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Failure mode and effects analysis: an integrated approach based on rough set theory and prospect theory
Soft Computing ( IF 4.1 ) Pub Date : 2019-08-28 , DOI: 10.1007/s00500-019-04305-8
Hong Fang , Jing Li , Wenyan Song

Abstract

Failure mode and effect analysis (FMEA), a bottom-up method, is one of risk assessment tools to eliminate or reduce failures in design and process. It has been applied to many industries due to its flexibility and effectiveness. However, the conventional FMEA considers less about the subjectivity and vagueness in the process of risk assessment and assumes that three risk factors’ importance is the same. Although a lot of approaches based on fuzzy logic are proposed to deal with vague information in previous literature, they need priori assumptions leading to fixed intervals to express vagueness. In addition, most of the previous methods suppose that decision makers are totally rational without considering their psychological factors. To solve the problems, an extended technique for order performance by similarity to ideal solution (TOPSIS) is developed to improve FMEA approach, which combines the advantage of variable precision rough number in dealing with vague information and the strength of prospect theory (PT) in considering decision maker’s bounded rationality. The proposed method consists of two stages: one is the determination of risk factors’ weight function values; and the other is ranking risk priority of failure modes with the PT-based TOPSIS. Finally, a case study of a steam valve system is used to demonstrate the effectiveness and efficiency of the proposed method.



中文翻译:

失效模式和后果分析:基于粗糙集理论和预期理论的集成方法

摘要

故障模式和效果分析(FMEA)是一种自下而上的方法,是消除或减少设计和过程中的故障的风险评估工具之一。由于它的灵活性和有效性,它已被应用于许多行业。但是,传统的FMEA在风险评估过程中很少考虑主观性和模糊性,并假设三个风险因素的重要性相同。尽管在以前的文献中提出了许多基于模糊逻辑的方法来处理模糊信息,但是它们需要先验假设,从而导致固定间隔来表达模糊性。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。为了解决问题 开发了一种类似于理想解决方案的扩展订单性能技术(TOPSIS),以改进FMEA方法,该方法结合了可变精度粗糙数在处理模糊信息方面的优势以及前景理论(PT)在考虑决策者有限理性方面的优势。所提出的方法包括两个阶段:一是确定危险因素的权重函数值;二是确定风险因素的权重函数值。另一个是使用基于PT的TOPSIS对失败模式的风险优先级进行排序。最后,以蒸汽阀系统为例,验证了该方法的有效性和有效性。所提出的方法包括两个阶段:一是确定危险因素的权重函数值;二是确定风险因素的权重函数值。另一个是使用基于PT的TOPSIS对失败模式的风险优先级进行排序。最后,以蒸汽阀系统为例,验证了该方法的有效性和有效性。所提出的方法包括两个阶段:一是确定危险因素的权重函数值;二是确定风险因素的权重函数值。另一个是使用基于PT的TOPSIS对失败模式的风险优先级进行排序。最后,以蒸汽阀系统为例,验证了该方法的有效性和有效性。

更新日期:2020-04-06
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