Fuzzy Grey Cognitive Maps in reliability engineering

Current industrial equipment has become more complex and huge. In this case, the conventional reliability techniques cannot correctly support functional assessment. This paper integrates an innovative soft computing methodology, Fuzzy Grey Cognitive Map (FGCM), into a traditional reliability analysis for better knowledge. FGCMs are used for evaluating, modelling and aiding decision-making by examining causal relations among relevant domain concepts. The proposed procedure is illustrated with a reliability analysis of a transformer active part. Twenty failure causes in the transformer's active part are identified and assessed. In addition, six failure scenarios are simulated. The results revealed the potential of the combination of FGCM and failure analysis for complex systems. The proposed methodology exposes the potential benefits it could provide in order to assist electric power system decision-makers to supply its customer electrical energy with a high degree of reliability.

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► An innovative soft computing methodology-based Fuzzy Grey Cognitive Maps (FGCMs) is presented.
► The proposed FGCM model exhibits several advantages over the FCM.
► Potential benefits appear in electrical reliability engineering using FGCM.
► Twenty failure causes in the active part of a transformer has been modelled.