DocumentCode
2049749
Title
Decision surface modeling of textile spinning operations using neural network technology
Author
Wu, Peitsang ; Fang, Shu-Cherng ; Nuttle, Henry L W ; King, Russell E. ; Wilson, James R.
Author_Institution
Dept. of Operations Res. & Ind. Eng., North Carolina State Univ., Raleigh, NC, USA
fYear
1994
fDate
4-5 May 1994
Firstpage
0
Lastpage
19
Abstract
The authors study the spinning operations in textile manufacturing. An attempt to “metamodel” the relation between key inputs and performance measures using neural network technology is reported. Two different neural network models, namely a backpropagation neural network and a fuzzy control neural network, were investigated. According to their experience, both models are capable of providing high quality predictions. In addition, results obtained using a fuzzy controller for the learning rate suggest a significant potential for speeding up the training process
Keywords
backpropagation; control system analysis computing; decision theory; fuzzy control; neural nets; process computer control; process control; textile industry; backpropagation; decision surface modeling; fuzzy control; learning rate; manufacturing; metamodelling; neural network technology; predictions; textile spinning operations; training process; Fabrics; Fuzzy control; Manufacturing industries; Neural networks; Object oriented modeling; Pipelines; Spinning; Textile industry; Textile technology; Yarn;
fLanguage
English
Publisher
ieee
Conference_Titel
Textile, Fiber and Film Industry Technical Conference, 1994., IEEE 1994 Annual
Conference_Location
Greenville, SC
Print_ISBN
0-7803-1802-1
Type
conf
DOI
10.1109/TEXCON.1994.320735
Filename
320735
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