Failure mode and effects analysis based on a novel fuzzy evidential method
Failure mode and effects analysis based on a novel fuzzy evidential method
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基于新颖模糊证据方法的失效模式和影响分析
DOI：
10.1016/j.asoc.2017.04.008
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发表时间：
2017-08-01
影响因子：
8.7
通讯作者：
Tang, Yongchuan
中科院分区：
文献类型：
--
作者：
Jiang, Wen;Xie, Chunhe;Tang, Yongchuan
失效模式与效应分析（FMEA）已被广泛应用于检查系统、设计和产品中的潜在失效。风险优先数（RPN）是确定失效模式风险优先级的关键标准。传统上，RPN的确定是基于风险因素，如发生率（O），严重程度（S）和检测（D），这些因素需要精确评估。但该方法存在许多不合理之处，需要进一步改进以适应更多的应用。为了克服传统FMEA的缺点，更好地处理模型和过程的不确定性，我们提出了一种新的模糊证据方法的FMEA模型。采用模糊隶属度对各风险因素的风险进行评价。在此基础上，提出了一种基于证据理论的O、S、D特征信息融合的失效模式风险综合排序方法。该方法的优点是既能覆盖风险评估的多样性和不确定性，又能通过数据融合提高风险概率网的可靠性。为了验证所提出的方法，一个微机电系统（MEMS）的案例研究。实验结果表明，该方法是合理的，有效的真实的应用。(C)2017爱思唯尔B.V.保留所有权利。
Failure mode and effect analysis (FMEA) has been widely applied to examine potential failures in systems, designs, and products. The risk priority number (RPN) is the key criteria to determine the risk priorities of the failure modes. Traditionally, the determination of RPN is based on the risk factors like occurrence (O), severity (S) and detection (D), which require to be precisely evaluated. However, this method has many irrationalities and needs to be improved for more applications. To overcome the shortcomings of the traditional FMEA and better model and process uncertainties, we propose a FMEA model based on a novel fuzzy evidential method. The risks of the risk factors are evaluated by fuzzy membership degree. As a result, a comprehensive way to rank the risk of failure modes is proposed by fusing the feature information of O, S and D with DempsterShafer (DS) evidence theory. The advantages of the proposed method are that it can not only cover the diversity and uncertainty of the risk assessment, but also improve the reliability of the RPN by data fusion. To validate the proposed method, a case study of a micro-electro-mechanical system (MEMS) is performed. The experimental results show that this method is reasonable and effective for real applications. (C) 2017 Elsevier B.V. All rights reserved.