Failure mode and effect analysis (FMEA) is a powerful risk discerning technique for identifying, evaluating, and reducing possible failures of products or processes. However, the classical FMEA has been criticized for inherent limitations, such as equal weights of risk elements and lack of capability in handling inaccurate information. Although fuzzy‐based modified FMEA methods are frequently utilized to handle vagueness of experts' judgments, they still have some drawbacks, for example, requiring extra assumptions, neglecting experts' bounded rationality and psychological effects, lacking consideration of randomness, and only considering three classical risk elements among most of them. Therefore, this study develops an extended risk assessment method to enhance the performance of FMEA, which integrates the superiority of rough number theory in handling subjective and inaccurate information and the advantage of cloud model theory in reflecting the randomness of qualitative evaluations. Moreover, two synthetic weighting methods are developed to determine the weights of risk elements and handle the experts' individual effects, respectively, which consider both subjective and objective aspects. In addition, maintenance is added into the classical risk elements, and then a hierarchical structure containing four risk dimensions is built to evaluate failures' risk levels comprehensively. Finally, an application case to demonstrate the effectiveness of the developed FMEA model is presented.

中文翻译：

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不确定环境下失效模式和影响分析的一种改进方法：以关键功能组件为例

故障模式和效果分析（FMEA）是一种强大的风险识别技术，用于识别，评估和减少产品或过程的可能故障。但是，经典FMEA因其固有的局限性而受到批评，例如风险要素的权重相等以及缺乏处理不准确信息的能力。尽管基于模糊的改进的FMEA方法经常被用来处理专家判断的模糊性，但是它们仍然存在一些缺陷，例如，需要额外的假设，忽略了专家有限的理性和心理影响，缺乏对随机性的考虑，仅考虑了三种经典方法。其中大多数是危险因素。因此，本研究开发了一种扩展的风险评估方法来增强FMEA的性能，它融合了粗糙数理论在处理主观和不准确信息方面的优势，以及云模型理论在反映定性评估的随机性方面的优势。此外，开发了两种综合加权方法来确定风险要素的权重并分别处理专家的个人影响，这些考虑了主观和客观方面。此外，将维护添加到经典风险元素中，然后构建包含四个风险维度的层次结构来全面评估故障的风险级别。最后，给出了一个应用案例来证明所开发的FMEA模型的有效性。