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A novel approach for modelling complex maintenance systems using discrete event simulation

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  • Alrabghi, Abdullah
  • Tiwari, Ashutosh

Abstract

Existing approaches for modelling maintenance rely on oversimplified assumptions which prevent them from reflecting the complexity found in industrial systems. In this paper, we propose a novel approach that enables the modelling of non-identical multi-unit systems without restrictive assumptions on the number of units or their maintenance characteristics. Modelling complex interactions between maintenance strategies and their effects on assets in the system is achieved by accessing event queues in Discrete Event Simulation (DES). The approach utilises the wide success DES has achieved in manufacturing by allowing integration with models that are closely related to maintenance such as production and spare parts systems. Additional advantages of using DES include rapid modelling and visual interactive simulation. The proposed approach is demonstrated in a simulation based optimisation study of a published case. The current research is one of the first to optimise maintenance strategies simultaneously with their parameters while considering production dynamics and spare parts management. The findings of this research provide insights for non-conflicting objectives in maintenance systems. In addition, the proposed approach can be used to facilitate the simulation and optimisation of industrial maintenance systems.

Suggested Citation

  • Alrabghi, Abdullah & Tiwari, Ashutosh, 2016. "A novel approach for modelling complex maintenance systems using discrete event simulation," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 160-170.
    • Handle: RePEc:eee:reensy:v:154:y:2016:i:c:p:160-170
    DOI: 10.1016/j.ress.2016.06.003
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    References listed on IDEAS

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    1. Robin P. Nicolai & Rommert Dekker, 2008. "Optimal Maintenance of Multi-component Systems: A Review," Springer Series in Reliability Engineering, in: Complex System Maintenance Handbook, chapter 11, pages 263-286, Springer.
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    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. Van Horenbeek, Adriaan & Buré, Jasmine & Cattrysse, Dirk & Pintelon, Liliane & Vansteenwegen, Pieter, 2013. "Joint maintenance and inventory optimization systems: A review," International Journal of Production Economics, Elsevier, vol. 143(2), pages 499-508.
    6. Jahangirian, Mohsen & Eldabi, Tillal & Naseer, Aisha & Stergioulas, Lampros K. & Young, Terry, 2010. "Simulation in manufacturing and business: A review," European Journal of Operational Research, Elsevier, vol. 203(1), pages 1-13, May.
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    Cited by:

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    2. Jyrki Savolainen & Michele Urbani, 2021. "Maintenance optimization for a multi-unit system with digital twin simulation," Journal of Intelligent Manufacturing, Springer, vol. 32(7), pages 1953-1973, October.
    3. Zahedi-Hosseini, Farhad & Scarf, Philip & Syntetos, Aris, 2017. "Joint optimisation of inspection maintenance and spare parts provisioning: a comparative study of inventory policies using simulation and survey data," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 306-316.
    4. Wakiru, James M. & Pintelon, Liliane & Muchiri, Peter N. & Chemweno, Peter K., 2019. "A simulation-based optimization approach evaluating maintenance and spare parts demand interaction effects," International Journal of Production Economics, Elsevier, vol. 208(C), pages 329-342.
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    6. Wakiru, James & Pintelon, Liliane & Muchiri, Peter N. & Chemweno, Peter K. & Mburu, Stanley, 2020. "Towards an innovative lubricant condition monitoring strategy for maintenance of ageing multi-unit systems," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    7. Moura, Márcio das Chagas & Santana, João Mateus & Droguett, Enrique López & Lins, Isis Didier & Guedes, Bruno Nunes, 2017. "Analysis of extended warranties for medical equipment: A Stackelberg game model using priority queues," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 338-354.
    8. 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.
    9. Hu, Yang & Miao, Xuewen & Si, Yong & Pan, Ershun & Zio, Enrico, 2022. "Prognostics and health management: A review from the perspectives of design, development and decision," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    10. Özgür-Ünlüakın, Demet & Türkali, Busenur, 2021. "Evaluation of proactive maintenance policies on a stochastically dependent hidden multi-component system using DBNs," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    11. 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.
    12. Aizpurua, J.I. & Catterson, V.M. & Papadopoulos, Y. & Chiacchio, F. & D'Urso, D., 2017. "Supporting group maintenance through prognostics-enhanced dynamic dependability prediction," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 171-188.
    13. Leoni, Leonardo & De Carlo, Filippo & Tucci, Mario, 2023. "Developing a framework for generating production-dependent failure rate through discrete-event simulation," International Journal of Production Economics, Elsevier, vol. 266(C).

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