DocumentCode
301768
Title
Building a hybrid pultrusion Derakane 440/40 process model using neural networks and process data
Author
Wright, David T. ; Williams, David J.
Author_Institution
Dept. of Manuf. Eng., Loughborough Univ. of Technol., UK
Volume
4
fYear
1995
fDate
22-25 Oct 1995
Firstpage
3748
Abstract
Previous extensive laboratory pultrusion trials and materials analysis yielded a rich data set. This paper details various representations of this data set in alternate artificial neural networks (ANN). The authors examine the effectiveness of the various ANN process models. A number of existing mathematical pultrusion models are discussed. Further, hybrid process models were developed which gave novel insight into various relationships between inter-process variables
Keywords
glass fibre reinforced composites; knowledge representation; manufacturing processes; modelling; neural nets; process control; hybrid pultrusion Derakane 440/40 process model; materials analysis; neural networks; process data; Artificial neural networks; Data engineering; Knowledge representation; Materials testing; Mathematical model; Mechanical sensors; Neural networks; Object oriented modeling; Pulp manufacturing; Resins;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-2559-1
Type
conf
DOI
10.1109/ICSMC.1995.538371
Filename
538371
Link To Document