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Journal of Applied Sciences
  Year: 2011 | Volume: 11 | Issue: 17 | Page No.: 3204-3208
DOI: 10.3923/jas.2011.3204.3208
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Slub Yarn Quality Optimization by using Desirability Function and Neural Networks

Hajer Souid and Morched Cheikhrouhou

Yarn quality is an essential concept defined by customer which requests the satisfaction of several properties simultaneously. The objective of this study is to optimize Slub yarn quality and then predict it. The approach used to characterize Slub yarn quality is the desirability functions. The present method allowed us to qualify yarn quality by an index belonging to the interval [0, 1] which includes the major physical properties of cotton Slub yarn. Each yarn response is to be maximized, minimized or targeted. These goals have contributed to get a better yarn quality representation. The second step of this study involves the prediction of the overall yarn quality with the consideration of the construction parameters by using artificial neural networks. The artificial neural network is trained to foresee only one response which is the Slub yarn quality index that includes all yarn responses. The definition of the yarn quality can be modified according to customer demands. The model elaborated has presented a good performance and flexibility.
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  •    INfluence of Some Mechanical Factors of Ring Spinning Machine on Cotton Yarn Quality
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How to cite this article:

Hajer Souid and Morched Cheikhrouhou, 2011. Slub Yarn Quality Optimization by using Desirability Function and Neural Networks. Journal of Applied Sciences, 11: 3204-3208.

DOI: 10.3923/jas.2011.3204.3208






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