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Grey Relational Analysis to Determine the Optimum process parameters for Open-end Spinning Yarns

Abstract

This article focuses on an approach based on the Taguchi method with grey relational analysis for optimizing the process parameters for open-end spun yarns with multiple performance characteristics. A grey relational grade obtained from the grey relational analysis is used to optimize the process parameters. Optimal process parameters can then be determined by the Taguchi method using the grey relational grade as the performance index. CVm%, hair number per meter, and tenacity of yarn were selected as quality characteristics. Using these characteristics, the process parameters, including rotor speed, rotor diameter, opener speed, yarn linear density and navel type are optimized. The raw materials used in this investigation were cotton fibers (35%) and cotton waste (65%) collected from ginning machines. The Experimental results show parameter rotor speed has the most significant effect on the multiple performance characteristics.

 


 

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