A new method in failure mode and effects analysis based on evidential reasoning

被引：36

作者：

Du Y. ^{[1
]}

Mo H. ^{[1
,2
]}

Deng X. ^{[1
]}

Sadiq R. ^{[3
]}

Deng Y. ^{[1
,4
]}

机构：

[1] School of Computer and Information Science, Southwest University

[2] Department of the Tibetan Language, Sichuan University of Nationalities, Sichuan 626001, Kangding

[3] School of Engineering, University of British Columbia Okanagan, Kelowna, BC

[4] School of Engineering, Vanderbilt University, Nashville

来源：

International Journal of System Assurance Engineering and Management | 2014年 / 5卷 / 1期

基金：

中国国家自然科学基金;

关键词：

Evidential reasoning; Failure mode and effects analysis; Risk priority number; TOPSIS;

D O I：

10.1007/s13198-014-0218-5

中图分类号：

学科分类号：

摘要：

The traditional failure mode and effects analysis (FMEA) is determined by risk priority number (RPN), which is the product of three risk factors occurrence (O), severity (S), and detection (D). One of the open issues is how to precisely determine and aggregate the risk factors. However, the traditional FMEA has been extensively criticized for various reasons. In this paper, a new method in fuzzy FMEA is proposed using evidential reasoning (ER) and the technique for order preference by similarity to ideal solution (TOPSIS). The ER approach is used to express the experts' assessment information which may be imprecise and uncertain. Considering the experts' weights, we construct the group assessment. Weighted average method is then utilized to transform the group assessment value into crisp value. TOPSIS is applied to aggregate the risk factors which are taken to account as the multi-attribute, and used to rank the risk priority. By making full use of attribute information, TOPSIS provides a cardinal ranking of alternatives, and does not require the attribute preferences are independent. A numerical example shows that the proposed method is efficient to its applications. © 2014 The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.

引用

页码：1 / 10

页数：9

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