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Reducing Costs Of Spare Parts Supply Systems Via Static Priorities

Author

Listed:
  • I. J. B. F. ADAN

    (Department of Mathematics and Computer Science, Eindhoven University of Technology, P. O. Box 513, 5600 MB Eindhoven, The Netherlands)

  • A. SLEPTCHENKO

    (Ab Ovo Nederland B. V., Barbizonlaan 75, 2908 ME Capelle aan den IJssel, The Netherlands)

  • G. J. VAN HOUTUM

    (School of Industrial Engineering, Eindhoven University of Technology, P. O. Box 513, 5600 MB Eindhoven, The Netherlands)

Abstract

We study static repair priorities in a system consisting of one repair shop and one stockpoint, where spare parts of multiple, critical repairables are kept on stock to serve an installed base of technical systems. Demands for ready-for-use parts occur according to Poisson processes, and are accompanied by returns of failed parts. The demands are met from stock if possible, and otherwise they are backordered and fulfilled as soon as a ready-for-use part becomes available. Returned failed parts are immediately sent into repair. The repairables are assigned to static priority classes. The repair shop is modeled as a single-server queue, where the failed parts are served according to these priority classes. We show that under a given assignment of repairables to priority classes, optimal spare parts stock levels follow from Newsvendor equations. Next, we develop fast and effective heuristics for the assignment of repairables to priority classes. Subsequently, we compare the performance of the system under these static priorities to the case with a First-Come First-Served (FCFS) service discipline. We show that in many cases static priorities reduce total inventory holding and backordering costs by more than 40%. Finally, we analyse the effect of the number of priority classes. We show that 2 priority classes suffice to obtain 90% of the maximal savings via static priorities.

Suggested Citation

  • I. J. B. F. Adan & A. Sleptchenko & G. J. Van Houtum, 2009. "Reducing Costs Of Spare Parts Supply Systems Via Static Priorities," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 26(04), pages 559-585.
    • Handle: RePEc:wsi:apjorx:v:26:y:2009:i:04:n:s0217595909002377
    DOI: 10.1142/S0217595909002377
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    Citations

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    Cited by:

    1. Levner, Eugene & Perlman, Yael & Cheng, T.C.E. & Levner, Ilya, 2011. "A network approach to modeling the multi-echelon spare-part inventory system with backorders and interval-valued demand," International Journal of Production Economics, Elsevier, vol. 132(1), pages 43-51, July.
    2. Bruneel, Herwig & Maertens, Tom & Walraevens, Joris, 2014. "Class clustering destroys delay differentiation in priority queues," European Journal of Operational Research, Elsevier, vol. 235(1), pages 149-158.
    3. Arts, Joachim, 2017. "A multi-item approach to repairable stocking and expediting in a fluctuating demand environment," European Journal of Operational Research, Elsevier, vol. 256(1), pages 102-115.
    4. Driessen, M.A. & van Houtum, G.J. & Zijm, W.H.M. & Rustenburg, W.D., 2020. "Capacity assignment in repair shops with high material uncertainty," International Journal of Production Economics, Elsevier, vol. 221(C).
    5. Sleptchenko, Andrei & Turan, Hasan Hüseyin & Pokharel, Shaligram & ElMekkawy, Tarek Y., 2019. "Cross-training policies for repair shops with spare part inventories," International Journal of Production Economics, Elsevier, vol. 209(C), pages 334-345.
    6. 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).
    7. H. G. H. Tiemessen & M. Fleischmann & G. J. Houtum, 2017. "Dynamic control in multi-item production/inventory systems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(1), pages 165-191, January.
    8. van der Heijden, M.C. & Alvarez, E.M. & Schutten, J.M.J., 2013. "Inventory reduction in spare part networks by selective throughput time reduction," International Journal of Production Economics, Elsevier, vol. 143(2), pages 509-517.
    9. Herwig Bruneel & Tom Maertens & Bart Steyaert & Dieter Claeys & Dieter Fiems & Joris Walraevens, 2018. "Analysis of a two-class single-server discrete-time FCFS queue: the effect of interclass correlation," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(3), pages 403-436, October.
    10. Tiemessen, H.G.H. & van Houtum, G.J., 2013. "Reducing costs of repairable inventory supply systems via dynamic scheduling," International Journal of Production Economics, Elsevier, vol. 143(2), pages 478-488.

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