NDLI: Optimization of the processing conditions and prediction of the quality for dyeing nylon and lycra blended fabrics

Content Provider	Springer Nature Link
Author	Kuo, Chung Feng Jeffrey Fang, Chien Chou
Copyright Year	2006
Abstract	This paper is intended to determine the optimal processing parameters applied to the dyeing procedure so that the desired color strength of a raw fabric can be achieved. Moreover, the processing parameters are also used for constructing a system to predict the fabric quality. The fabric selected is the nylon and Lycra blend. The dyestuff used for dyeing is acid dyestuff and the dyeing method is one-bath-two-section. The Taguchi quality method is applied for parameter design. The analysis of variance (ANOVA) is applied to arrange the optimal condition, significant factors and the percentage contributions. In the experiment, according to the target value, a confirmation experiment is conducted to evaluate the reliability. Furthermore, the genetic algorithm (GA) is combined with the back propagation neural network (BPNN) in order to establish the forecasting system for searching the best connecting weights of BPNN. It can be shown that this combination not only enhances the efficiency of the learning algorithm, but also decreases the dependency of the initial condition during the network training. Most of all, the robustness of the learning algorithm will be increased and the quality characteristic of fabric will be precisely predicted.
Starting Page	344
Ending Page	351
Page Count	8
File Format	PDF
ISSN	12299197
Journal	Fibers and Polymers
Volume Number	7
Issue Number	4
e-ISSN	18750052
Language	English
Publisher	Springer-Verlag
Publisher Date	2006-01-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Nylon and lycra blended fabrics Optimizing dyeing Taguchi method Neural network Genetic algorithm (GA) Polymer Sciences
Content Type	Text
Resource Type	Article
Subject	Chemistry Chemical Engineering Polymers and Plastics

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