IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v152y2021ics1366554521001691.html
   My bibliography  Save this article

Decision support models for annual catenary maintenance task identification and assignment

Author

Listed:
  • Xu, Ren-Hong
  • Lai, Yung-Cheng
  • Huang, Kwei-Long

Abstract

A well-maintained catenary system is crucial to efficient and safe railway operations. Schedule catenary maintenance tasks with consideration of reliability and cost is vital for annual maintenance planning. Since past research on catenary maintenance planning mainly adopt the preventive maintenance (PM) policy with fixed maintenance intervals, this study considers practical concerns of railway operators and applies predictive maintenance (PdM) policy in the annual catenary maintenance planning. A decision support model is proposed by using both mixed integer programming and heuristic methods to identify and assign catenary maintenance tasks with the objective of minimizing maintenance cost and labor cost. The numerical results show that the cost can be improved by 25% compared to the current PM-only practice. The proposed model assists planners to determine and schedule maintenance tasks effectively and ensures the required reliability.

Suggested Citation

  • Xu, Ren-Hong & Lai, Yung-Cheng & Huang, Kwei-Long, 2021. "Decision support models for annual catenary maintenance task identification and assignment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    • Handle: RePEc:eee:transe:v:152:y:2021:i:c:s1366554521001691
    DOI: 10.1016/j.tre.2021.102402
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554521001691
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2021.102402?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Abate, Megersa & Lijesen, Mark & Pels, Eric & Roelevelt, Adriaan, 2013. "The impact of reliability on the productivity of railroad companies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 51(C), pages 41-49.
    2. Kilsby, Paul & Remenyte-Prescott, Rasa & Andrews, John, 2017. "A modelling approach for railway overhead line equipment asset management," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 326-337.
    3. Pham, Hoang & Wang, Hongzhou, 1996. "Imperfect maintenance," European Journal of Operational Research, Elsevier, vol. 94(3), pages 425-438, November.
    4. García Márquez, Fausto Pedro & Lewis, Richard W. & Tobias, Andrew M. & Roberts, Clive, 2008. "Life cycle costs for railway condition monitoring," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(6), pages 1175-1187, November.
    5. Do, Phuc & Voisin, Alexandre & Levrat, Eric & Iung, Benoit, 2015. "A proactive condition-based maintenance strategy with both perfect and imperfect maintenance actions," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 22-32.
    6. Richard E. Barlow & Larry C. Hunter, 1961. "Reliability Analysis of a One-Unit System," Operations Research, INFORMS, vol. 9(2), pages 200-208, April.
    7. Zhou, Xiaojun & Xi, Lifeng & Lee, Jay, 2007. "Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation," Reliability Engineering and System Safety, Elsevier, vol. 92(4), pages 530-534.
    8. Jian Li & Boliang Lin & Zhongkai Wang & Lei Chen & Jiaxi Wang, 2016. "A Pragmatic Optimization Method for Motor Train Set Assignment and Maintenance Scheduling Problem," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-13, March.
    9. Peng, Fan & Ouyang, Yanfeng, 2012. "Track maintenance production team scheduling in railroad networks," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1474-1488.
    10. Hong, H.P. & Zhou, W. & Zhang, S. & Ye, W., 2014. "Optimal condition-based maintenance decisions for systems with dependent stochastic degradation of components," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 276-288.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jingyi Zhao & Chunhai Gao & Tao Tang, 2022. "A Review of Sustainable Maintenance Strategies for Single Component and Multicomponent Equipment," Sustainability, MDPI, vol. 14(5), pages 1-22, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
    2. Dai, Anshu & Wang, Xin & Li, Yu & Li, Ting & He, Shuguang, 2023. "Design of a performance-based warranty policy with replacement–repair strategy and cumulative cost threshold," International Journal of Production Economics, Elsevier, vol. 255(C).
    3. Wu, Fan & Niknam, Seyed A. & Kobza, John E., 2015. "A cost effective degradation-based maintenance strategy under imperfect repair," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 234-243.
    4. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    5. Zhao, Xiujie & He, Shuguang & Xie, Min, 2018. "Utilizing experimental degradation data for warranty cost optimization under imperfect repair," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 108-119.
    6. Zhengxin Zhang & Xiaosheng Si & Changhua Hu & Xiangyu Kong, 2015. "Degradation modeling–based remaining useful life estimation: A review on approaches for systems with heterogeneity," Journal of Risk and Reliability, , vol. 229(4), pages 343-355, August.
    7. You, Ming-Yi & Li, Hongguang & Meng, Guang, 2011. "Control-limit preventive maintenance policies for components subject to imperfect preventive maintenance and variable operational conditions," Reliability Engineering and System Safety, Elsevier, vol. 96(5), pages 590-598.
    8. Lin, Zu-Liang & Huang, Yeu-Shiang & Fang, Chih-Chiang, 2015. "Non-periodic preventive maintenance with reliability thresholds for complex repairable systems," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 145-156.
    9. Tanwar, Monika & Rai, Rajiv N. & Bolia, Nomesh, 2014. "Imperfect repair modeling using Kijima type generalized renewal process," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 24-31.
    10. Xia, Tangbin & Xi, Lifeng & Zhou, Xiaojun & Lee, Jay, 2012. "Dynamic maintenance decision-making for series–parallel manufacturing system based on MAM–MTW methodology," European Journal of Operational Research, Elsevier, vol. 221(1), pages 231-240.
    11. Jiawen Hu & Zuhua Jiang & Hong Wang, 2016. "Preventive maintenance for a single-machine system under variable operational conditions," Journal of Risk and Reliability, , vol. 230(4), pages 391-404, August.
    12. Ait Mokhtar, El Hassene & Laggoune, Radouane & Chateauneuf, Alaa, 2023. "Imperfect maintenance modeling and assessment of repairable multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    13. Nguyen, Kim-Anh & Do, Phuc & Grall, Antoine, 2017. "Joint predictive maintenance and inventory strategy for multi-component systems using Birnbaum’s structural importance," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 249-261.
    14. Liu, Qiannan & Ma, Lin & Wang, Naichao & Chen, Ankang & Jiang, Qihang, 2022. "A condition-based maintenance model considering multiple maintenance effects on the dependent failure processes," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    15. Wang, Weikai & Chen, Xian, 2023. "Piecewise deterministic Markov process for condition-based imperfect maintenance models," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    16. Zhang, Wenyu & Zhang, Xiaohong & He, Shuguang & Zhao, Xing & He, Zhen, 2024. "Optimal condition-based maintenance policy for multi-component repairable systems with economic dependence in a finite-horizon," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    17. Lam, Ji Ye Janet & Banjevic, Dragan, 2015. "A myopic policy for optimal inspection scheduling for condition based maintenance," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 1-11.
    18. Azadeh, A. & Asadzadeh, S.M. & Salehi, N. & Firoozi, M., 2015. "Condition-based maintenance effectiveness for series–parallel power generation system—A combined Markovian simulation model," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 357-368.
    19. Jiawen Hu & Zuhua Jiang & Haitao Liao, 2017. "Preventive maintenance of a batch production system under time-varying operational condition," International Journal of Production Research, Taylor & Francis Journals, vol. 55(19), pages 5681-5705, October.
    20. Nguyen, Kim-Anh & Do, Phuc & Grall, Antoine, 2015. "Multi-level predictive maintenance for multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 83-94.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:152:y:2021:i:c:s1366554521001691. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.