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Joint planning of service engineers and spare parts

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  • Sleptchenko, Andrei
  • Al Hanbali, Ahmad
  • Zijm, Henk

Abstract

We analyze the joint optimization of spare parts inventories and workforce allocation in a single-site maintenance system. In this system, for each failure, a service engineer with a necessary replacement part has to be allocated. If one of the required resources is not available, the incoming failure request is routed to an external provider, such as a centralized repair facility or a sub-contractor. We study multiple failure types (related to failing components) with exponentially distributed inter-failure times. The system repair times and the replenishment times of the spare parts inventory are also exponentially distributed. The inventory replenishment is done according to a Base-Stock policy. The objective is to minimize the total system cost consisting of annual holding costs of the spare parts and the service engineers, and incidental outsourcing costs. For the joint optimization of the resources, we propose a Mixed-Integer Programming (MIP) formulation using the balance equations of the Markov Chain representation of the system. Furthermore, we provide a simple and efficient heuristic that produces close-to-optimal (< 0.3% difference) results, for solving larger instances. Using the proposed optimization methods and real-life data, we analyze the optimal balance between the costs of the resources and the outsourcing costs and show how the outsourcing rates and the total costs behave for different system parameters.

Suggested Citation

  • Sleptchenko, Andrei & Al Hanbali, Ahmad & Zijm, Henk, 2018. "Joint planning of service engineers and spare parts," European Journal of Operational Research, Elsevier, vol. 271(1), pages 97-108.
  • Handle: RePEc:eee:ejores:v:271:y:2018:i:1:p:97-108
    DOI: 10.1016/j.ejor.2018.05.014
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    2. Debabrata Das & Sameer Kumar & Nirmal Baran Hui & Vipul Jain & Charu Chandra, 2023. "Pricing and revenue-based outsourcing strategies in a multi-echelon lot-sizing model under insufficient production capacity," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(6), pages 514-530, December.
    3. Scarf, P.A. & Cavalcante, C.A.V. & Lopes, R.S., 2019. "Delay-time modelling of a critical system subject to random inspections," European Journal of Operational Research, Elsevier, vol. 278(3), pages 772-782.
    4. Zhang, Shuguang & Dan, Bin & Zhou, Maosen, 2019. "After-sale service deployment and information sharing in a supply chain under demand uncertainty," European Journal of Operational Research, Elsevier, vol. 279(2), pages 351-363.
    5. Turan, Hasan Hüseyin & Atmis, Mahir & Kosanoglu, Fuat & Elsawah, Sondoss & Ryan, Michael J., 2020. "A risk-averse simulation-based approach for a joint optimization of workforce capacity, spare part stocks and scheduling priorities in maintenance planning," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    6. Kafiabad, Shayan Tavakoli & Kazemi Zanjani, Masoumeh & Nourelfath, Mustapha, 2020. "Integrated planning of operations and on-job training in maintenance logistics networks," Reliability Engineering and System Safety, Elsevier, vol. 199(C).

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