Abstract

Failure mode and effects analysis (FMEA), as a commonly used risk management method, has been extensively applied to the engineering domain. A vital parameter in FMEA is the risk priority number (RPN), which is the product of occurrence (O), severity (S), and detection (D) of a failure mode. To deal with the uncertainty in the assessments given by domain experts, a novel Deng entropy weighted risk priority number (DEWRPN) for FMEA is proposed in the framework of Dempster–Shafer evidence theory (DST). DEWRPN takes into consideration the relative importance in both risk factors and FMEA experts. The uncertain degree of objective assessments coming from experts are measured by the Deng entropy. An expert’s weight is comprised of the three risk factors’ weights obtained independently from expert’s assessments. In DEWRPN, the strategy of assigning weight for each expert is flexible and compatible to the real decision-making situation. The entropy-based relative weight symbolizes the relative importance. In detail, the higher the uncertain degree of a risk factor from an expert is, the lower the weight of the corresponding risk factor will be and vice versa. We utilize Deng entropy to construct the exponential weight of each risk factor as well as an expert’s relative importance on an FMEA item in a state-of-the-art way. A case study is adopted to verify the practicability and effectiveness of the proposed model.

Highlights

  • Risk represents the possibility of unintended faults occurring in a system

  • The practicability and effectiveness of Deng entropy weighted risk priority number (DEWRPN) model for failure mode and effects analysis (FMEA) are verified by a case study in [66]

  • In order to illustrate the validation of this novel DEWRPN model for FMEA, the results obtained for ten failure modes (FMs) using the proposed method are compared with the sorting results in [54,59], where the methods and experiment results are rational

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Summary

Introduction

Risk represents the possibility of unintended faults occurring in a system. Uncertainty is a key issue in risk analysis and management [1,2]. In [48], AMWRPN model for FMEA is presented It processes the weights of risk factors utilizing the fuzziness of experts’ evaluations. The previous methods do not take the relative importance of both risk factors and different experts into account To resolve this problem, a novel Deng entropy weighted RPN (DEWRPN) model for FMEA is proposed. In this method, Deng entropy is firstly used to calculate the weights among three risk factors according to the assessments for every failure mode. In. Section 3, a new Deng entropy weighted risk priority number approach for FMEA model, named.

Preliminaries
Dempster–Shafer Evidence Theory
Deng Entropy
Deng Entropy Weighted Risk Priority Number for FMEA
Application
Discussion
Conclusions
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