DocumentCode :
2001256
Title :
Hybrid manufacturing line supervision and diagnosis by means of fuzzy rules connected with a causal graph
Author :
Chevalier, Emmanuel ; Martin, Joseph Aguilar ; Colomb, Gil Blanch i ; Laserna, J.L.M.
Author_Institution :
LAAS, CNRS, Toulouse, France
Volume :
3
fYear :
1997
fDate :
1-5 Jul 1997
Firstpage :
1259
Abstract :
The method proposed here consists in generating reactive knowledge represented by fuzzy rules from a given causal graph model. Causal reasoning forms a practical support for model-based diagnosis. Also the fuzzy logic allows us to generate the corrective actions for a qualitative model-based system (supervision). These two kinds of reasoning have been integrated in a computer system for a real world application. A global model based on a causal graph of the process is used for the diagnostic, but local fuzzy reasoning blocks are used for supervision
Keywords :
common-sense reasoning; fault diagnosis; fuzzy logic; graph theory; knowledge acquisition; manufacturing processes; model-based reasoning; process control; causal graph; causal reasoning; corrective actions; diagnosis; fuzzy logic; fuzzy rules; global model; local fuzzy reasoning blocks; manufacturing line; model-based diagnosis; qualitative model-based system; reactive knowledge; supervision; Application software; Computer aided manufacturing; Computer industry; Fuzzy logic; Fuzzy reasoning; Fuzzy systems; Humans; Hybrid power systems; Manufacturing processes; Virtual manufacturing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on
Conference_Location :
Barcelona
Print_ISBN :
0-7803-3796-4
Type :
conf
DOI :
10.1109/FUZZY.1997.619468
Filename :
619468
Link To Document :
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