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Failure Mode and Effects Analysis Using Variable Precision Rough Set Theory and TODIM Method

机译:基于可变精度粗糙集理论和TODIM方法的失效模式及影响分析

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摘要

Failure mode and effects analysis (FMEA) is a widely used tool of risk assessment to identify and eliminate failures of products and systems. However, the conventional FMEA has some defects, such as the same importance of risk factors, utilizing crisp numbers to evaluate failures without considering vagueness. Although fuzzy methods are used to improve the conventional FMEA, the fuzzy FMEA requires much priori information (e.g., fuzzy membership function), which cannot flexibly reflect the changes of a decision makers preference. In addition, most of the previous methods suppose that decision makers are totally rational without considering their psychological factors. Actually, FMEA members' judgments on the failure modes are often influenced by their bounded rationality. To solve those problems, an integrated FMEA model is proposed in this paper, which integrates the strength of variable precision rough set theory in handling vagueness and the merit of TODIM (an acronym in Portuguese of Interactive and Multicriteria Decision Making) approach in manipulating bounded rationality of decision makers. Finally, the proposed method is validated with a case study of a steam valve system to demonstrate its effectiveness and efficiency.
机译:故障模式和影响分析(FMEA)是广泛使用的风险评估工具,用于识别和消除产品和系统的故障。但是,传统的FMEA具有一些缺陷,例如风险因素的重要性相同,利用明晰的数字来评估故障而不考虑模糊性。尽管使用模糊方法来改进常规FMEA,但是模糊FMEA需要大量先验信息(例如,模糊隶属函数),这不能灵活地反映决策者偏好的变化。此外,大多数以前的方法都假定决策者是完全理性的,而不考虑他们的心理因素。实际上,FMEA成员对失效模式的判断通常受其有限理性的影响。为了解决这些问题,本文提出了一个集成的FMEA模型,该模型整合了可变精度粗糙集理论在处理模糊性方面的优势以及TODIM(交互式和多准则决策的葡萄牙语的缩写)在处理有限理性中的优点。决策者。最后,以蒸汽阀系统为例,验证了该方法的有效性和有效性。

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