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Risk Evaluation in Failure Mode and Effects Analysis Using Fuzzy Measure and Fuzzy Integral

机译:基于模糊测度和模糊积分的失效模式风险评估与影响分析

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Failure mode and effects analysis (FMEA) is a popular and useful approach applied to examine potential failures in different products, designs, processes, and services. As a vital index, the risk priority number (RPN) can determine the risk priorities of failure modes by some risk factors such as occurrence (O), severity (S), and detection (D). However, in FMEA, the traditional risk priority number approach has some shortcomings, especially in setting the weight of risk factors. This paper presents an improved risk priority number approach based on a fuzzy measure and fuzzy integral. A fuzzy measure is used to reflect the importance of the individual indicators and the indicator set and a fuzzy integral is a nonlinear function defined on the basis of fuzzy measure. The weights of risk factors given by domain experts are seen as fuzzy densities to generate a λ -fuzzy measure which can reflect the weights’ difference and relevance about risk factors. Then, the Choquet integral is used to fuse every value of risk factors about failure modes so as to obtain the comprehensive evaluation result. The result can reflect the comprehensive risk level, so it has a definite physical significance. Finally, an illustrative example and a comparison with another approach are given to show the effectiveness of the proposed approach in the paper.
机译:故障模式和影响分析(FMEA)是一种流行且有用的方法,用于检查不同产品,设计,过程和服务中的潜在故障。作为重要指标,风险优先级数字(RPN)可以通过某些风险因素(例如发生(O),严重性(S)和检测(D))确定故障模式的风险优先级。但是,在FMEA中,传统的风险优先级数字方法存在一些缺点,尤其是在确定风险因素的权重方面。本文提出了一种基于模糊测度和模糊积分的改进风险优先级数方法。模糊测度用于反映各个指标和指标集的重要性,而模糊积分是在模糊测度的基础上定义的非线性函数。领域专家给出的风险因子的权重被视为模糊密度,以生成λ-模糊度量,该度量可以反映权重与风险因子之间的差异和相关性。然后,使用Choquet积分融合关于故障模式的风险因子的每个值,以获得综合评估结果。结果可以反映综合风险水平,因此具有一定的物理意义。最后,给出了一个说明性示例并与另一种方法进行了比较,以证明本文中提出的方法的有效性。

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