Publication | Closed Access
New Failure Mode and Effects Analysis: An Evidential Downscaling Method
74
Citations
37
References
2014
Year
Bayesian Decision TheoryEngineeringTypical FmeaSafety ScienceDiagnosisRisk AnalysisFailure ModeUncertainty FormalismFuzzy Risk AnalysisDecision AnalyticsReliability EngineeringData ScienceUncertainty QuantificationRisk ManagementManagementFailure AnalysisSystems EngineeringBayesian MethodsFmea ModelReliability AnalysisStatisticsFailure DetectionReliabilityRisk AnalyticsEngineering Failure AnalysisDecision Support SystemsEvidential ReasoningNew Failure ModeRisk AssessmentBayesian StatisticsFailure PredictionDempster-shafer Theory
Failure mode and effects analysis (FMEA) is an engineering and management technique, which is widely used to define, identify, and eliminate known or potential failures, problems, errors, and risk from the design, process, service, and so on. In a typical FMEA, the risk evaluation is determined by using the risk priority number (RPN), which is obtained by multiplying the scores of the occurrence, severity, and detection. However, because of the uncertainty in FMEA, the traditional RPN has been criticized because of several shortcomings. In this paper, an evidential downscaling method for risk evaluation in FMEA is proposed. In FMEA model, we utilize evidential reasoning approach to express the assessment from different experts. Multi-expert assessments are transformed to a crisp value with weighted average method. Then, Euclidean distance from multi-scale is applied to construct the basic belief assignments in Dempster–Shafer evidence theory application. According to the proposed method, the number of ratings is decreased from 10 to 3, and the frame of discernment is decreased from 210 to 23, which greatly decreases the computational complexity. Dempster's combination rule is utilized to aggregate the assessment of risk factors. We illustrate a numerical example and use the proposed method to deal with the risk priority evaluation in FMEA. The results and comparison show that the proposed method is more flexible and reasonable for real applications. Copyright © 2014 John Wiley & Sons, Ltd.
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