5 research outputs found

    Adaptation-Guided retrieval for a diagnostic and repair help system dedicated to a pallets transfer.

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    International audienceIn this paper, we describe a CBR approach for failure diagnosis of a pallets transfer. Adaptation phase is the key problem of the case-based reasoning system conception. This paper is a contribution to fill this gap in the equipments diagnostic and repair help. Retrieval step guided by adaptation is proposed, as a result measures associated with an adaptation measure are proposed. These two measures will make it possible to select among the retrieved cases the most adaptable case. Then, an adaptation algorithm is proposed and will rely on a descriptors hierarchy, a context model as well as the dependences between problem and solution of the source cases. A feasibility study of the proposed algorithm is made on a real industrial diagnosis case. Three scenarios are treated in this study concerning various dependency relation values and belonging to the hierarchical classes of descriptors

    A methodology to conceive a case based system of industrial diagnosis.

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    International audienceThe 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

    Reutilization of diagnostic cases by adaptation of knowledge models.

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    International audienceThis paper deals with design of knowledge oriented diagnostic system. Two challenges are addressed. The first one concerns the elicitation of expert practice and the proposition of a methodology for developing four knowledge containers of case based reasoning system. The second one concerns the proposition of a general adaptation phase to reuse case solving diagnostic problems in a different context. In most cases, adaptation methods are application-specific and the challenge in this work is to make a general adaptation method for the field of industrial diagnostics applications. This paper is a contribution to fill this gap in the field of fault diagnostic and repair assistance of equipment. The proposed adaptation algorithm relies on hierarchy descriptors, an implied context model and dependencies between problems and solutions of the source cases. In addition, one can note that the first retrieved case is not necessarily the most adaptable case, and to take into account this report, an adaptation-guided retrieval step based on a similarity measure associated with an adaptation measure is realized on the diagnostic problem. These two measures allow selecting the most adaptable case among the retrieved cases. The two retrieval and adaptation phases are applied on real industrial system called Supervised industrial system of Transfer of pallets (SISTRE)
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