there is no appreciable change in yarn tenacity and elongation. The data show that there is small change of yarn tenacity and elongation with the change of spindle speed from 10000 up to 17500 rpm., meaning that the differences in yarn tenacity and elongation are marginal. This result is basically due to the constancy of the yarn tension along the bobbin build. This finding is not supported by Chaudhuri (2003), who stated that, at higher spindle speed, packing coefficient is higher resulting higher compactness. Higher the compactness of the yarn structure better is the fiber migration within the yarn and hence higher is the interlocking structure of fibers within the yarn. As a result yarn strength rises with the increase in spindle speed of the ring frame.
Effect of spindle speed on yarn unevenness and hairiness index
The mean values pertaining to yarn unevenness under different levels of spindle speed are tabulated in Table 3. There is an appreciable change in unevenness and hairiness index value of the yarns according to the increase in spindle speed. The data show that there is significant increase of yarn unevenness with the increase in of spindle speed, while there is a slight increase in yarn hairiness index. The reason may be due to a high centrifugal force acting on the yarn which gives more outward force of the tail end of the fiber causing formation of more protruding ends and irregularity on the yarn surface Chaudhuri (2003).
Effect of spindle speed on yarn imperfections
The mean values of yarn imperfections are given in Table 3. It is observed that the total imperfections is minimum at 10000 rpm of the ring frame spindle for the cotton variety under study, and beyond this speed the imperfections increases gradually with the increase in spindle speed. This finding was supported by Chaudhuri (2003) who reported that at higher spindle speed, the drafting force becomes higher. So, at the higher drafting force the average fiber tension at the front roller will cause an increase in the dragging out of the sliver into the front roller-nip. This dragging out of un-drafted sliver into the nip of the front roller and the subsequent retreat under the action of internal elastic force would cause an increase in the irregularity and imperfections that would offset the randomization effect of the speed.
A proposed spinning procedure for the CRI 96 spindle-hour spinning test
Confidence limits and degree of precision are calculated as follows;
It could be seen from Table 4, that the degree of precision decreased markedly when total number of spindles were increased from 16 to 96. The differences between the degrees of precision for the same number of spindles are ascribed to the real differences between fiber properties of the cotton varieties "Giza 80, Giza 86 and Giza 70". Figure 2 illustrated the potential spinning of the three cotton varieties using the number of end breakage rates within the control limits of 16 "for Giza 80" to 12 "for Giza 86 and Giza 70."



After many experimental trials, the following test procedure was developed starting with 40s for LS Upper Egypt cottons, 50s for LS Delta cottons and 70s for
1. Frame specification:
96 spindles with pendulum arm 45 mm diameter ring
10,000 — 18,000 rpm spindle speed range.
ELS cottons, but it can be easily adapted to evaluate the spinning performance of any cotton and yarn numbers.
2. Spinning work reported in this
investigation was done on 16 spindles.
Spinning duration was 6 hours per run.
3. Use about 50 Kg of cotton, based on
average 3 Kg per roving bobbin.
4. Select a yarn count that is estimated
to be the spinning limit, and set up the spinning frame.
5. Use a constant 14000 spindle speed
with appropriate traveler and twist multiplier according to ASTM, D­2811, (1991).
6. For LS Egyptian cotton, the tests
were started at initial medium yarn count of 40 Ne, while ELS cotton, started at fine carded yarn count of 70 Ne and 100 Ne for combed yarns.
7. For this test, spin all the 16 bobbins
for 6 hours. In this respect, six different cotton varieties in the same cotton category can be spun.
8. After sufficient time of running, size
all the 16 bobbins for the actual yarn
count and set up the machine for the target yarn count.
9. Use the end breakage rates within
the control limits of 25 and 12, according to yarn count, Ratnam and chellamani (1999).
10. Spin the twelve 30- minute intervals and sum up the data, Table 5.
11. The frame should be doffed after each yarn count to test yarn quality parameters, hence each run will start with empty bobbins.
12. After the first yarn count has been run, set up the frame for another yarn count and follow a similar procedure for progressive finer yarn count by increasing yarn count in increments of 5 units.

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Compare Blowroom

Comparative Performance Analysis of Blowroom Cleaning Machinery for Cotton
Fibre Length Characteristics
The effect of beater speed, grid bar setting and cotton trash percentage upon Uniclean (B 11) and Giant cleaner setup were studied for quality characteristics of cotton. The results in respect of fibre length and uniformity ratio showed highly significant differences in the mean values for different combination of settings as well as cleaning segments. Uniclean exert swift gentle but firm action of less stress on fibres whereas the action of Giant cleaner is very aggressive and severe during its cleaning action, which is detrimental to fibre staple.
Key words: Uniclean, Blowroom, Cotton Fibre Length, span length, Uniformity Ratio
Introduction
The cotton textile industry enjoys a highly significant position in the economy of Pakistan. For today's rapidly advancing textile industry and quality conscious international market, the comprehensive information about the characteristics of lint cotton, which is the raw material of the industry is a dire need for producing quality goods at competitive costs by way of reducing wastage and improving productivity level.
Since mechanized spinning industry came into being various opening and cleaning machines were developed most of which are now obsolete. With the passage of time and with the advent of new technologies high-speed machines were designed having more opening and cleaning efficiency. In the past a typical blow room line for the cleaning of cotton consists of four to six, and in some cases even seven beating points. The underlying idea was to open and clean the material slowly and gradually. But during the last decade, the trend has shifted to minimize the number of machines in the blow room line. Now in modern cleaning line only two to three beating points are available. This became possible only due to the introduction of machines with higher degree of opening capabilities.
Most of the spinning mills in Pakistan are equipped with conventional cleaning set-up in blow room. Step or Giant cleaner for example is used for excellence in opening and cleaning of cotton through the combination of the action of opposing spikes and the beating action. In this machine, the material falls into the feed hopper and passes to the first beater. From there, it is transported upwards by six beating rollers, each carrying profiled bars, the beaters are arranged on a line inclined upwards at 45°. The elimination of impurities takes place during the continual passage of the material over the grid arranged under the rollers. The grids are always adjustable and usually the beater speed is also adjustable. In Giant cleaner, progressive increase
in speed results in a directly proportional increase in waste extraction. The proportions of lint and trash in the dropping are independent of speed up to about 550 rev/min, so that a much greater cleaning efficiency is achieved at these higher speeds. At speed greater than 550 rev/min, however the lint loss is much greater as compared to the trash extraction.
Some reports are available regarding the effect of cleaning machinery upon fibre characteristics. Behery (1992) narrated that opening and cleaning machines removes short fibres and effect the change in fibre length due to fibre/machine interaction, whereas Schneider (1995) advocated that the Rieter Uniclean performs three main functions equally well viz; efficient cleaning at the start of the blow room lines, integration of an efficient dedusting elements and exceptionally gentle treatments of fibres. Similarly Klein (2000) lamented that Uniclean leads to a higher degree of cleaning, a better cleaning efficiency, and less stress on the fibres. Also Liu et al. (2001) commented as the large variation of single fibre properties within a single variety suggests a very strong influence of growth conditions and development.
Materials and Methods
The present research was initiated in the Department of Fibre Technology, University of Agriculture, Faisalabad and conducted at Resham Textile Industries Limited Pattoki District Kasoor during the year 2002. The details of the material used and methods applied to test the raw material and to measure various quality characteristics are briefly described here under.
Material Used
Lint cotton samples with different level of trash was collected from running material at M/S Resham Textile Industries Limited, cotton samples were subjected to the physical testing.
Spinning Process
Lint cotton with different levels of trash was processed at Trutzschler blow room line with and without Reiter Uniclean set-up, and following mechanical changes were undertaken at Uniclean as well as Giant cleaner in blow room.
After every possible combination of above variables at Uniclean as well as Giant cleaner, samples from the duct were collected and tested for the basic fibre characteristics along with the quality evaluation tests for staple length and uniformity ratio.


Atmospheric Conditions
The testing work was carried out under the standard laboratory conditions, which were maintained at 65+2% relative humidity and 20±2°C temperature.
Statistical Analysis
Four Factor Factorial Completely Randomized Design was applied in the analysis of variance for testing differences among various quality characters studied in this investigation. Duncan's Multiple Range Test was also applied for individual comparison of means among various quality characteristics as suggested by Steel and Torrie (1980). The data thus obtained was subjected to statistical manipulation on computer employing M-Stat micro computer program as devised by Freed (1992).
Results and Discussion

Span Length
The statistical analysis of variance regarding to span length of cotton for different settings at Uniclean as well as Giant cleaner in blow room is given in Table 1. The effects of Machines (M) and Beater Speed (5) are found highly significant. However the effects of trash percentage in cotton upon span length and of interactions are non-significant.
The comparison of individual mean values for machines in blow room on fibre span length is presented in Table la. Which indicated that the highest fibre span length of value 27.48 millimeter is obtained for Uniclean (M1) and the lowest value of staple length 27.43 mm is obtained for Giant cleaner (M2). Hence these machines differ significantly for their action upon cotton. On the basis of above results, it is crystal clear that Uniclean exert swift gentle but firm action of less stress on fibres whereas the action of Giant cleaner is very aggressive and severe during its cleaning action which is detrimental to fibre staple. Similarly views were put forth by Klein (2000) who lamented that Uniclean leads to a higher degree of cleaning, a better cleaning efficiency, and less stress on the fibres. Identical observation were presented by Schneider (1995) who advocated that the Rieter Uniclean performs three main functions equally well viz; efficient cleaning at the start of the blow room lines, integration of an efficient dedusting elements and exceptionally gentle treatments of fibres. Hence it can be very well visualized from the present research of that the cleaning action Uniclean is exceptionally smart and safe, less injurious to fibre for fibre cleaning operation in comparison with/to Giant cleaner.
As regards to the trash percentage the comparison of individual means revealed that best value of staple length (27.47 mm) is recorded at T1 followed by T 2and T 3with their respective means as 27.45 and 27.44 mm and these values are at par. The above results indicate that trash record independent effect upon staple length. Some previous researchers indicated that mill cleaning opens the cotton to small tuft size and extract as much trash as possible before the cotton goes to card and proper cleaning protects the staple length (Bel et al., 1991).
Duncan's multiple range test for individual comparison of mean values reveals, that beater speed, starting from B1 (480 rpm) till B, (960 rpm) recorded highly significant difference in their mean values. At 134 (629 rpm) maximum value of fibre length is observed followed by B3, B5, B6, B2, B7, BE and B1, respective mean for staple being 27.50, 27.49, 27.48, 27.46, 27.44, 27.44,27.42 and
27.41 millimeter. The above results express that for too high or too low beater speeds, the corresponding fibre length decreases, while the moderate speed 134 (629 rpm) recorded best results. The present research findings get full confirmation from the work of lqbal (2002) who concluded that fibre length decreased both at too low and too high beater speeds.
As regard to grid bar settings, best mean value of fibre length is recorded at (G5) followed by G4, G3, G2 and G1 with their respective mean values of length as 27.47, 27.46, 27.46, 27.45 and 27.44 millimeter. These values indicate nill effect of grid bar settings upon fibre length. Similarly previous researcher Maqsood (2000) postulated that grid bar settings at scutcher has a non-significant effect on fibre length. Whereas Behery (1992) advanced this statement that opening and cleaning machines removes short fibres and effect the change in fibre length due to fibre/machine interaction. From the above all results it can be inferred that grid bar opening angle has no effect upon the staple of cotton because it only facilitate the drain of non-lint elements.

Length Uniformity Ratio
The statistical analysis of variance regarding to length uniformity ratio of cotton for different settings at Uniclean as well as Giant cleaner in blow room is given in Table 2a, which indicate that the effects of Machines (M), Beater Speed (5) and Grid bar settings (G) are highly significant whereas the effect of trash percentage in cotton and all interactions are non-significant.
The comparison of individual mean values for machines in blow room on length uniformity ratio is presented in Table 2b. Which indicate that maximum length uniformity ratio of 47.49 percent is obtained for Uniclean (M1) and the lowest value of 47.17 percent is obtained for Giant cleaner (M2). Hence these machines significantly differ from one another. From the above discussion it is evident that the performance of Uniclean is for better then Giant cleaner. Similar views were put forth by Schneider (1995) who mentioned that the Reiter Uniclean performs three main functions equally well viz efficient cleaning at the start of the blow room lines, integration of an efficient dedusting elements and exceptionally gentle treatments of fibres. Similarly Anonymous (2000) argued that the Uniclean B„ is a machine for cleaning and extracting for cotton of any origin. Impurities are removed gently and effectively. The raw material is feed through without nipping. Hence it can be very well visualized from the present research, that cleaning action of Uni-clean is exceptionally smart and safe, less injurious to fibre for fibre cleaning operation in comparison with Giant cleaner.
The individual comparison for trash percentage recorded non-significant differences in their mean values. Maximum value of length uniformity ratio is recorded at T, followed by T2 and T3 with their respective mean values as 47.42, 47.32 and 47.36 percent. The above results indicate that trash in cotton does not record any significant effect upon length uniformity ratio. Previous researcher agreed that cotton yarn irregularity was considerably influenced by the properties of fibre from which uniformity was the most important property Ramey and Beaton (1989).
The individual comparison of means values reveals that various beater speeds starting from B, (480 rpm) till B, (960 rpm) recorded highly significant differences in their mean values. At 134 (629 rpm) maximum value of length uniformity is observed followed by B3, B5, B2, Bo B1, B7 and B8 with their respective means being 47.64, 47.59, 47.48, 47.36, 47.28, 47.19, 47.16 and 46.96 percent. The above results express that uniformity ratio gradually decrease with the increase in beater speed. At high speed more short fibre are produced which may cause reduction in uniformity ratio. The present finding get full confirmation from the work of lqbal (2002) who noted that at higher beater speed more short fibres are formed which may cause reduction in uniformity ratio. In earlier work Backe (1986) reported that as uniformity increased, the short fibre content decreased.
The individual means of grid bar opening differ significantly from each other for the length uniformity ratio of cotton fibre. Best value of uniformity ratio (47.79%) is recorded at G, opening followed by G4, G3, G2 and G, with their respective mean values as 47.56, 47.33, 47.09 and 46.90 percent. The present results show that at wider opening of grid bar, the uniformity ratio may improve due to the removal of short fibre. Similar views are given by Maqsood (2000) who elucidated that short fibre content may reduce as the more opening of grid bar and uniformity ratio may improve. Likewise Ghani (1997), reported that uniformity ratio of fibres is increased due to removal of short fibres.

Beating action of both machines M1 (Uniclean) and M, (Giant cleaner) negatively affected fibre quality characteristics. However, the performance of Uniclean Bil was exceptionally good for fibre span length and length uniformity ratio. Different intrinsic trash levels have no effect upon fibre span length and length uniformity ratio. Too low and too high speed negative effect upon span length and uniformity ratio. The effect of changing grid bar setting has non-significant effect on span length while the highly significant effect on uniformity ratio.

Sh. Muhammad Nawaz, Babar Shahbaz, Assad Farooq and Muhammad Asif
Department of Fibre Technology, University of Agriculture Faisalabad, Pakistan.

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COTTON - LENGTH RELATED PROPERTIES

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

Cotton is the shortest of the common textile fibers, hence, other things being equal, it makes the most irregular yarns and fabrics. Accordingly the market pays a premium for good length.

The various methods of measuring length may be classified according to whether they

• measure the staple length only, or other parameters
• work by aligning the fiber ends, e.g comb sorters,
• measure only length, or use the tuft for other measurements, such as strength etc

The importance of fiber length to textile processing is significant. Longer fibers produce stronger yarns by allowing fibers to twist around each other more times. Longer fibers can produce finer yarns to allow for more valuable end products. Longer fibers also enable higher spinning speeds by reducing the amount of twist necessary to produce yarn.

The variability in fiber length can be explained 70-80 percent by genetics , so variety selection is very important. Fiber elongation begins at bloom and continues for about 21 days. Moisture stress during the fiber elongation period will reduce fiber length in all varieties. Starting with a variety that has better genetic potential for fiber length will minimize the probability of producing fiber length in the discount range. Severe weathering after bolls have opened can reduce fiber length because more breakage can be expected in the ginning process. Besides variety, water management and maintaining good plant-water relations is probably the most important factor affecting fiber length

Length Uniformity and Short Fiber Content. Length uniformity is now part of the premium/discount valuation of cotton. Short fibers within a process mix of cotton cannot wrap around each other and contribute little or nothing to yarn strength. Short fibers are virtually uncontrolled in the manufacturing process, indirectly causing product defaults and directly contributing to higher waste and lower manufacturing efficiency.

Since short fiber content and length uniformity are derived from length, they are influenced by the same factors as length.. Length uniformity can be more influenced by environment than effective length because temperature is involved in the regulation of genes, which cause epidermal cells to differentiate into fibers. Crop management practices that influence where bolls are located on the plant can impact short fiber content levels. Uniform fruit retention patterns encourage better length uniformity. Disruption to the natural length distribution is most often caused by mechanical damage, so maintaining recommended moisture levels at the gin is important.

SHORT FIBER

The original theory of the fibrogram as developed by Hertel more than fifty years ago has served as the basis of all subsequent cotton length measurements. The major assumptions Hertel made in deriving the theory of the fibrogram are embodied in the statement "The fiber is to be selected at random and every point on every fiber is equally probable." This statement translates to:

• A sampled fiber is held at a random point along its length.
• The probability of sampling a particular fiber is proportional to its length.

Since the longer fibers have a greater probability of being sampled, this results in the length distribution in the fiber beard becoming biased toward the longer fibers.. Using Suter-Webb data and assuming uniform fiber fineness, it is possible to calculate the distributions for the length biased samples.

To investigate the validity of the second assumption, we measured the length distribution of a few fiber samples in their original forms and of fiber beards made from these samples. The selected samples for the experiment were two staple standard cotton samples (SS28 and SS40). Length measurements were performed on the samples in their original forms using standard Suter-Webb Array (SWA) methods and the Advanced Fiber Information System Length and Diameter module (AFIS-L/D) made by Zellweger Uster, Inc. In addition, the AFIS was used to measure the length distributions of fiber beards prepared using a model 192 fibrosampler with and without allowing the beards to pass over the carding section of the fibrosampler. All AFIS-L/D results are the averages of three repetitions with three thousands fibers were measured in each repetition. The experimental results along with the calculated results based on a length biased sample are listed in Table 1..

Table I. Suter-Webb Array (SWA) and AFIS Length data.
Sample: Staple Standard 28
	SWA Raw	SWA Expected	AFIS Raw	AFIS Uncarded	AFIS Carded
By Weight
Mean Length in.	1.19	1.27	1.10	1.09	1.08
Length CV%	29.9	23.7	32.7	31.5	29.9
Short Fiber %	14.2	6.6	13.6	13.6	13.3
Upper Quartile in.	0.92	0.96	0.89	0.89	0.88
By Number
Mean Length in.	0.63	0.75	0.64	0.64	0.65
Length CV%	44.7	29.9	43.1	41.8	39.3
Short Fiber %	31.6	14.2	28.7	28.3	26.7
Upper Quartile in.	0.84	0.92	0.81	0.81	0.81
Sample: Staple Standard 40
	SWA Raw	SWA Expected	AFIS Raw	AFIS Uncarded	AFIS Carded
By Weight
Mean Length in.	1.19	1.27	1.10	1.09	1.08
Length CV%	25.7	19.5	31.2	31.4	31.2
Short Fiber %	4.0	1.1	4.6	4.9	4.6
Upper Quartile in.	1.41	1.44	1.31	1.31	1.3
By Number
Mean Length in.	1.0	1.2	0.9	0.9	0.9
Length CV%	44.0	25.7	40.3	40.3	38.9
Short Fiber %	17.3	4.0	14.0	14.3	13.0
Upper Quartile in.	1.34	1.41	1.22	1.21	1.19

A comparison of the Suter-Webb array data and the AFIS data for the raw stock show good agreement between the methods with small differences characteristic of this version of AFIS. Of more importance is a comparison of the AFIS data between the raw, uncarded and carded samples. The mean lengths and length distributions as indicated by the coefficient of variation are almost identical to those in their original forms. Even if some fiber damage occurs in the AFIS, the damage would be very similar for a given sample and allow us to detect differences in the samples due to the sampling or carding process. Since the differences of the length distributions and the calculated mean lengths between fiber beards and the original fiber samples are small, this would indicate that the second assumption should be modified such that each fiber in the original sample has equal probability to be caught in forming the fiber beard. This in turn would indicate fibers are sampled in clumps rather than individually. Thus the fibrogram theory derived by Hertel should not be applied to the fiber beards prepared from the fibrosampler. However, his theory appears to apply to those fiber beards prepared from sliver by using sliver clamp.

The short fiber algorithm as developed by Zellweger Uster is based on the assumption that the fibers are sampled in clumps and integrates the optical response of the fibers over the width of the lens. The first few length groups are estimated by the character of the fibrogram in the form of a quadratic since the HVI is not able to scan in front of the 0.150 in position. This allows us to calculate a complete fiber distribution from the fibrogram, This data is then treated as Suter-Webb data and various length parameters calculated including short fiber content.

The cotton set with which the short fiber algorithm was originally verified at Zellweger Uster includes international cottons collected by sales agents from around the world along with all available ICC cottons. This set of cottons was tested on two different AFIS instruments. Suter-Webb tests were performed at Zellweger Uster and at the University of Tennessee. The results are shown in figures 1.2 and 3.. The AFIS shows its usual excellent correlation (r=0.97) with Suter-Webb data. In addition, the short fiber value developed by the distribution calculated by the HVI using the new short fiber algorithm correlates well with both AFIS (r=0.93) and with Suter-Webb (r=0.94).

FIG 1

FIG.2

FIG.3

The USDA crop samples from 1990 to 1994 were obtained from Clemson and tested on three HVIs. The agreement between two of the HVIs is shown in figure 4 (r=0.97). As stated before, the entire fiber distribution is obtained. This allows us to calculate not only short fiber values but also other fiber length parameters such as the upper quartile length based on the complete fibrogram rather than a small section of the fibrogram. The relationship of the upper quartile length calculated from Suter-Webb data and the fibrogram is shown in figure 5 (r=0.90).

FIG.4

FIG .5

The USDA, AMS, Cotton Program has been evaluating two methods for determining short fiber content using the Zellweger Uster HVI system. The first method utilizes a short fiber index algorithm, developed by Zellweger Uster, to derive a fibrogram based short fiber index measurement (Riley, 1993). This method has been under evaluation by the Cotton Program for the past two classing seasons (Gibson, 1999). The accuracy of the measurement has improved during this time with the addition of a cotton calibration routine.

The second method being evaluated utilizes a prediction model to derive short fiber index from the HVI measurements of length and uniformity index. This model was designed to predict the short fiber measurement provided by the HVI short fiber index algorithm. Development of the predicted short fiber index measurement began in early 1998. Final revisions to the model, followed by a preliminary evaluation were carried out during the 1998 classing season. Results indicated a strong correlation (R2 = 97%) between the two HVI short fiber measurement methods. Overall reproducibility between HVIs, with a tolerance of 1.0, was 75.1% for the predicted short fiber index measurement compared to 58.7% for the HVI short fiber index algorithm.

Introduction

Short fiber content is defined as the percentage of fibers in a sample, by weight, less than one half inch in length (Bargeron, 1991). Direct short fiber content measurements can be made with methods such as the Suter-Webb Array and AFIS. Although methods such as these provide useful information, testing speed is slow and the short fiber measurement accuracy is questionable. Another option for obtaining a measurement of short fiber is through the HVI system.

All HVI length related measurements such as length and uniformity index are derived from the HVI length fibrogram. Similarly, information exists in the fibrogram to provide a measure of a cotton’s short fiber content. The short fiber measurement provided by the HVI is technically defined as a short fiber index since the HVI is capable of only an indication of the true short fiber content. Since many of the short fibers in a sample are too short to extend from the HVI’s specimen holding clamp into the optical scanning device, a direct short fiber content measurement is not possible.

HVI Short Fiber Index

The addition of the Zellweger Uster HVI Short Fiber Index measurement did not require any HVI hardware modifications. Since this measurement is derived from the same fibrogram used in the determination of length and uniformity index measurements, the only change was the addition of the short fiber algorithm to the HVI’s operating software. The first version of the HVI short fiber index measurement was evaluated in 1997. This early version did not use cotton standards as a basis for calibration. The calibration routine relied on hardware settings which were not successful in providing a common level of testing between multiple instruments (Ramey, 1998). In 1998, a short fiber cotton calibration was developed and added to the existing strength, length and uniformity index cotton calibration routine. Short fiber index values were established on an initial set of calibration cottons using an AFIS instrument.

Subsequent value establishment on replacement standards was performed by the Quality Assurance Unit on HVI’s calibrated to the initial set. Results of the 1998 evaluation showed a reduction in level differences in addition to improved reproducibility between HVI systems (Gibson, 1999). Table 1 is a summary of some of the 1998 evaluation results. Reproducibility (single test versus single test) between each classing office and Quality Assurance is given along with overall classing office averages.

Predicted Short Fiber Index

Considerable research has shown the predictability of short fiber content from HVI measurements of length and uniformity index (Zeidman, 1991; Bragg, 1994; Ramey 1998; Rowland, 1999). The concept of predicting short fiber content from the HVI measurements of length and uniformity index was investigated in 1989 (Zeidman, 1991). This work resulted in a first order prediction model known as the "Zeidman equation." More recent work has shown that an improved prediction model can be developed with the help of a second order prediction model (Rowland, 1999). The advantage of the second order model over the first is the ability to provide accurate short fiber predictions over a wider range of fiber lengths.

The Cotton Program began development of a short fiber prediction equation during the evaluations of the HVI short fiber index measurement. Several equation revisions were made as more HVI short fiber index data was collected. The data used for developing the final prediction equation came from 31,000 samples tested two times in 1998 by the Cotton Program’s Quality Assurance check lot program. These samples are representative of all the major U.S. cotton growing areas and therefore have a very wide range of fiber lengths and short fiber contents.

In addition, the data contained the necessary measurements of HVI length, uniformity index and short fiber index for development of a prediction equation. In order to give the proper weighting to the data, average short fiber indexes were calculated for every combination of length and uniformity index. A total of 269 combinations of length and uniformity index along with the averaged short fiber indexes were computed. Table 2 is a sampling of the combination data used in deriving the short fiber prediction equation. The sample count shows the data distribution for the given length grouping.

The regression analysis of the combination data set resulted in an R2 of 0.97 and produced the second order equation given below:

Z = a + bX + cY + dX2 + eY2 +fXY where

Z = Predicted Short Fiber Index

X = HVI Length

Y = Uniformity Index

a = 384.39664 b = -120.3791 c = -6.700362

d = 12.490109 e = 0.0295697 f = 1.0305676

Applying the equation back to the original data set resulted in favorable predicted short fiber reproducibility between the two tests made on each of the 31,000 samples. Reproducibility was 75.1% with a tolerance of 1.0 between the two predicted measurements. A reproducibility of 58.7% was calculated for the HVI

short fiber index on the same test data. In order to evaluate the agreement between the predicted and HVI short fiber index measurements, reproducibility was calculated within one test of the 31,000 samples. In other words, a comparison was made between the two short fiber measurement methods within the same sample fibrogram. Variability due to between test differences is therefore eliminated. The resulting reproducibility was 77.5%.

The predicted short fiber measurement provides the simplest method for obtaining HVI short fiber information. Obtaining short fiber information is simply a matter of plugging length and uniformity index measurements into the equation. Since the short fiber measurement is derived from these well established measurements, additional calibration routines and calibration standards are not required. In addition, evaluations show that the predicted measurement not only agree extremely well with the HVI short fiber measurement, but is also more repeatable.

Any new HVI measurement should provide meaningful information regarding its subsequent use (Ramey, 1997). Good progress is being made in the HVI determination of a cotton’s short fiber content. Both of the short fiber measurement methods presented in this report are showing their potential. Studies are underway in mill processing environments to assess the utility value of short fiber measurements provided by both methods. In addition, the Cotton Program plans to continue evaluating and comparing these short fiber measurement methods during the upcoming classing season.

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