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Failure modes and effects analysis using integrated weight-based fuzzy TOPSIS
120
Citations
36
References
2013
Year
EngineeringIndustrial EngineeringFuzzy Risk AnalysisProcess SafetyFuzzy Multi-criteria Decision-makingReliability EngineeringAbstract Failure ModeFmea MethodRisk ManagementConventional FmeaSystems EngineeringFuzzy OptimizationReliabilityFuzzy LogicStructural Health MonitoringEngineering Failure AnalysisReliability PredictionCivil EngineeringFuzzy Expert SystemFailure PredictionFailure Modes
Abstract Failure mode and effect analysis (FMEA) technique has been extensively used as a powerful tool for identifying and assessing potential failures in different phases of the product life cycle. However, the conventional FMEA has been criticised much for its deficiencies in measurement scale, computation of risk priority numbers (RPN), risk factors' weights, etc. In this work, the authors propose a more reasonable failure evaluation structure using fuzzy weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). To fully reflect the importance of risk factors severity (S), occurrence (O) and detection (D), the authors consider integrating both subjective weights and objective weights, which is not presented in literature before, avoid failure modes from being underestimated or overestimated. For ranking fuzzy TOPSIS is adopted to get the closeness coefficient for each failure mode. Then, all failure modes can be ranked according to the closeness coefficients. A case of nuclear reheat valve system is provided to illustrate the applications and benefits of proposed FMEA method. Keywords: failure mode and effects analysisintegrated weightsfuzzy TOPSIS Acknowledgement The authors thank the editor and the anonymous reviewers for their helpful comments and suggestions on this article.
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