Author/Authors :
Rezki، Nafissa نويسنده LAP: Laboratory, Industrial Engineering Department, University of Batna, 05000 Batna, Algeria , , Kazar، Okba نويسنده LINFI Laboratory, Computer Science Department, University of Biskra, 07000 Biskra, Algeria , , Mouss، Leila Hayet نويسنده LAP: Laboratory, Industrial Engineering Department, University of Batna, 05000 Batna, Algeria , , Kahloul، Laid نويسنده LINFI Laboratory, Computer Science Department, University of Biskra, 07000 Biskra, Algeria , , Rezki ، Djamil نويسنده LAP: Laboratory, Industrial Engineering Department, University of Batna, 05000 Batna, Algeria ,
Abstract :
The objective of the current paper is to present an intelligent system for complex process monitoring, based on artificial intelligence technologies. This system aims to realize with success all the complex process monitoring tasks that are: detection, diagnosis, identification and reconfiguration. For this purpose, the development of a multi-agent system that combines multiple intelligences such as: multivariate control charts, neural networks, Bayesian networks and expert systems has became a necessity. The proposed system is evaluated in the monitoring of the complex process Tennessee Eastman process.
