IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v238y2024i4p754-763.html
   My bibliography  Save this article

Optimal condition based maintenance using attribute Bayesian control chart

Author

Listed:
  • Hasan Rasay
  • Seyed Mohammad Hadian
  • Farnoosh Naderkhani
  • Fariba Azizi

Abstract

Condition-based maintenance (CBM) has been emerged as a relatively new trend in maintenance management. Instead of conducting preventive maintenance actions in specified time intervals, the CBM program collects information through condition monitoring, then recommends maintenance actions based on the observed data. On the other hand, Bayesian control charts use the posterior probability of being the system in an unhealthy state as the chart statistic. An attribute Bayesian control chart is employed in this study to monitor a deteriorating system and plan CBM actions based on a continuous-time homogeneous Markov chain. The system consists of three states: healthy, unhealthy, and failure states. A partially observable Markov decision process (POMDP) is developed, which optimally determines the sample size, sampling interval, and warning limit to minimize the long-term expected cost per time unit. Numerical examples and sensitivity analyses are conducted to clarify the performance of the proposed attribute control chart. To the best of the authors’ knowledge, this is the first study of the applications of attribute Bayesian control charts in condition-based maintenance.

Suggested Citation

  • Hasan Rasay & Seyed Mohammad Hadian & Farnoosh Naderkhani & Fariba Azizi, 2024. "Optimal condition based maintenance using attribute Bayesian control chart," Journal of Risk and Reliability, , vol. 238(4), pages 754-763, August.
  • Handle: RePEc:sae:risrel:v:238:y:2024:i:4:p:754-763
    DOI: 10.1177/1748006X231174960
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X231174960
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1748006X231174960?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. Linderman, Kevin & McKone-Sweet, Kathleen E. & Anderson, John C., 2005. "An integrated systems approach to process control and maintenance," European Journal of Operational Research, Elsevier, vol. 164(2), pages 324-340, July.
    2. Olde Keizer, Minou C.A. & Teunter, Ruud H. & Veldman, Jasper & Babai, M. Zied, 2018. "Condition-based maintenance for systems with economic dependence and load sharing," International Journal of Production Economics, Elsevier, vol. 195(C), pages 319-327.
    3. Wu, Jianmou & Makis, Viliam, 2008. "Economic and economic-statistical design of a chi-square chart for CBM," European Journal of Operational Research, Elsevier, vol. 188(2), pages 516-529, July.
    4. 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.
    5. Kuo, Yarlin, 2006. "Optimal adaptive control policy for joint machine maintenance and product quality control," European Journal of Operational Research, Elsevier, vol. 171(2), pages 586-597, June.
    6. Wang, Wenbin, 2012. "A simulation-based multivariate Bayesian control chart for real time condition-based maintenance of complex systems," European Journal of Operational Research, Elsevier, vol. 218(3), pages 726-734.
    7. Panagiotidou, Sofia & Nenes, George, 2009. "An economically designed, integrated quality and maintenance model using an adaptive Shewhart chart," Reliability Engineering and System Safety, Elsevier, vol. 94(3), pages 732-741.
    8. Jue Wang & Chi-Guhn Lee, 2015. "Multistate Bayesian Control Chart Over a Finite Horizon," Operations Research, INFORMS, vol. 63(4), pages 949-964, August.
    9. Makis, Viliam, 2009. "Multivariate Bayesian process control for a finite production run," European Journal of Operational Research, Elsevier, vol. 194(3), pages 795-806, May.
    10. Michael Jong Kim & Viliam Makis, 2013. "Joint Optimization of Sampling and Control of Partially Observable Failing Systems," Operations Research, INFORMS, vol. 61(3), pages 777-790, June.
    11. Nadia Bahria & Anis Chelbi & Hanen Bouchriha & Imen Harbaoui Dridi, 2019. "Integrated production, statistical process control, and maintenance policy for unreliable manufacturing systems," International Journal of Production Research, Taylor & Francis Journals, vol. 57(8), pages 2548-2570, April.
    12. Kim, Michael Jong & Jiang, Rui & Makis, Viliam & Lee, Chi-Guhn, 2011. "Optimal Bayesian fault prediction scheme for a partially observable system subject to random failure," European Journal of Operational Research, Elsevier, vol. 214(2), pages 331-339, October.
    13. Hasan Rasay & Mohammad Saber Fallahnezhad & Yahia Zaremehrjerdi, 2019. "An integrated model of statistical process control and maintenance planning for a two-stage dependent process under general deterioration," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 13(2), pages 149-177.
    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. Kampitsis, Dimitris & Panagiotidou, Sofia, 2022. "A Bayesian condition-based maintenance and monitoring policy with variable sampling intervals," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    2. Liu, Liping & Yu, Miaomiao & Ma, Yizhong & Tu, Yiliu, 2013. "Economic and economic-statistical designs of an X¯ control chart for two-unit series systems with condition-based maintenance," European Journal of Operational Research, Elsevier, vol. 226(3), pages 491-499.
    3. Xiang, Yisha, 2013. "Joint optimization of X¯ control chart and preventive maintenance policies: A discrete-time Markov chain approach," European Journal of Operational Research, Elsevier, vol. 229(2), pages 382-390.
    4. Zhou, Wenhui & Zheng, Zhibin & Xie, Wei, 2017. "A control-chart-based queueing approach for service facility maintenance with energy-delay tradeoff," European Journal of Operational Research, Elsevier, vol. 261(2), pages 613-625.
    5. Yin, Hui & Zhang, Guojun & Zhu, Haiping & Deng, Yuhao & He, Fei, 2015. "An integrated model of statistical process control and maintenance based on the delayed monitoring," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 323-333.
    6. Ho, Linda Lee & Quinino, Roberto C., 2012. "Integrating on-line process control and imperfect corrective maintenance: An economical design," European Journal of Operational Research, Elsevier, vol. 222(2), pages 253-262.
    7. Liping Liu & Lining Jiang & Ding Zhang, 2017. "An integrated model of statistical process control and condition-based maintenance for deteriorating systems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(11), pages 1452-1460, November.
    8. Azizi, Fariba & Salari, Nooshin, 2023. "A novel condition-based maintenance framework for parallel manufacturing systems based on bivariate birth/birth–death processes," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    9. Chiel van Oosterom & Lisa M. Maillart & Jeffrey P. Kharoufeh, 2017. "Optimal maintenance policies for a safety‐critical system and its deteriorating sensor," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(5), pages 399-417, August.
    10. Azimpoor, Samareh & Taghipour, Sharareh, 2021. "Joint inspection and product quality optimization for a system with delayed failure," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    11. Panagiotidou, S. & Tagaras, G., 2012. "Optimal integrated process control and maintenance under general deterioration," Reliability Engineering and System Safety, Elsevier, vol. 104(C), pages 58-70.
    12. 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).
    13. Jue Wang, 2016. "Minimizing the false alarm rate in systems with transient abnormality," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(4), pages 320-334, June.
    14. Ho, Linda Lee & Trindade, Anderson Laécio Galindo, 2009. "Economic design of an X chart for short-run production," International Journal of Production Economics, Elsevier, vol. 120(2), pages 613-624, August.
    15. Uit Het Broek, Michiel A.J. & Teunter, Ruud H. & de Jonge, Bram & Veldman, Jasper, 2021. "Joint condition-based maintenance and load-sharing optimization for two-unit systems with economic dependency," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1119-1131.
    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. Petchrompo, Sanyapong & Parlikad, Ajith Kumar, 2019. "A review of asset management literature on multi-asset systems," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 181-201.
    18. Yang, Li & Ye, Zhi-sheng & Lee, Chi-Guhn & Yang, Su-fen & Peng, Rui, 2019. "A two-phase preventive maintenance policy considering imperfect repair and postponed replacement," European Journal of Operational Research, Elsevier, vol. 274(3), pages 966-977.
    19. Rui Jiang & Michael Kim & Viliam Makis, 2012. "A Bayesian model and numerical algorithm for CBM availability maximization," Annals of Operations Research, Springer, vol. 196(1), pages 333-348, July.
    20. Huda, Shamsul & Abdollahian, Mali & Mammadov, Musa & Yearwood, John & Ahmed, Shafiq & Sultan, Ibrahim, 2014. "A hybrid wrapper–filter approach to detect the source(s) of out-of-control signals in multivariate manufacturing process," European Journal of Operational Research, Elsevier, vol. 237(3), pages 857-870.

    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:238:y:2024:i:4:p:754-763. 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.