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A novel approach for multivariate process monitoring using several intelligences

Author

Listed:
  • Nafissa Rezki
  • Okba Kazar
  • Leila Hayet Mouss
  • Laid Kahloul
  • Djamil Rezki

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).

Suggested Citation

  • Nafissa Rezki & Okba Kazar & Leila Hayet Mouss & Laid Kahloul & Djamil Rezki, 2017. "A novel approach for multivariate process monitoring using several intelligences," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 26(3), pages 344-363.
    • Handle: RePEc:ids:ijisen:v:26:y:2017:i:3:p:344-363
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    Cited by:

    1. Jose Ruiz-Tamayo & Jose Antonio Vazquez-Lopez & Edgar Augusto Ruelas-Santoyo & Aidee Hernandez-Lopez & Ismael Lopez-Juarez & Armando Javier Rios-Lira, 2021. "Multivariate Pattern Recognition in MSPC Using Bayesian Inference," Mathematics, MDPI, vol. 9(4), pages 1-18, February.

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