Fuzzy Grey Cognitive Maps in reliability engineering |
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| Authors: | Jose L Salmeron Ester Gutierrez |
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| Affiliation: | 1. University Pablo de Olavide, 1st km. Utrera Road, 41013 Seville, Spain;2. University of Seville, C. Descubrimientos s/n, 41092 Seville, Spain;1. Department of Trauma and Emergency Surgery, Chang Gung Memorial Hospital, Chang Gung University, Taoyuan, Taiwan;2. Department of Trauma and Emergency Surgery, Taipei Medical University-Wan Fang Hospital, Taipei Medical University, No 111, Sec 3, Xinglong Rd, Taipei 11696, Taiwan;3. School of Medicine, Taipei Medical University, Taipei, Taiwan;1. School of Engineering and Information Technology (SEIT), The University of New South Wales, Canberra, ACT 2612, Australia;2. Faculty of Science, Engineering and Technology, Swinburne University of Technology, Hawthorn, VIC 3122, Australia |
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| Abstract: | 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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