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Thinking sewing machines for intelligent garment manufacture

G. Stylios (Department of Industrial Technology, University of Bradford, Bradford, UK)
J.O. Sotomi (Department of Industrial Technology, University of Bradford, Bradford, UK)

International Journal of Clothing Science and Technology

ISSN: 0955-6222

Article publication date: 1 March 1996

487

Abstract

Quantitative fabric‐needle‐sewing machine interactions at different speeds have been used to construct qualitative rules mapping fabric properties to optimum sewing machine settings for the next generation of “intelligent sewing machines”, using model free estimation. The inference procedures of fuzzy logic have been implemented in a neural network to allow for optimization of output membership functions and subsequently, self‐learning. The technique is successfully applied to industrial lockstitch and overlock sewing machines. Optimum settings were achieved under static and dynamic machine conditions from the properties of difficult fabrics and compensation for mishandling by the operator over the speed range of the sewing machine.

Keywords

Citation

Stylios, G. and Sotomi, J.O. (1996), "Thinking sewing machines for intelligent garment manufacture", International Journal of Clothing Science and Technology, Vol. 8 No. 1/2, pp. 44-55. https://doi.org/10.1108/09556229610109609

Publisher

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MCB UP Ltd

Copyright © 1996, MCB UP Limited

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