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Reliability analysis and maintenance decision for railway sleepers using track condition information

Author

Listed:
  • J Zhao

    (The University of Birmingham)

  • A H C Chan

    (The University of Birmingham)

  • M P N Burrow

    (The University of Birmingham)

Abstract

This paper describes the development of a model which can be used to evaluate the reliability of a sleeper system when the sleeper condition is known. Two cases that are of particular interest to the railway industry are investigated. These are the failure of a sleeper system caused by at least two consecutive failed sleepers and by at least three consecutive failed ones, respectively. A model to optimize sleeper maintenance is proposed, which minimizes the number of sleepers restored during immediate maintenance subject to meeting the requirements of reliable and safe sleeper operation. Finally, an example is given to illustrate the model.

Suggested Citation

  • J Zhao & A H C Chan & M P N Burrow, 2007. "Reliability analysis and maintenance decision for railway sleepers using track condition information," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(8), pages 1047-1055, August.
    • Handle: RePEc:pal:jorsoc:v:58:y:2007:i:8:d:10.1057_palgrave.jors.2602251
    DOI: 10.1057/palgrave.jors.2602251
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    References listed on IDEAS

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    1. Yun, Won Young & Ferreira, Luis, 2003. "Prediction of the demand of the railway sleepers: A simulation model for replacement strategies," International Journal of Production Economics, Elsevier, vol. 81(1), pages 589-595, January.
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    Cited by:

    1. Bressi, Sara & Santos, João & Losa, Massimo, 2021. "Optimization of maintenance strategies for railway track-bed considering probabilistic degradation models and different reliability levels," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    2. Zai-Wei Li & Xiao-Zhou Liu & Si-Xin Chen, 2022. "A reliability assessment approach for slab track structure based on vehicle-track dynamics and surrogate model," Journal of Risk and Reliability, , vol. 236(1), pages 79-89, February.
    3. Cárdenas-Gallo, Iván & Sarmiento, Carlos A. & Morales, Gilberto A. & Bolivar, Manuel A. & Akhavan-Tabatabaei, Raha, 2017. "An ensemble classifier to predict track geometry degradation," Reliability Engineering and System Safety, Elsevier, vol. 161(C), pages 53-60.
    4. Sedghi, Mahdieh & Kauppila, Osmo & Bergquist, Bjarne & Vanhatalo, Erik & Kulahci, Murat, 2021. "A taxonomy of railway track maintenance planning and scheduling: A review and research trends," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    5. Saleh, Ali & Remenyte-Prescott, Rasa & Prescott, Darren & Chiachío, Manuel, 2024. "Intelligent and adaptive asset management model for railway sections using the iPN method," Reliability Engineering and System Safety, Elsevier, vol. 241(C).

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