IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v30y2016i12d10.1007_s11269-016-1412-9.html
   My bibliography  Save this article

Utility-Based Maintenance Optimization for Complex Water-Distribution Systems Using Bayesian Networks

Author

Listed:
  • El Hassene Ait Mokhtar

    (Université de Bejaia)

  • Radouane Laggoune

    (Université de Bejaia)

  • Alaa Chateauneuf

    (Université Clermont Auvergne, Université Blaise Pascal, Institut Pascal
    CNRS, UMR 6602, Institut Pascal)

Abstract

Water supply systems (WSS), as well as other real-world systems, are characterized by complex configurations. For these systems, it is essential to ensure appropriate utility through optimal maintenance planning. The difficulties in decision-making are much increased by lack of information regarding the operation and failure conditions. When maintenance optimization is considered for systems configured as networks, comprising a large number of components, the main challenge is to model the reliability characteristics, such as availability, taking account of the interactions and dependencies between different components. The aim of this paper is to provide an optimal Preventive Maintenance (PM) plan with a view to maximizing the utility of a complex repairable system using Bayesian Networks (BNs). For each node of the BN, the optimal PM periodicity is obtained, in accordance with the policy of periodic imperfect PM with minimal repair at failure. The system availability is then computed, by Bayesian inference, for various combinations of nodes, or subsystems, periodicities and partial renewals before the complete renewal of the whole system. A utility function is then introduced to provide the maintenance plan for the system, leading to the implementation of the best policy. The methodology is illustrated by numerical application on WSS.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:waterr:v:30:y:2016:i:12:d:10.1007_s11269-016-1412-9
    DOI: 10.1007/s11269-016-1412-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-016-1412-9
    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/s11269-016-1412-9?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. 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. Muller, Alexandre & Suhner, Marie-Christine & Iung, Benoît, 2008. "Formalisation of a new prognosis model for supporting proactive maintenance implementation on industrial system," Reliability Engineering and System Safety, Elsevier, vol. 93(2), pages 234-253.
    3. Muhammad Al-Zahrani & Amin Abo-Monasar, 2015. "Urban Residential Water Demand Prediction Based on Artificial Neural Networks and Time Series Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3651-3662, August.
    4. Flavio Trojan & Danielle Morais, 2015. "Maintenance Management Decision Model for Reduction of Losses in Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3459-3479, August.
    5. Symeon Christodoulou, 2011. "Water Network Assessment and Reliability Analysis by Use of Survival Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(4), pages 1229-1238, March.
    6. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    7. Sou-Sen Leu & Quang-Nha Bui, 2016. "Leak Prediction Model for Water Distribution Networks Created Using a Bayesian Network Learning Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2719-2733, June.
    8. Janez Sušnik & Jose-Luis Molina & Lydia Vamvakeridou-Lyroudia & Dragan Savić & Zoran Kapelan, 2013. "Comparative Analysis of System Dynamics and Object-Oriented Bayesian Networks Modelling for Water Systems Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(3), pages 819-841, February.
    9. Langseth, Helge & Portinale, Luigi, 2007. "Bayesian networks in reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 92-108.
    10. 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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Leydiana Sousa Pereira & Danielle Costa Morais, 2020. "Multicriteria Decision Model to Establish Maintenance Priorities for Wells in a Groundwater System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(1), pages 377-392, January.

    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, 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.
    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. 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.
    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. 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.
    6. Rebello, Sinda & Yu, Hongyang & Ma, Lin, 2018. "An integrated approach for system functional reliability assessment using Dynamic Bayesian Network and Hidden Markov Model," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 124-135.
    7. 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.
    8. 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.
    9. Özgür-Ünlüakın, Demet & Türkali, Busenur & Karacaörenli, Ayşe & Çağlar Aksezer, S., 2019. "A DBN based reactive maintenance model for a complex system in thermal power plants," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    10. 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.
    11. Alessandro Pagano & Raffaele Giordano & Ivan Portoghese & Umberto Fratino & Michele Vurro, 2014. "A Bayesian vulnerability assessment tool for drinking water mains under extreme events," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(3), pages 2193-2227, December.
    12. Meysam MALEKI & Virgilio CRUZ MACHADO, 2013. "Generic Integration of Lean, Agile, Resilient, and Green Practices in Automotive Supply Chain," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 14(2), pages 237-248, May.
    13. González, Esteban Le Maitre & Desforges, Xavier & Archimède, Bernard, 2018. "Assessment method of the multicomponent systems future ability to achieve productive tasks from local prognoses," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 403-415.
    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. Prabal Das & D. A. Sachindra & Kironmala Chanda, 2022. "Machine Learning-Based Rainfall Forecasting with Multiple Non-Linear Feature Selection Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 6043-6071, December.
    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. Agathoklis Agathokleous & Chrystalleni Christodoulou & Symeon E. Christodoulou, 2017. "Topological Robustness and Vulnerability Assessment of Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(12), pages 4007-4021, September.

    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:waterr:v:30:y:2016:i:12:d:10.1007_s11269-016-1412-9. 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.