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Journal of Failure Analysis and Prevention

, Volume 19, Issue 2, pp 350–360 | Cite as

An Extended FMECA Method and Its Fuzzy Assessment Model for Equipment Maintenance Management Optimization

  • Ling WangEmail author
  • Yangfen Gao
  • Wenbin Xu
  • Kaixing Hong
  • Bingrui Wang
  • Xiai Chen
Technical Article---Peer-Reviewed
  • 131 Downloads

Abstract

The failure mode, effect and criticality analysis (FMECA) is a famous bottom-up analytical method for quantifying and ranking critical failures of a product normally at its design stage. At present, as the importance of equipment maintenance increases in industry, FMECA is often applied in maintenance management. In practical cases, equipment is composed of different components, and its maintenance optimization should consider requirements of reliability, availability and costs together. This paper proposes the method called the extended failure mode, effect and criticality analysis (e-FMECA) for equipment maintenance management optimization on the basis of the FMECA theory. This method gives the procedure of analyzing the risks of different failure modes associated with reliability, availability and maintenance costs of equipment. In order to measure these risks of reliability, availability and maintenance costs quantitatively, a fuzzy risk priority method for e-FMECA is developed. Finally, the case study of the e-FMECA method in terms of metro rolling stocks is given. The proposed e-FMECA might be beneficial for selecting the maintenance strategies, maintenance polices and maintenance optimizing objects for maintenance management optimization.

Keywords

Equipment maintenance management optimization Extended FMECA Reliability Availability Maintenance cost Fuzzy risk priority method 

Notes

Acknowledgment

The research work described in this paper was supported by the Public Welfare Technology Application Research Project of Zhejiang Province Science and Technology Department (LGG18F030010), Research Project of Education Department of Zhejiang Province (Y201839978), and National Natural Science Foundation of China (Nos. 51504228, 51575503).

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Copyright information

© ASM International 2019

Authors and Affiliations

  • Ling Wang
    • 1
    Email author
  • Yangfen Gao
    • 1
  • Wenbin Xu
    • 2
  • Kaixing Hong
    • 1
  • Bingrui Wang
    • 1
  • Xiai Chen
    • 1
  1. 1.School of Mechanical and Electrical EngineeringChina Jiliang UniversityHangzhouPeople’s Republic of China
  2. 2.Shanghai Rail Transit Maintenance Support CentreShanghaiPeople’s Republic of China

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