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Measuring the influence of fibre-to-fabric properties on the pilling of wool fabrics

journal contribution
posted on 2006-01-01, 00:00 authored by Rafael Beltran, Lijing Wang, Xungai Wang
This study ranks the contribution of various fibre, yarn and fabric attributes to the pilling of wool knitwear. On the basis of an artificial neural network modelling, a combination of sensitivity analysis, forwards/backwards search and genetic algorithms was used to identify the importance of various fibre/yarn/fabric input parameters. The three different techniques show broad similarities in their assessment of which input parameters are important or are not important in affecting fabric pilling. The ranking shows that fabric cover factor has the most effect on pilling, followed by yarn count and thin places, fibre length, yarn twist, etc. It is further illustrated that the directional trend of the predicted pilling outputs for a selection of inputs was in line with the expected behaviour. To verify the findings of input feature selection, input factors deemed to have a small effect on the predicted pilling output, such as fibre length and diameter variations and curvature, were removed and the subsequent performance statistically compared to the original multi-layer perceptron. Differences between the outputs predicted by the original and pruned models are found not to be statistically significant at the 5% significance level. Results from this study may help manufacturers and knitwear designers in choosing the most appropriate materials and structures to reduce the pilling propensity of wool knitwear.

History

Journal

Journal of the textile institute

Volume

97

Issue

3

Pagination

197 - 204

Publisher

Taylor & Francis

Location

Manchester, England

ISSN

0040-5000

eISSN

1754-2340

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2006, Taylor & Francis