Failure mode risk assessment methodology for controlling multi-uncertainties in the evaluation process

Abstract

The failure mode risk evaluation results of FMEA are affected by multi-uncertainties. This paper proposes a risk evaluation methodology for controlling multi-uncertainties in the assessment process. First, the fuzzy confidence interval number (FCIN) evaluation model is provided to control the uncertainty in assessing the severity (S), occurrence (O), and detectability (D). Then, the FCINs are converted into generalized trapezoidal fuzzy numbers (GTrFNs), and the GTrFNs’ scalar characteristic distances modified by the non-membership are used as the evaluation results of S, O, D and their synthesizer or risk priority number (RPN) to control the risk evaluation model uncertainty. Furthermore, the evaluation parameter value criteria of S, O, D are formulated based on the sensitivity analysis results, more precise than the general value guidelines introduced by industrial FMEA standards. The case study results show that the proposed methodology can significantly improve the risk assessment results and the risk discrimination of failure modes.