A Methodology to Conceive A Case Based System Of Industrial Diagnosis

  • Brigitte Chebel-Morello
  • Karim Haouchine
  • Noureddine Zerhouni
Conference paper


The objective of this paper is to address the diagnosis knowledge-oriented system in terms of artificial intelligence, particular by the Case-Based Reasoning (CBR) approach. Indeed, the use of CBR, which is an approach to problem solving and learning, in diagnosis goes back to a long time with the appearance of diagnostic support systems based on CBR. A diagnostic system by CBR implements an expertise-base composed of past experiences through which the origins of failure and the maintenance strategy are given according to a description of a specific situation of diagnostic. A study is made on the different diagnostic systems based on CBR. This study showed that there was no common methodology for building a CBR system. This design depends primarily on the case representation and knowledge models of the domain application. Consequently, this paper proposes a general design approach of a diagnostic system based on the CBR approach.


Context Model Case Base Reasoning Adaptation Phase Knowledge Model Retrieval Phase 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Brigitte Chebel-Morello
    • 1
  • Karim Haouchine
    • 1
  • Noureddine Zerhouni
    • 1
  1. 1.Automatic Control and Micro-Mechatronic Systems Department FEMTO-ST Institute –UMR CNRS 6174BesançonFrance

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