IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v231y2017i5p558-572.html
   My bibliography  Save this article

Benefit and customer demand approach for maintenance optimization of complex systems using Bayesian networks

Author

Listed:
  • El Hassene Ait Mokhtar
  • Radouane Laggoune
  • Alaa Chateauneuf

Abstract

The satisfaction of client needs is the goal of most of the industrial systems, which can be achieved by appropriate life-cycle management. When it concerns complex real-world systems, the difficulty of managing their life-cycle increases with increasing of the links and interactions between the system components and between the system and its environment. Therefore, the need of addressing a complete and realistic maintenance planning approach to face these difficulties is crucial. This article presents a methodology for maintenance optimization of complex systems using Bayesian networks. In this methodology, the objective function, which aims at maximizing the system benefit, allows conciliating between two contradictory objectives: reducing the maintenance costs and reaching an availability target fixed according to the customer demand. The Bayesian networks are used to take into account the system interactions, while the maintenance policy, which is based on the imperfect preventive maintenance and considers several efficiency levels, is used to build a realistic maintenance planning model. An application to a water supply system is included to illustrate the benefit and the effectiveness of the proposed approach.

Suggested Citation

  • El Hassene Ait Mokhtar & Radouane Laggoune & Alaa Chateauneuf, 2017. "Benefit and customer demand approach for maintenance optimization of complex systems using Bayesian networks," Journal of Risk and Reliability, , vol. 231(5), pages 558-572, October.
  • Handle: RePEc:sae:risrel:v:231:y:2017:i:5:p:558-572
    DOI: 10.1177/1748006X17716314
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X17716314
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1748006X17716314?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. Jones, B. & Jenkinson, I. & Yang, Z. & Wang, J., 2010. "The use of Bayesian network modelling for maintenance planning in a manufacturing industry," Reliability Engineering and System Safety, Elsevier, vol. 95(3), pages 267-277.
    2. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    3. Laggoune, Radouane & Chateauneuf, Alaa & Aissani, Djamil, 2010. "Impact of few failure data on the opportunistic replacement policy for multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 95(2), pages 108-119.
    4. Langseth, Helge & Portinale, Luigi, 2007. "Bayesian networks in reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 92-108.
    5. Godoy, David R. & Pascual, Rodrigo & Knights, Peter, 2014. "A decision-making framework to integrate maintenance contract conditions with critical spares management," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 102-108.
    6. El Hassene Ait Mokhtar & Radouane Laggoune & Alaa Chateauneuf, 2016. "Utility-Based Maintenance Optimization for Complex Water-Distribution Systems Using Bayesian Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4153-4170, September.
    7. Chiang, Cheng-Hsiung & Chen, Liang-Hsuan, 2007. "Availability allocation and multi-objective optimization for parallel-series systems," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1231-1244, August.
    8. Simon, C. & Weber, P. & Evsukoff, A., 2008. "Bayesian networks inference algorithm to implement Dempster Shafer theory in reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 950-963.
    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. El Hassene Ait Mokhtar & Radouane Laggoune & Alaa Chateauneuf, 2016. "Utility-Based Maintenance Optimization for Complex Water-Distribution Systems Using Bayesian Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4153-4170, September.
    2. 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).
    3. N. Knofius & M. C. Heijden & A. Sleptchenko & W. H. M. Zijm, 2021. "Improving effectiveness of spare parts supply by additive manufacturing as dual sourcing option," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 189-221, March.
    4. Wang, Wenbin, 2012. "An overview of the recent advances in delay-time-based maintenance modelling," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 165-178.
    5. Oakley, Jordan L. & Wilson, Kevin J. & Philipson, Pete, 2022. "A condition-based maintenance policy for continuously monitored multi-component systems with economic and stochastic dependence," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    6. de Jonge, Bram & Dijkstra, Arjan S. & Romeijnders, Ward, 2015. "Cost benefits of postponing time-based maintenance under lifetime distribution uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 140(C), pages 15-21.
    7. 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.
    8. Lei Jiang & Yiliu Liu & Xiaomin Wang & Mary Ann Lundteigen, 2019. "Operation-oriented reliability and availability evaluation for onboard high-speed train control system with dynamic Bayesian network," Journal of Risk and Reliability, , vol. 233(3), pages 455-469, June.
    9. Cai, Baoping & Liu, Yonghong & Liu, Zengkai & Tian, Xiaojie & Dong, Xin & Yu, Shilin, 2012. "Using Bayesian networks in reliability evaluation for subsea blowout preventer control system," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 32-41.
    10. Zhang, Xiaohong & Zeng, Jianchao, 2015. "A general modeling method for opportunistic maintenance modeling of multi-unit systems," Reliability Engineering and System Safety, Elsevier, vol. 140(C), pages 176-190.
    11. Zhang, Xiaoge & Mahadevan, Sankaran & Deng, Xinyang, 2017. "Reliability analysis with linguistic data: An evidential network approach," Reliability Engineering and System Safety, Elsevier, vol. 162(C), pages 111-121.
    12. Chemweno, Peter & Pintelon, Liliane & Van Horenbeek, Adriaan & Muchiri, Peter, 2015. "Development of a risk assessment selection methodology for asset maintenance decision making: An analytic network process (ANP) approach," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 663-676.
    13. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    14. Sahu, Atma Ram & Palei, Sanjay Kumar, 2022. "Fault analysis of dragline subsystem using Bayesian network model," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    15. Baoping Cai & Yonghong Liu & Zengkai Liu & Xiaojie Tian & Yanzhen Zhang & Renjie Ji, 2013. "Application of Bayesian Networks in Quantitative Risk Assessment of Subsea Blowout Preventer Operations," Risk Analysis, John Wiley & Sons, vol. 33(7), pages 1293-1311, July.
    16. Medina-Oliva, G. & Weber, P. & Iung, B., 2013. "PRM-based patterns for knowledge formalisation of industrial systems to support maintenance strategies assessment," Reliability Engineering and System Safety, Elsevier, vol. 116(C), pages 38-56.
    17. Hashemi, M. & Asadi, M. & Zarezadeh, S., 2020. "Optimal maintenance policies for coherent systems with multi-type components," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    18. Chuan Wang & Yupeng Liu & Wen Hou & Chao Yu & Guorong Wang & Yuyan Zheng, 2021. "Reliability and availability modeling of Subsea Autonomous High Integrity Pressure Protection System with partial stroke test by Dynamic Bayesian," Journal of Risk and Reliability, , vol. 235(2), pages 268-281, April.
    19. 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.
    20. Coria, V.H. & Maximov, S. & Rivas-Dávalos, F. & Melchor, C.L. & Guardado, J.L., 2015. "Analytical method for optimization of maintenance policy based on available system failure data," Reliability Engineering and System Safety, Elsevier, vol. 135(C), pages 55-63.

    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:231:y:2017:i:5:p:558-572. 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.