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A new method to evaluate risk in failure mode and effects analysis under fuzzy information

机译:一种评估模糊信息失败模式风险的新方法及其效应分析

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摘要

Failure mode and effects analysis (FMEA) is a useful and effective tool to identify and mitigate project risk, which utilizes the risk priority number (RPN) to determine the risk priority order of failure modes. In many applications when multiple experts give their opinions about one failure mode, the risk evaluations can be vague and imprecise, which could arise conflicting evidence that is hard to manage. To address this issue, the information offered by experts should be analyzed under a model of fuzzy numbers and Dempster-Shafer (D-S) combination theory. Here, the traditional RPN is not sufficient for risk evaluation. A new RPN is proposed in this paper with two parts. The first part is a product of memberships whose average degrees are equal to one, and the second part results from applying the Dempster-Shafer theory with tools of evidential downscaling method and belief entropy function. The new RPN can be effective and convictive to handle conflicting evidence in FEMA.
机译:失败模式和效果分析(FMEA)是一个有用且有效的工具来识别和减轻项目风险,利用风险优先级(RPN)来确定失败模式的风险优先顺序。 在许多应用程序中,当多个专家提供了对一个失败模式的意见时,风险评估可能是模糊的和不精确的,这可能产生难以管理的矛盾的证据。 为了解决这个问题,应根据模糊数和Dempster-Shafer(D-S)组合理论的模型分析专家提供的信息。 在这里,传统的RPN不足以满足风险评估。 在本文中提出了一种新的RPN,两部分。 第一部分是成员资格的产物,其平均度等于一个,第二部分是将Dempster-Shafer理论应用于证据缩小方法和信仰熵功能的工具。 新的RPN可以有效和定罪,以处理FEMA中的矛盾的证据。

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