Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System

Abstract : Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach.
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N Rabah, R Saddem, F Ben Hmida, V Carre-Menetrier, M Tagina. Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System. 13th European Workshop on Advanced Control and Diagnosis, Oct 2016, Lille, France. pp.012009, ⟨10.1088/1742-6596/783/1/012009⟩. ⟨hal-01899933⟩

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