Diagnosing urban rail transit vehicles with FMEA and fuzzy set

The purpose of this paper is to develop an effective treatment to analyze and diagnose urban rail transit (URT) vehicle maintenance strategy.

In this paper, the technique of Failure Mode and Effects Analysis (FMEA) is introduced into the examination of URT trains, first. Then the method of fuzzy-set-based assessment for FMEA is presented, which is the quantitative tool of Fuzzy-Set-based treatment for FMEA in analysis and diagnoses to URT maintenance strategy. Moreover, recommendations for further improvement of the proposed approach are also provided. Initial application into the vehicle maintenance of Shanghai URT System shows, that the proposed approach has a good performance and consequently is worth further development.

The paper presents a FMEA and fuzzy-set-based theoretical approach for analyzing and diagnosing current methods in URT vehicle maintenance strategy.

With rapid development of URT systems in the world especially in those highly populated areas, much more attentions are turning to researches on URT maintenance, nevertheless, few quantitative research achievement are mentioned or applied. This paper is a tentative attempt at introducing fuzzy-set theory into quantitative analysis and diagnoses of URT maintenance strategy.

The study in this paper is helpful in theory and practice of URT maintenance and its methodology could be further applied into a broad family of facility group or system in other engineering fields.