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Joint Optimization of Maintenance and Spare Parts Inventory Strategies for Emergency Engineering Equipment Considering Demand Priorities

Author

Listed:
  • Xiaoyue Wang

    (School of E-Business and Logistics, Beijing Technology and Business University, Beijing 100048, China)

  • Jingxuan Wang

    (School of E-Business and Logistics, Beijing Technology and Business University, Beijing 100048, China)

  • Ru Ning

    (School of E-Business and Logistics, Beijing Technology and Business University, Beijing 100048, China)

  • Xi Chen

    (School of E-Business and Logistics, Beijing Technology and Business University, Beijing 100048, China)

Abstract

To respond to emergencies in a timely manner, emergency engineering equipment has been an important tool to implement emergency strategies. However, random failures of the equipment may occur during operation. Therefore, appropriate maintenance and spare parts inventory strategies are crucial to ensure the smooth operation of the equipment. Furthermore, the urgency degree of emergencies varies in practice. Nevertheless, existing studies rarely consider the impact of urgency degree and demand priorities on the service order of the equipment. To bridge the research gaps, this paper establishes a joint optimization model of maintenance and spare parts inventory strategies for emergency engineering equipment considering demand priorities. The proposed model includes two types of emergency engineering equipment with different service rates. The more urgent demand can be fulfilled by the equipment with a higher priority. Corrective maintenance and spare parts inventory policies are simultaneously performed for the equipment. The Markov process imbedding method is utilized to derive the probabilistic indexes of the system. To maximize the system availability, the number of maintenance engineers and the spare parts inventory strategy is optimized via the construction of the joint optimization model. The optimal solution for the optimization problem is obtained using the branch-and-bound method. Finally, this study presents practical examples to verify the effectiveness of the model and methods.

Suggested Citation

  • Xiaoyue Wang & Jingxuan Wang & Ru Ning & Xi Chen, 2023. "Joint Optimization of Maintenance and Spare Parts Inventory Strategies for Emergency Engineering Equipment Considering Demand Priorities," Mathematics, MDPI, vol. 11(17), pages 1-18, August.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:17:p:3688-:d:1226389
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    References listed on IDEAS

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    Cited by:

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    2. Mete Özbaltan, 2024. "Hidden Abstract Stack Markov Models with Learning Process," Mathematics, MDPI, vol. 12(13), pages 1-19, July.
    3. Feng-Rung Hu & Jia-Sheng Hu, 2024. "On V-Geometric Ergodicity Markov Chains of the Two-Inertia Systems," Mathematics, MDPI, vol. 12(10), pages 1-11, May.

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