Developing a life cycle cost model for real-time condition monitoring in railways under uncertainty

Di Zhang, Hao Hu, Clive Roberts, Lei Dai, Anson Jack

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

The Shanghai Transport Committee has estimated that passenger traffic increased fivefold between 2005 and 2014, and will continue to increase. At the same time, the maintenance costs of the Shanghai Metro have increased to about six times their original value. To ensure reliability, availability, maintainability and safety (RAMS) in railways, equipment sometimes needs to be upgraded; new technology is an effective way of modernizing the system. Condition monitoring techniques are considered to be a pragmatic approach to improve RAMS in railways. Bearings are seen to be a key factor in the successful operation of railways, as their performance is related to safety and reliability. To meet the safety requirements, an efficient method is to implement a real-time condition monitoring (RTCM) technique. To evaluate the economic cost of this investment in RTCM, the life cycle cost (LCC) should be considered. A Petri net combined with the Monte Carlo method is used to simulate the LCC evaluation process and a case study of how to employ this method is presented.
Original languageEnglish
Pages (from-to)111-121
Number of pages11
JournalProceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit
Volume231
Issue number1
Early online date17 Dec 2015
DOIs
Publication statusPublished - 1 Jan 2017

Keywords

  • railway
  • bearings
  • life cycle cost
  • Petri net
  • Real-time condition monitoring

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