Zheng Haixia, Tang Yongchuan
School of Big Data and Software Engineering, Chongqing University, Chongqing 401331, China.
Entropy (Basel). 2020 Feb 28;22(3):280. doi: 10.3390/e22030280.
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.
失效模式与效应分析（FMEA）作为一种常用的风险管理方法，已在工程领域得到广泛应用。FMEA中的一个关键参数是风险优先数（RPN），它是失效模式的发生度（O）、严重度（S）和探测度（D）的乘积。为了处理领域专家评估中的不确定性，在Dempster-Shafer证据理论（DST）框架下，提出了一种用于FMEA的新型邓熵加权风险优先数（DEWRPN）。DEWRPN考虑了风险因素和FMEA专家两方面的相对重要性。专家客观评估的不确定程度通过邓熵来衡量。专家的权重由从专家评估中独立获得的三个风险因素的权重组成。在DEWRPN中，为每位专家分配权重的策略灵活且与实际决策情况相适应。基于熵的相对权重象征着相对重要性。具体而言，专家对某个风险因素的不确定程度越高，相应风险因素的权重就越低，反之亦然。我们以一种先进的方式利用邓熵构建每个风险因素的指数权重以及专家对FMEA项目的相对重要性。通过一个案例研究来验证所提模型的实用性和有效性。
