DocumentCode :
2693244
Title :
Synergy of artificial neural networks and knowledge-based expert systems for intelligent FMS scheduling
Author :
Rabelo, Luis Carlos ; Alptekin, Sema ; Kiran, A. Shyam
fYear :
1990
fDate :
17-21 June 1990
Firstpage :
359
Abstract :
A hybrid architecture that integrates artificial neural networks and knowledge-based expert systems to generate solutions for the real-time scheduling of flexible manufacturing systems is described. The artificial neural networks perform pattern recognition and, due to their inherent characteristics, support the implementation of automated knowledge acquisition and refinement schemes through a feedback mechanism. The artificial neural network structures enable the system to recognize patterns in the tasks to be solved in order to select the best scheduling rule according to different demands. The knowledge-based expert systems are the higher-order elements which drive the inference strategy and interpret the constraints and restrictions imposed by the upper levels of the flexible manufacturing system control hierarchy. The level of self-organization achieved provides a system with a higher probability of success than traditional approaches
Keywords :
expert systems; flexible manufacturing systems; knowledge acquisition; knowledge based systems; neural nets; real-time systems; scheduling; artificial neural networks; automated knowledge acquisition; automated knowledge refinement; feedback; flexible manufacturing systems; hybrid architecture; inference strategy; intelligent FMS scheduling; knowledge-based expert systems; pattern recognition; real-time scheduling; scheduling rule; self-organization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1990., 1990 IJCNN International Joint Conference on
Conference_Location :
San Diego, CA, USA
Type :
conf
DOI :
10.1109/IJCNN.1990.137594
Filename :
5726554
Link To Document :
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