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 Executive Summary

Cotton cost has always been the single major contributor to the cost of grey yarns. Consequently, economic cotton selection for meeting yarn specifications continues to be one of the major concerns of a spinner. Most often, the spinner has to decide upon the purchase of cotton on the basis of fibre-test reports. This is by no means an easy task. Why?

 
 

We know that yarn tenacity is the manifestation of fibre tenacity. However, we come across instances wherein length plays a decisive role. We find that of two cottons, the weaker but longer cotton spins a yarn that is as strong as, or even stronger than, the yarn spun from stronger but shorter cotton. We explain this by reasoning that the longer cotton spins a more even yarn than shorter cotton. In other words, for any one given yarn count, along the axis, the longer fibre yarn has less variation in the number of fibres in the cross-section than the shorter-fibre yarn. This means that, at the place of yarn break in tenacity testing, the yarn from the longer fibres will contain more number of fibres in cross-section than the yarn from the short fibre. The extra number of fibres that break in the case of the long fibre yarn possibly more than compensates for the deficiency in fibre strength itself. This explains why the yarn from the longer, but weaker fibre is stronger than the yarn from the stronger but shorter fibre.

 
 

Implicit in the situation is a trade off: there must exist instances in which a shorter, but stronger cotton spins yarn of the same tenacity as the yarn from a longer, but weaker cotton. In the early nineteen-eighties ATIRA investigations showed that the stronger but shorter F-414 can spin warp yarns comparable in strength to yarns from the longer but weaker S-4. Discerning spinners used this finding, and thereby achieved considerable savings in yarn cost. Such instances are, however, rare, and remain unexplored by default. There are two reasons for this. The first is psychological: the persistence in memory of cotton evaluation by hand stapling. The second is real: the non-availability of a method toquantify accurately the compensation of extra strength for a shortfall in length.

 
 

This is where equations that help estimate yarn tenacity from fibre test data are useful. Consequently, research workers have, over the years, published many yarn tenacity equations.

 
 
All available equations, however, suffer from one or both of two shortcomings: in spite of an impressive value of correlation coefficient, large errors in individual estimates of CSP, even consistent bias in the case of some cottons; not contributing to our understanding of the specific manner in which fibre-length and fibre-fineness contribute to the translation of fibre-tenacity to yarn tenacity. Also, most available equations can only estimate CSP of yarns spun at the optimum twist. Very few equations aim at predicting CSP of yarns at a range of twists.
 
 

It is for these reasons that we have constructed the General Equation for estimating yarn tenacity. With the availability of computers it is possible to perform even very complex calculations instantaneously. In the construction of the equation, therefore, we do not shirk the use of complex expressions where these decidedly enhance the fulfilment of the spinner’s twin expectations of a tenacity equation: accuracy of estimates of yarn tenacity; elucidation of the specific manner in which fibre-length and fibre-fineness contribute to the translation of fibre-tenacity to yarn tenacity.

 
 

In its original form, the general equation requires for its application the following fibre test data: effective length, %-age fibres shorter than 12-mm, %-age fibres longer than 24-mm; fibre fineness, millitex; fibre-bundle strength at zero- and 1/8th gauges.

 
 

We have successfully modified the General Equation to use HIV data for estimating CSP of ring-spun yarns of optimum TM; there is a possibility of extending this method to the estimation of CSP at values of TM other than the optimum. We have also modified the General Equation to predict rotor spun yarn CSP from HVI length, uniformity ratio, and micronaire values.

 
 

The General Equation for estimating cotton yarn tenacity is the outcome of work that I carried out in ATIRA during the period of 1985 to 1991.

 


TAS with inputs from,
Ashok Hirway

Sections in New Research
 Part - I
Index - I
Why Do We Need Another Equation for the Prediction of Yarn Tenacity?
Strcturing the General Equation for Yarn Tenacity

The Algebraic Expressions for the General Equation

The Choice of Parameters of Fibre-Length Distribution for Use in the Irregularity Fraction

Improved Algebraic Expressions for the General Equation
Making Use of the Equation in a Mill
What Does the General Equation Tell Us?
How General Is The General Equation ?

Can We Use the General Equation to Estimate the CSP of Yarns from Mixings of Cottons?            

Can We Modify the General Equation to Estimate CSP Of Combed Yarns?
A Note of Caution
Can We Modify the General Equation to Accept HVI Data?
The General Equation, A Tool for Economic Cotton Selection
 
 Part - II
Index - II
Concept and Structure of a General Equation
The Algebraic Expression 0f the General Equation:The First Attempt

Improved Algebraic Expressions And Their Interpretation

Implications of the General Equation

Appraisal
Practical Application
APPENDIX II - 1 Derivation of the algebraic expressions in the general equation for Brown’s data
APPENDIX II - 2. Regression equations for estimating Uster frequencies of thin and thick places in yarn

Appendix II - 3 Estimating yarn CS from the ATIRA expressions for the general equation.

Appendix II - 4 Cross-Checking Applicability Of Model To Viscose Yarns
Appendix II - 5 Procedure for Adjusting SITRA HVI Test Data To Use In The Modified General Equation For Estimating CS Of Ring-spun Yarns of optimum twist
 
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