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

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  • 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
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    References listed on IDEAS

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    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. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    3. 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.
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    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).

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