IDEAS home Printed from https://ideas.repec.org/a/spr/jsched/v27y2024i1d10.1007_s10951-023-00800-x.html
   My bibliography  Save this article

Scheduling the repair and replacement of individual components in operating systems: a bi-objective mathematical optimization model

Author

Listed:
  • Gabrijela Obradović

    (Chalmers University of Technology and University of Gothenburg)

  • Ann-Brith Strömberg

    (Chalmers University of Technology and University of Gothenburg)

  • Kristian Lundberg

    (Saab AB)

Abstract

Preventive maintenance (PM) is performed so that failure is avoided while corrective maintenance is performed after a failure has occurred in order to restore the system back to an operational state. This research aims at scheduling PM activities for a multi-component system within a finite time horizon. We consider a setting with two stakeholders, being the system operator and the maintenance workshop, and two different contract types governing their joint activities, namely an availability contract and a turn-around time contract. Components in the systems that are to be maintained are sent to the maintenance workshop, which needs to schedule and perform all maintenance activities while at the same time satisfying the contract and not exceeding the workshop capacity. Our modelling is based on a mixed-binary linear optimization model of a PM scheduling problem with so-called interval costs over a finite and discretized time horizon. We enhance this scheduling model with the flow of individual components through the maintenance workshop, including stocks of spare components, both those components that need repair and the repaired ones. The resulting scheduling model is then utilized in the optimization of two main contracts, namely maximizing the availability of repaired (or new) components and minimizing the deviation from the contracted turn-around times for the components in the maintenance loop. Each of these objectives is combined with the objective to minimize the costs for maintenance of the operating system, leading to two bi-objective optimization problems. We analyse the two contracting forms between the stakeholders by studying and comparing the Pareto fronts resulting from different parameter settings, regarding minimum allowed stock levels and investments in repair capacity of the workshop. Our bi-objective mixed-binary linear optimization model is able to capture important properties of the results from the contracting forms as well as to show that, in our setting, an availability contract performs better than a turn-around time contract in terms of tractability.

Suggested Citation

  • Gabrijela Obradović & Ann-Brith Strömberg & Kristian Lundberg, 2024. "Scheduling the repair and replacement of individual components in operating systems: a bi-objective mathematical optimization model," Journal of Scheduling, Springer, vol. 27(1), pages 87-101, February.
    • Handle: RePEc:spr:jsched:v:27:y:2024:i:1:d:10.1007_s10951-023-00800-x
    DOI: 10.1007/s10951-023-00800-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10951-023-00800-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10951-023-00800-x?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Gavranis, Andreas & Kozanidis, George, 2015. "An exact solution algorithm for maximizing the fleet availability of a unit of aircraft subject to flight and maintenance requirements," European Journal of Operational Research, Elsevier, vol. 242(2), pages 631-643.
    2. Lin, Boliang & Wu, Jianping & Lin, Ruixi & Wang, Jiaxi & Wang, Hui & Zhang, Xuhui, 2019. "Optimization of high-level preventive maintenance scheduling for high-speed trains," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 261-275.
    Full references (including those not matched with items on IDEAS)

    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. Gabrijela Obradović & Ann-Brith Strömberg & Kristian Lundberg, 2023. "Simultaneous scheduling of replacement and repair of common components in operating systems," Annals of Operations Research, Springer, vol. 322(1), pages 147-165, March.
    2. Zhang, Fengxia & Shen, Jingyuan & Liao, Haitao & Ma, Yizhong, 2021. "Optimal preventive maintenance policy for a system subject to two-phase imperfect inspections," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    3. Lin, Boliang & Zhao, Yinan, 2021. "Synchronized optimization of EMU train assignment and second-level preventive maintenance scheduling," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    4. Zhao, Xian & Dai, Ying & Qiu, Qingan & Wu, Yaguang, 2022. "Joint optimization of mission aborts and allocation of standby components considering mission loss," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    5. Cheng, Ruijun & Cheng, Yu & Chen, Dewang & Song, Haifeng, 2021. "Online quantitative safety monitoring approach for unattended train operation system considering stochastic factors," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    6. Carlos Lagos & Felipe Delgado & Mathias A. Klapp, 2020. "Dynamic Optimization for Airline Maintenance Operations," Transportation Science, INFORMS, vol. 54(4), pages 998-1015, July.
    7. Levitin, Gregory & Xing, Liudong & Dai, Yanshun, 2022. "Minimum cost replacement and maintenance scheduling in dual-dissimilar-unit standby systems," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    8. Feng, Qiang & Bi, Xiong & Zhao, Xiujie & Chen, Yiran & Sun, Bo, 2017. "Heuristic hybrid game approach for fleet condition-based maintenance planning," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 166-176.
    9. Fei Peng & Xian Fan & Puxin Wang & Mingan Sheng, 2022. "A Time-Space Network-Based Optimization Method for Scheduling Depot Drivers," Sustainability, MDPI, vol. 14(21), pages 1-19, November.
    10. Zhang, Qin & Liu, Yu & Xiahou, Tangfan & Huang, Hong-Zhong, 2023. "A heuristic maintenance scheduling framework for a military aircraft fleet under limited maintenance capacities," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    11. Khaled Alhamad & Yousuf Alkhezi & M. F. Alhajri, 2022. "Nonlinear Integer Programming for Solving Preventive Maintenance Scheduling Problem for Cogeneration Plants with Production," Sustainability, MDPI, vol. 15(1), pages 1-18, December.
    12. Wang, Jiaxi, 2024. "Maintenance scheduling at high-speed train depots: An optimization approach," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    13. Zhang, Fengxia & Shen, Jingyuan & Ma, Yizhong, 2020. "Optimal maintenance policy considering imperfect repairs and non-constant probabilities of inspection errors," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    14. 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.
    15. Niu, Jiaxin & Qiao, Ke & Zhao, Peng, 2025. "Reliability improvement of rolling stock planning with maintenance requirements for high-speed railway," Reliability Engineering and System Safety, Elsevier, vol. 259(C).
    16. Oszczypała, Mateusz & Konwerski, Jakub & Ziółkowski, Jarosław & Małachowski, Jerzy, 2024. "Reliability analysis and redundancy optimization of k-out-of-n systems with random variable k using continuous time Markov chain and Monte Carlo simulation," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    17. Tao, Xin & Mårtensson, Jonas & Warnquist, Håkan & Pernestål, Anna, 2022. "Short-term maintenance planning of autonomous trucks for minimizing economic risk," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    18. Debroy, Arindam & Dadsena, Krishna Kumar & Bhattacharjee, Pushparenu & Verma, Anuj & Verma, Meenakshi, 2024. "Evaluating the inhibitors in the growth of high-speed railway in India: A multi-stakeholder perspective," Transport Policy, Elsevier, vol. 155(C), pages 93-109.
    19. Franco Peschiera & Robert Dell & Johannes Royset & Alain Haït & Nicolas Dupin & Olga Battaïa, 2021. "A novel solution approach with ML-based pseudo-cuts for the Flight and Maintenance Planning problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(3), pages 635-664, September.
    20. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2021. "Optimal operation and maintenance scheduling in m-out-of-n standby systems with reusable elements," Reliability Engineering and System Safety, Elsevier, vol. 211(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:spr:jsched:v:27:y:2024:i:1:d:10.1007_s10951-023-00800-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.