IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v94y2009i9p1416-1421.html
   My bibliography  Save this article

Analyzing maintenance strategies by agent-based simulations: A feasibility study

Author

Listed:
  • Kaegi, M.
  • Mock, R.
  • Kröger, W.

Abstract

Thoroughly planned and implemented maintenance strategies save time and cost. However, the integration of maintenance work into reliability analysis is difficult as common modeling techniques are often not applicable due to state explosion which calls for restrictive model assumptions and oversimplification. From authors’ point of view, agent-based modeling (ABM) of technical and organizational systems is a promising approach to overcome such problems. But since ABM is not well established in reliability analysis its feasibility in this area still has to be demonstrated. For this purpose ABM is compared with Markov chains, namely by analyzing the reliability of a maintained n-unit system with dependent repair events, applying both modeling approaches. Although ABM and Markov chains lead to the same numerical results, the former points out the potentiality of an improved system state handling. This is demonstrated by extending the ABM with operators as additional “agents†featuring their location (x;y) availability (0;1) and different maintenance strategies. This extension highlights the capability of ABM to analyze complex emergent system behavior and allows a systematic refinement and optimization of the maintenance strategies.

Suggested Citation

  • Kaegi, M. & Mock, R. & Kröger, W., 2009. "Analyzing maintenance strategies by agent-based simulations: A feasibility study," Reliability Engineering and System Safety, Elsevier, vol. 94(9), pages 1416-1421.
    • Handle: RePEc:eee:reensy:v:94:y:2009:i:9:p:1416-1421
    DOI: 10.1016/j.ress.2009.02.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832009000350
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2009.02.002?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. Theresa Brown & Walt Beyeler & Dianne Barton, 2004. "Assessing infrastructure interdependencies: the challenge of risk analysis for complex adaptive systems," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 1(1), pages 108-117.
    2. Briš, Radim, 2008. "Parallel simulation algorithm for maintenance optimization based on directed Acyclic Graph," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 874-884.
    3. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    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. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.
    2. Lee, Juseong & Mitici, Mihaela, 2020. "An integrated assessment of safety and efficiency of aircraft maintenance strategies using agent-based modelling and stochastic Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    3. Meilian Zhu & Guoli Yang & Yanan Jiang & Xiaojun Wang, 2023. "Agent-Based Modeling for Water–Energy–Food Nexus and Its Application in Ningdong Energy and Chemical Base," Sustainability, MDPI, vol. 15(14), pages 1-25, July.
    4. Hong, Liu & Ouyang, Min & Peeta, Srinivas & He, Xiaozheng & Yan, Yongze, 2015. "Vulnerability assessment and mitigation for the Chinese railway system under floods," Reliability Engineering and System Safety, Elsevier, vol. 137(C), pages 58-68.
    5. Heracleous, Constantinos & Kolios, Panayiotis & Panayiotou, Christos G. & Ellinas, Georgios & Polycarpou, Marios M., 2017. "Hybrid systems modeling for critical infrastructures interdependency analysis," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 89-101.
    6. Fonoberova, Maria & Fonoberov, Vladimir A. & Mezić, Igor, 2013. "Global sensitivity/uncertainty analysis for agent-based models," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 8-17.
    7. Nan, Cen & Sansavini, Giovanni, 2015. "Multilayer hybrid modeling framework for the performance assessment of interdependent critical infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 10(C), pages 18-33.
    8. Gao, Guibing & Wang, Junshen & Yue, Wenhui & Ou, Wenchu, 2020. "Structural-vulnerability assessment of reconfigurable manufacturing system based on universal generating function," Reliability Engineering and System Safety, Elsevier, vol. 203(C).

    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. Stock, Eduardo Velasco & da Silva, Roberto, 2023. "Lattice gas model to describe a nightclub dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    2. Varas, A. & Cornejo, M.D. & Mainemer, D. & Toledo, B. & Rogan, J. & Muñoz, V. & Valdivia, J.A., 2007. "Cellular automaton model for evacuation process with obstacles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(2), pages 631-642.
    3. Murilo S Baptista & Hai-Peng Ren & Johen C M Swarts & Rodrigo Carareto & Henk Nijmeijer & Celso Grebogi, 2012. "Collective Almost Synchronisation in Complex Networks," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-11, November.
    4. Xianing Wang & Zhan Zhang & Ying Wang & Jun Yang & Linjun Lu, 2022. "A Study on Safety Evaluation of Pedestrian Flows Based on Partial Impact Dynamics by Real-Time Data in Subway Stations," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    5. Chen, Changkun & Sun, Huakai & Lei, Peng & Zhao, Dongyue & Shi, Congling, 2021. "An extended model for crowd evacuation considering pedestrian panic in artificial attack," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    6. Michael Batty & Jake Desyllas & Elspeth Duxbury, 2003. "Safety in Numbers? Modelling Crowds and Designing Control for the Notting Hill Carnival," Urban Studies, Urban Studies Journal Limited, vol. 40(8), pages 1573-1590, July.
    7. Johansson, Jonas & Hassel, Henrik, 2010. "An approach for modelling interdependent infrastructures in the context of vulnerability analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1335-1344.
    8. Ma, Jian & Song, Wei-guo & Zhang, Jun & Lo, Siu-ming & Liao, Guang-xuan, 2010. "k-Nearest-Neighbor interaction induced self-organized pedestrian counter flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(10), pages 2101-2117.
    9. Illés J Farkas & Shuohong Wang, 2018. "Spatial flocking: Control by speed, distance, noise and delay," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-12, May.
    10. Zheng, Yaochen & Chen, Jianqiao & Wei, Junhong & Guo, Xiwei, 2012. "Modeling of pedestrian evacuation based on the particle swarm optimization algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4225-4233.
    11. P. Daniel Wright & Matthew J. Liberatore & Robert L. Nydick, 2006. "A Survey of Operations Research Models and Applications in Homeland Security," Interfaces, INFORMS, vol. 36(6), pages 514-529, December.
    12. Yue, Hao & Zhang, Junyao & Chen, Wenxin & Wu, Xinsen & Zhang, Xu & Shao, Chunfu, 2021. "Simulation of the influence of spatial obstacles on evacuation pedestrian flow in walking facilities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    13. Sungryong Bae & Jun-Ho Choi & Hong Sun Ryou, 2020. "Modification of Interaction Forces between Smoke and Evacuees," Energies, MDPI, vol. 13(16), pages 1-10, August.
    14. Lasse Pedersen, 2009. "When Everyone Runs for the Exit," International Journal of Central Banking, International Journal of Central Banking, vol. 5(4), pages 177-199, December.
    15. Ebrahim Bagheri & Ali A. Ghorbani, 2010. "UML-CI: A reference model for profiling critical infrastructure systems," Information Systems Frontiers, Springer, vol. 12(2), pages 115-139, April.
    16. Shiwakoti, Nirajan & Sarvi, Majid, 2013. "Understanding pedestrian crowd panic: a review on model organisms approach," Journal of Transport Geography, Elsevier, vol. 26(C), pages 12-17.
    17. Ofer Tchernichovski & Marissa King & Peter Brinkmann & Xanadu Halkias & Daniel Fimiarz & Laurent Mars & Dalton Conley, 2017. "Tradeoff Between Distributed Social Learning and Herding Effect in Online Rating Systems," SAGE Open, , vol. 7(1), pages 21582440176, February.
    18. Liu, Huan & Tatano, Hirokazu & Pflug, Georg & Hochrainer-Stigler, Stefan, 2021. "Post-disaster recovery in industrial sectors: A Markov process analysis of multiple lifeline disruptions," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    19. Krbálek, Milan & Hrabák, Pavel & Bukáček, Marek, 2018. "Pedestrian headways — Reflection of territorial social forces," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 38-49.
    20. Natalie Fridman & Gal A. Kaminka, 2010. "Modeling pedestrian crowd behavior based on a cognitive model of social comparison theory," Computational and Mathematical Organization Theory, Springer, vol. 16(4), pages 348-372, December.

    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:eee:reensy:v:94:y:2009:i:9:p:1416-1421. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.