Predicting the Performance of Fabrics in Garment Manufacturing with Artificial Neural Networks

Author:

Gong R.H.1,Chen Y.2

Affiliation:

1. Department of Textiles, University of Manchester Institute of Science and Technology, Manchester M60 1QD, United Kingdom

2. Department of Silk Textile Engineering, Suzhou Institute of Silk Textile Technology, Suzhou, People's Republic of China

Abstract

Neural networks are used to predict the performance of fabrics in clothing manufac turing. The predictions are based on fabric mechanical properties measured on the KES-FB system. The influence of the number of input and hidden nodes on the convergence speed and the prediction accuracy are investigated. Tests indicate that these artificial neural networks are effective for predicting potential problems in clothing manufacturing.

Publisher

SAGE Publications

Subject

Polymers and Plastics,Chemical Engineering (miscellaneous)

Reference18 articles.

1. Yarn Strength Prediction Using Neural Networks

2. Ito, K., Process Control for Tailoring Based on Objective Data about Fabric Properties , in "Proc. 2nd Australia-Japan Joint Symposium: Objective Evaluation of Apparel Fabrics," The Textile Machinery Society of Japan, 1983, p. 89.

3. Kawabata, S., Recent Developments in the Objective Measurement of Apparel Fabric Handle, Quality and Physical Properties , in "Proc. 2nd Australia-Japan Joint Symposium: Objective Evaluation of Apparel Fabrics," The Textile Machinery Society of Japan, 1983, p. 15.

4. Mahar, T.J., Dhingra, R.C., and Postle, R., The Investigation and Objective Measurement of Fabric Mechanical and Physical Properties Relevant to Tailoring, in "Proc. 1st Australia-Japan Joint Symposium: Objective Specification of Fabric Quality, Mechanical Properties and Performance ," The Textile Machinery Society of Japan , 1982, p. 301.

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