IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v215y2021ics0951832021003495.html
   My bibliography  Save this article

Maintenance gravity window based opportunistic maintenance scheduling for multi-unit serial systems with stochastic production waits

Author

Listed:
  • Zhou, Xiaojun
  • Ning, Xiaohan

Abstract

This paper proposes an Opportunistic Maintenance (OM) scheduling model for the multi-unit serial system subject to random production waits. With the stochastic nature of production waits involved, the pre-scheduled Preventive Maintenance (PM) time for each unit changes from a specific time to a time window. To effectively group the PM activities of the units with a series of time windows, a new concept called Maintenance Gravity Window (MGW) is introduced and then a novel MGW based OM policy is developed. Whenever one of the units reaches its PM threshold or accepts a production wait to conduct PM, a PM opportunity for the system arises. At that time, all the other units, which also reach their own PM thresholds or accept this production wait, or whose gravity related to the current PM opportunity is within the MGW, will be preventively maintained together with this unit. The optimal MGW for the system is obtained by minimizing the total maintenance cost per unit time throughout the PM scheduling horizon. Finally, numerical examples and comparisons are illustrated to show the cost-effectiveness of the proposed MGW based OM policy.

Suggested Citation

  • Zhou, Xiaojun & Ning, Xiaohan, 2021. "Maintenance gravity window based opportunistic maintenance scheduling for multi-unit serial systems with stochastic production waits," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
  • Handle: RePEc:eee:reensy:v:215:y:2021:i:c:s0951832021003495
    DOI: 10.1016/j.ress.2021.107828
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832021003495
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2021.107828?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. Wang, Jun & Zhu, Xiaoyan, 2021. "Joint optimization of condition-based maintenance and inventory control for a k-out-of-n:F system of multi-state degrading components," European Journal of Operational Research, Elsevier, vol. 290(2), pages 514-529.
    2. Zhou, P. & Yin, P.T., 2019. "An opportunistic condition-based maintenance strategy for offshore wind farm based on predictive analytics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 1-9.
    3. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    4. Zhou, Xiaojun & Yu, Mengqi, 2020. "Semi-dynamic maintenance scheduling for multi-station series systems in multi-specification and small-batch production," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    5. Abdelhakim Khatab & EL Houssaine Aghezzaf & Claver Diallo & Imene Djelloul, 2017. "Selective maintenance optimisation for series-parallel systems alternating missions and scheduled breaks with stochastic durations," International Journal of Production Research, Taylor & Francis Journals, vol. 55(10), pages 3008-3024, May.
    6. Zhu, Qiushi & Peng, Hao & Timmermans, Bas & van Houtum, Geert-Jan, 2017. "A condition-based maintenance model for a single component in a system with scheduled and unscheduled downs," International Journal of Production Economics, Elsevier, vol. 193(C), pages 365-380.
    7. Zhou, Xiaojun & Huang, Kaimin & Xi, Lifeng & Lee, Jay, 2015. "Preventive maintenance modeling for multi-component systems with considering stochastic failures and disassembly sequence," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 231-237.
    8. Lu, Biao & Zhou, Xiaojun, 2017. "Opportunistic preventive maintenance scheduling for serial-parallel multistage manufacturing systems with multiple streams of deterioration," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 116-127.
    9. Cavalcante, C.A.V. & Lopes, R.S. & Scarf, P.A., 2018. "A general inspection and opportunistic replacement policy for one-component systems of variable quality," European Journal of Operational Research, Elsevier, vol. 266(3), pages 911-919.
    10. C. Drent & S. Kapodistria & J. A. C. Resing, 2019. "Condition-based maintenance policies under imperfect maintenance at scheduled and unscheduled opportunities," Queueing Systems: Theory and Applications, Springer, vol. 93(3), pages 269-308, December.
    11. Do Van, Phuc & Barros, Anne & Bérenguer, Christophe & Bouvard, Keomany & Brissaud, Florent, 2013. "Dynamic grouping maintenance with time limited opportunities," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 51-59.
    12. Truong Ba, H. & Cholette, M.E. & Borghesani, P. & Zhou, Y. & Ma, L., 2017. "Opportunistic maintenance considering non-homogenous opportunity arrivals and stochastic opportunity durations," Reliability Engineering and System Safety, Elsevier, vol. 160(C), pages 151-161.
    13. Ding, Fangfang & Tian, Zhigang, 2012. "Opportunistic maintenance for wind farms considering multi-level imperfect maintenance thresholds," Renewable Energy, Elsevier, vol. 45(C), pages 175-182.
    14. Si, Guojin & Xia, Tangbin & Zhu, Ying & Du, Shichang & Xi, Lifeng, 2019. "Triple-level opportunistic maintenance policy for leasehold service network of multi-location production lines," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    15. Juan Izquierdo & Adolfo Crespo Márquez & Jone Uribetxebarria & Asier Erguido, 2019. "Framework for Managing Maintenance of Wind Farms Based on a Clustering Approach and Dynamic Opportunistic Maintenance," Energies, MDPI, vol. 12(11), pages 1-17, May.
    16. Hu, Jiawen & Shen, Jingyuan & Shen, Lijuan, 2020. "Opportunistic maintenance for two-component series systems subject to dependent degradation and shock," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    17. 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.
    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. Wei, Shuaichong & Nourelfath, Mustapha & Nahas, Nabil, 2023. "Analysis of a production line subject to degradation and preventive maintenance," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    2. Shi, Haohao & Zhang, Ji & Zio, Enrico & Zhao, Xufeng, 2023. "Opportunistic maintenance policies for multi-machine production systems with quality and availability improvement," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    3. Li, Yaping & Xia, Tangbin & Chen, Zhen & Pan, Ershun, 2023. "Multiple degradation-driven preventive maintenance policy for serial-parallel multi-station manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    4. Chen, Liwei & Gao, Yansan & Dui, Hongyan & Xing, Liudong, 2021. "Importance measure-based maintenance optimization strategy for pod slewing system," Reliability Engineering and System Safety, Elsevier, vol. 216(C).

    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. Vu, Hai Canh & Do, Phuc & Fouladirad, Mitra & Grall, Antoine, 2020. "Dynamic opportunistic maintenance planning for multi-component redundant systems with various types of opportunities," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    2. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    3. Wu, Tianyi & Yang, Li & Ma, Xiaobing & Zhang, Zihan & Zhao, Yu, 2020. "Dynamic maintenance strategy with iteratively updated group information," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    4. Zhou, Xiaojun & Yu, Mengqi, 2020. "Semi-dynamic maintenance scheduling for multi-station series systems in multi-specification and small-batch production," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    5. McMorland, J. & Collu, M. & McMillan, D. & Carroll, J. & Coraddu, A., 2023. "Opportunistic maintenance for offshore wind: A review and proposal of future framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    6. Wang, Yifei & He, Rui & Tian, Zhigang, 2023. "Opportunistic condition-based maintenance optimization for electrical distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    7. Zhu, Mixin & Zhou, Xiaojun, 2023. "Hybrid opportunistic maintenance policy for serial-parallel multi-station manufacturing systems with spare part overlap," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    8. Lu, Biao & Zhou, Xiaojun, 2017. "Opportunistic preventive maintenance scheduling for serial-parallel multistage manufacturing systems with multiple streams of deterioration," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 116-127.
    9. Liu, Gehui & Chen, Shaokuan & Ho, Tinkin & Ran, Xinchen & Mao, Baohua & Lan, Zhen, 2022. "Optimum opportunistic maintenance schedule over variable horizons considering multi-stage degradation and dynamic strategy," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    10. 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.
    11. He, Rui & Tian, Zhigang & Wang, Yifei & Zuo, Mingjian & Guo, Ziwei, 2023. "Condition-based maintenance optimization for multi-component systems considering prognostic information and degraded working efficiency," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    12. Wang, Jinhe & Zhang, Xiaohong & Zeng, Jianchao & Zhang, Yunzheng, 2020. "Joint external and internal opportunistic optimisation for wind turbine considering wind velocity," Renewable Energy, Elsevier, vol. 159(C), pages 380-398.
    13. Aseem K. Mishra & Divya Shrivastava & Prem Vrat, 2020. "An opportunistic group maintenance model for the multi-unit series system employing Jaya algorithm," OPSEARCH, Springer;Operational Research Society of India, vol. 57(2), pages 603-628, June.
    14. Dui, Hongyan & Tian, Tianzi & Wu, Shaomin & Xie, Min, 2023. "A cost-informed component maintenance index and its applications," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    15. Fecarotti, Claudia & Andrews, John & Pesenti, Raffaele, 2021. "A mathematical programming model to select maintenance strategies in railway networks," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    16. Truong Ba, H. & Cholette, M.E. & Borghesani, P. & Zhou, Y. & Ma, L., 2017. "Opportunistic maintenance considering non-homogenous opportunity arrivals and stochastic opportunity durations," Reliability Engineering and System Safety, Elsevier, vol. 160(C), pages 151-161.
    17. Urbani, Michele & Brunelli, Matteo & Punkka, Antti, 2023. "An approach for bi-objective maintenance scheduling on a networked system with limited resources," European Journal of Operational Research, Elsevier, vol. 305(1), pages 101-113.
    18. Do, Phuc & Assaf, Roy & Scarf, Phil & Iung, Benoit, 2019. "Modelling and application of condition-based maintenance for a two-component system with stochastic and economic dependencies," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 86-97.
    19. Li, Yao & He, Yihai & Ai, Jun & Wang, Chengcheng & Han, Xiao & Liao, Ruoyu & Yang, Xiuzhen, 2022. "Functional health prognosis approach of multi-station manufacturing system considering coupling operational factors," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    20. Izquierdo, J. & Márquez, A. Crespo & Uribetxebarria, J. & Erguido, A., 2020. "On the importance of assessing the operational context impact on maintenance management for life cycle cost of wind energy projects," Renewable Energy, Elsevier, vol. 153(C), pages 1100-1110.

    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:reensy:v:215:y:2021:i:c:s0951832021003495. 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: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.