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Prediction of Polypropylene Yarn Shrinkage in the Heat-Setting Process Using the Fuzzy Inference System

Research and development

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Nr DOI: 10.5604/01.3001.0014.3146

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Abstract:

In the carpet industry, yarn shrinkage is a very important specification, the percent of which being affected by heat-setting parameters, time and temperature. In order to obtain the best uniform appearance of carpets, the shrinkage of pile yarns should be minimum in the carpet sizing process. Inappropriately heat-set yarn may cause undesirable shrinkage and uneven pile height on carpets after the sizing process. It could be useful for manufacturers to understand the optimum condition of heat setting to obtain the low shrinkage of heat-set yarns before weaving. Therefore, a fuzzy logic model was designed to predict the shrinkage percentage of polypropylene yarn in different heat-setting conditions. Time and temperature are taken into account as input variables, and yarn shrinkage is predicted as the output. For validation of the model, yarn samples were heat set over various periods of time, at different temperatures, and finally yarn shrinkages were measured experimentally. The results of the fuzzy model prediction compared to regression results show that the fuzzy results present a good and better match with experimental results, with an acceptable R2 = 0.97 and average error (2.59%).



Tags:

heat setting, shrinkage, Fuzzy inference system, polypropylene.

Citation:

Dadgar M. Prediction of Polypropylene Yarn Shrinkage in the Heat-Setting Process Using the Fuzzy Inference System. FIBRES & TEXTILES in Eastern Europe  2020; 28, 6(144): 35-41. DOI: 10.5604/01.3001.0014.3146

Published in issue no 6 (144) / 2020, pages 35–41.

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