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An analytical model for reliability assessment of the rail system considering dependent failures (case study of Iranian railway)

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  • Nazarizadeh, Farzaneh
  • Alemtabriz, Akbar
  • Zandieh, Mostafa
  • Raad, Abbas

Abstract

Reliability plays an important role in the stable and safe operation of transportation systems. The rail system is one of the vital sectors of transportation that has affected the process of economic and social development. Therefore, accurate predicting of reliability is essential when designing, operating, and maintaining a rail system. This paper proposes an analytical model to estimate the dependent failure rate for the Iranian railway system. This model aims to accurate assessment and predict the reliability of the whole railway system by considering both common cause failure and interactive failure. This model developed by using of the two-variable Taylor expansion approach to estimate the dependent failure rate. The common cause coefficient and interactive coefficient have been estimated by the expert estimation method with the IEC62061 checklist and design structure matrix (DSM) respectively. The proposed model is implemented on the Iranian railway system and the results are analyzed. This paper verifies the model using case studies in the form of different scenarios and compared them with other models. The research results show an improvement in the accuracy of reliability prediction compared to other models.

Suggested Citation

  • Nazarizadeh, Farzaneh & Alemtabriz, Akbar & Zandieh, Mostafa & Raad, Abbas, 2022. "An analytical model for reliability assessment of the rail system considering dependent failures (case study of Iranian railway)," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
    • Handle: RePEc:eee:reensy:v:227:y:2022:i:c:s0951832022003490
    DOI: 10.1016/j.ress.2022.108725
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    2. Liu, Yimeng & Sui, Shaobo & Lu, Dan & Peng, Rui & Bai, Mingyang & Li, Daqing, 2024. "Emergent lifetime distribution from complex network systems aging," Reliability Engineering and System Safety, Elsevier, vol. 247(C).

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