Integrated importance measure of binary coherent systems

Shu Bin Si, Li Li Zhang, Zhi Qiang Cai, Ning Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Importance measure in reliability engineering is applied to find the weakest component in a system. Traditional importance measures for the binary coherent systems mainly concern reliability importance of an individual component or its structural importance separately, but seldom consider the reliabilities, structures and causalities of the components as a whole. In order to solve the problem above, first of all, four kinds of popular component importance measures are discussed and their calculation methods based on probability distributions are also provided. Then, based on the limitations of such importance measures in system analysis, the integrated importance measure for the binary coherent systems is presented to describe the mathematical expectation of the system reliability decrease based on the current component failure rate. Finally, the simulation study is illustrated based on three typical connection systems. The results show the differences of five importance measures and prove the effectiveness of the integrated importance measure.

Original languageEnglish
Title of host publicationProceedings - 2010 IEEE 17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010
Pages932-936
Number of pages5
DOIs
StatePublished - 2010
Event17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010 - Xiamen, China
Duration: 29 Oct 201031 Oct 2010

Publication series

NameProceedings - 2010 IEEE 17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010

Conference

Conference17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010
Country/TerritoryChina
CityXiamen
Period29/10/1031/10/10

Keywords

  • Binary coherent systems
  • Causality
  • Importance measure
  • Reliability
  • Structure

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