Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/157473
Authors: 
Rezki, Nafissa
Kazar, Okba
Mouss, Leila Hayet
Kahloui, Laid
Rezki, Djamil
Year of Publication: 
2016
Citation: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 12 [Year:] 2016 [Pages:] 111-118
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.
Subjects: 
Multivariate process
Hotelling T2 control chart
Multi-agent system
Bayesian network
Neural network
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

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