Title: A novel approach for multivariate process monitoring using several intelligences

Authors: Nafissa Rezki; Okba Kazar; Leila Hayet Mouss; Laid Kahloul; Djamil Rezki

Addresses: Department of Industrial Engineering, Batna University, LAP Laboratory of Automation and Production, Batna 05000, Algeria ' Department of Industrial Engineering, Batna University, LAP Laboratory of Automation and Production, Batna 05000, Algeria ' Department of Industrial Engineering, Batna University, LAP Laboratory of Automation and Production, Batna 05000, Algeria ' Department of Industrial Engineering, Batna University, LAP Laboratory of Automation and Production, Batna 05000, Algeria ' Department of Industrial Engineering, Batna University, LAP Laboratory of Automation and Production, Batna 05000, Algeria

Abstract: This paper presents a multi-agent system for multivariate process monitoring. The proposed multi-agent system combines several intelligences which are: multivariate control charts, neural networks, Bayesian networks, and expert systems. This system aims to realise a complete control of complex industrial process. In order to demonstrate the efficiency of the proposed multi-agent system, it has been applied and evaluated in the monitoring of the complex process Tennessee Eastman process (TEP).

Keywords: multivariate process; multi-agent system; Hotelling T² control chart; Bayesian network; neural network.

DOI: 10.1504/IJISE.2017.084424

International Journal of Industrial and Systems Engineering, 2017 Vol.26 No.3, pp.344 - 363

Received: 20 Apr 2015
Accepted: 28 Jun 2015
Published online: 07 Jun 2017 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article