IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v235y2021i3p458-473.html
   My bibliography  Save this article

Maintenance policy structure investigation and optimisation of a complex production system with intermediate buffers

Author

Listed:
  • Yifan Zhou
  • Chao Yuan
  • Tian Ran Lin
  • Lin Ma

Abstract

Existing research about the maintenance optimisation of production systems with intermediate buffers largely assumed a series system structure. However, practical production systems often contain subsystems of ring structures, for example, rework and feedforward. The maintenance optimisation of these complex systems is difficult due to the complicated structure of maintenance policies and the large search space for optimisation. This paper proves the control limit property of the optimal condition-based maintenance policy. Based on the control limit property, approximate policy structures that incur a smaller policy space are proposed. Because the state space of a production system is often large, the objective function of the maintenance optimisation cannot be evaluated analytically. Consequently, a stochastic branch and bound (SB&B) algorithm embedding a sequential simulation procedure is proposed to determine a cost-efficient condition-based maintenance policy. Numerical studies show that the proposed maintenance policy structures can deliver a cost-efficient maintenance policy, and the performance of the SB&B algorithm is enhanced by the inclusion of a sequential simulation procedure.

Suggested Citation

  • Yifan Zhou & Chao Yuan & Tian Ran Lin & Lin Ma, 2021. "Maintenance policy structure investigation and optimisation of a complex production system with intermediate buffers," Journal of Risk and Reliability, , vol. 235(3), pages 458-473, June.
    • Handle: RePEc:sae:risrel:v:235:y:2021:i:3:p:458-473
    DOI: 10.1177/1748006X20968958
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X20968958
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1748006X20968958?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
    ---><---

    References listed on IDEAS

    as
    1. Elisa Gebennini & Andrea Grassi, 2015. "Discrete-time model for two-machine one-buffer transfer lines with buffer bypass and two capacity levels," IISE Transactions, Taylor & Francis Journals, vol. 47(7), pages 715-727, July.
    2. Belmansour, Ahmed-Tidjani & Nourelfath, Mustapha, 2010. "An aggregation method for performance evaluation of a tandem homogenous production line with machines having multiple failure modes," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1193-1201.
    3. Kyriakidis, E.G. & Dimitrakos, T.D., 2006. "Optimal preventive maintenance of a production system with an intermediate buffer," European Journal of Operational Research, Elsevier, vol. 168(1), pages 86-99, January.
    4. Karamatsoukis, C.C. & Kyriakidis, E.G., 2010. "Optimal maintenance of two stochastically deteriorating machines with an intermediate buffer," European Journal of Operational Research, Elsevier, vol. 207(1), pages 297-308, November.
    5. Alexandros, Diamantidis C. & Chrissoleon, Papadopoulos T., 2009. "Exact analysis of a two-workstation one-buffer flow line with parallel unreliable machines," European Journal of Operational Research, Elsevier, vol. 197(2), pages 572-580, September.
    6. Liu, Bin & Wu, Shaomin & Xie, Min & Kuo, Way, 2017. "A condition-based maintenance policy for degrading systems with age- and state-dependent operating cost," European Journal of Operational Research, Elsevier, vol. 263(3), pages 879-887.
    7. Ping-Chen Chang, 2019. "Reliability estimation for a stochastic production system with finite buffer storage by a simulation approach," Annals of Operations Research, Springer, vol. 277(1), pages 119-133, June.
    8. Barış Tan & Stanley Gershwin, 2011. "Modelling and analysis of Markovian continuous flow systems with a finite buffer," Annals of Operations Research, Springer, vol. 182(1), pages 5-30, January.
    9. Wendy Xu & Barry Nelson, 2013. "Empirical stochastic branch-and-bound for optimization via simulation," IISE Transactions, Taylor & Francis Journals, vol. 45(7), pages 685-698.
    10. Zhou, Yifan & Guo, Yiming & Lin, Tian Ran & Ma, Lin, 2018. "Maintenance optimisation of a series production system with intermediate buffers using a multi-agent FMDP," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 39-48.
    11. Marcello Colledani & Stanley Gershwin, 2013. "A decomposition method for approximate evaluation of continuous flow multi-stage lines with general Markovian machines," Annals of Operations Research, Springer, vol. 209(1), pages 5-40, October.
    12. Dimitrakos, T.D. & Kyriakidis, E.G., 2008. "A semi-Markov decision algorithm for the maintenance of a production system with buffer capacity and continuous repair times," International Journal of Production Economics, Elsevier, vol. 111(2), pages 752-762, February.
    13. Rivera-Gómez, Héctor & Gharbi, Ali & Kenné, Jean-Pierre & Montaño-Arango, Oscar & Hernández-Gress, Eva Selene, 2018. "Subcontracting strategies with production and maintenance policies for a manufacturing system subject to progressive deterioration," International Journal of Production Economics, Elsevier, vol. 200(C), pages 103-118.
    14. Chang, Ping-Chen & Lin, Yi-Kuei & Chiang, Yu-Min, 2019. "System reliability estimation and sensitivity analysis for multi-state manufacturing network with joint buffers––A simulation approach," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 103-109.
    15. Stanley B. Gershwin, 1987. "An Efficient Decomposition Method for the Approximate Evaluation of Tandem Queues with Finite Storage Space and Blocking," Operations Research, INFORMS, vol. 35(2), pages 291-305, April.
    16. Chuan Shi & Stanley B. Gershwin, 2016. "A segmentation approach for solving buffer allocation problems in large production systems," International Journal of Production Research, Taylor & Francis Journals, vol. 54(20), pages 6121-6141, October.
    17. Amos H.C. Ng & Sabry Shaaban & Jacob Bernedixen, 2017. "Studying unbalanced workload and buffer allocation of production systems using multi-objective optimisation," International Journal of Production Research, Taylor & Francis Journals, vol. 55(24), pages 7435-7451, December.
    18. Fitouhi, Mohamed-Chahir & Nourelfath, Mustapha & Gershwin, Stanley B., 2017. "Performance evaluation of a two-machine line with a finite buffer and condition-based maintenance," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 61-72.
    19. L. Jeff Hong & Barry L. Nelson & Jie Xu, 2015. "Discrete Optimization via Simulation," International Series in Operations Research & Management Science, in: Michael C Fu (ed.), Handbook of Simulation Optimization, edition 127, chapter 0, pages 9-44, Springer.
    20. Cheng, Guo Qing & Zhou, Bing Hai & Li, Ling, 2018. "Integrated production, quality control and condition-based maintenance for imperfect production systems," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 251-264.
    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. Zhou, Yifan & Guo, Yiming & Lin, Tian Ran & Ma, Lin, 2018. "Maintenance optimisation of a series production system with intermediate buffers using a multi-agent FMDP," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 39-48.
    2. Zhang, Ning & Qi, Faqun & Zhang, Chengjie & Zhou, Hongming, 2022. "Joint optimization of condition-based maintenance policy and buffer capacity for a two-unit series system," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    3. Kiesmüller, G.P. & Sachs, F.E., 2020. "Spare parts or buffer? How to design a transfer line with unreliable machines," European Journal of Operational Research, Elsevier, vol. 284(1), pages 121-134.
    4. Dehayem Nodem, F.I. & Kenné, J.P. & Gharbi, A., 2011. "Simultaneous control of production, repair/replacement and preventive maintenance of deteriorating manufacturing systems," International Journal of Production Economics, Elsevier, vol. 134(1), pages 271-282, November.
    5. Ziwei Lin & Nicla Frigerio & Andrea Matta & Shichang Du, 2021. "Multi-fidelity surrogate-based optimization for decomposed buffer allocation problems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 223-253, March.
    6. Maria Chiara Magnanini & Tullio Tolio, 2020. "Switching- and hedging- point policy for preventive maintenance with degrading machines: application to a two-machine line," Flexible Services and Manufacturing Journal, Springer, vol. 32(2), pages 241-271, June.
    7. Fitouhi, Mohamed-Chahir & Nourelfath, Mustapha & Gershwin, Stanley B., 2017. "Performance evaluation of a two-machine line with a finite buffer and condition-based maintenance," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 61-72.
    8. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    9. Shuyuan Gan & Bolun Wang & Zhifang Song, 2021. "A Combined Maintenance Strategy Considering Spares, Buffer, and Quality," Journal of Risk and Reliability, , vol. 235(3), pages 431-445, June.
    10. Ünsal Özdoğru & Tayfur Altiok, 2015. "Continuous material flow systems: analysis of marine ports handling bulk materials," Annals of Operations Research, Springer, vol. 231(1), pages 79-104, August.
    11. Boumallessa, Zeineb & Chouikhi, Houssam & Elleuch, Mounir & Bentaher, Hatem, 2023. "Modeling and optimizing the maintenance schedule using dynamic quality and machine condition monitors in an unreliable single production system," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    12. Chang, Ping-Chen, 2022. "MC-based simulation approach for two-terminal multi-state network reliability evaluation without knowing d-MCs," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    13. Berthaut, F. & Gharbi, A. & Kenné, J.-P. & Boulet, J.-F., 2010. "Improved joint preventive maintenance and hedging point policy," International Journal of Production Economics, Elsevier, vol. 127(1), pages 60-72, September.
    14. Ait-El-Cadi, Abdessamad & Gharbi, Ali & Dhouib, Karem & Artiba, Abdelhakim, 2021. "Integrated production, maintenance and quality control policy for unreliable manufacturing systems under dynamic inspection," International Journal of Production Economics, Elsevier, vol. 236(C).
    15. Karamatsoukis, C.C. & Kyriakidis, E.G., 2010. "Optimal maintenance of two stochastically deteriorating machines with an intermediate buffer," European Journal of Operational Research, Elsevier, vol. 207(1), pages 297-308, November.
    16. 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).
    17. Gao, Kaiye & Peng, Rui & Qu, Li & Wu, Shaomin, 2020. "Jointly optimizing lot sizing and maintenance policy for a production system with two failure modes," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    18. Gia-Shie Liu, 2019. "A Group Replacement Decision Support System Based on Internet of Things," Mathematics, MDPI, vol. 7(9), pages 1-23, September.
    19. Zhang, Yongjin & Zhao, Ming & Zhang, Yanjun & Pan, Ruilin & Cai, Jing, 2020. "Dynamic and steady-state performance analysis for multi-state repairable reconfigurable manufacturing systems with buffers," European Journal of Operational Research, Elsevier, vol. 283(2), pages 491-510.
    20. Xiao Wang & Hongwei Wang & Chao Qi, 2016. "Multi-agent reinforcement learning based maintenance policy for a resource constrained flow line system," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 325-333, April.

    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:sae:risrel:v:235:y:2021:i:3:p:458-473. 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: SAGE Publications (email available below). General contact details of provider: .

    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.