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End-of-Life Inventory Problem with Phaseout Returns

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  • M. Pourakbar
  • E. Laan
  • R. Dekker

Abstract

We consider the service parts end-of-life inventory problem of a capital goods manufacturer in the final phase of its life cycle. The final phase starts as soon as the production of parts terminates and continues until the last service contract expires. Final order quantities are considered a popular tactic to sustain service fulfillment obligations and to mitigate the effect of obsolescence. In addition to the final order quantity, other sources to obtain serviceable parts are repairing returned defective items and retrieving parts from phase-out returns. Phase-out returns happen when a customer replaces an old system platform with a next generation one and returns the old product to the original equipment manufacturer (OEM). These returns can well serve the demand for service parts of other customers still using the old generation of the product. In this paper, we study the decision-making complications stemming from phase-out occurrence. We use a finite horizon Markov decision process to characterize the structure of the optimal inventory control policy. We show that the optimal policy consists of a time varying threshold level for item repair. Furthermore, we study the value of phase-out information by extending the results to cases with an uncertain phase-out quantity or an uncertain schedule. Numerical analysis sheds light on the advantages of the optimal policy compared to some heuristic policies.
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Suggested Citation

  • M. Pourakbar & E. Laan & R. Dekker, 2014. "End-of-Life Inventory Problem with Phaseout Returns," Production and Operations Management, Production and Operations Management Society, vol. 23(9), pages 1561-1576, September.
  • Handle: RePEc:bla:popmgt:v:23:y:2014:i:9:p:1561-1576
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    File URL: http://hdl.handle.net/10.1111/poms.12176
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    References listed on IDEAS

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    1. John R. Moore, Jr., 1971. "Forecasting and Scheduling for Past-Model Replacement Parts," Management Science, INFORMS, vol. 18(4-Part-I), pages 200-213, December.
    2. Teunter, Ruud H. & Klein Haneveld, Willem K., 1998. "The `final orderrs problem," European Journal of Operational Research, Elsevier, vol. 107(1), pages 35-44, May.
    3. Krikke, H.R. & van der Laan, E., 2009. "Last Time Buy and Control Policies With Phase-Out Returns : A Case Study in Plant Control Systems," Other publications TiSEM c1a3c438-6d31-4147-afd7-8, Tilburg University, School of Economics and Management.
    4. Pourakbar, M. & Frenk, J.B.G. & Dekker, R., 2010. "End-of-Life Inventory Decisions for Consumer Electronics Service Parts," Econometric Institute Research Papers EI 2009-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Cattani, Kyle D. & Souza, Gilvan C., 2003. "Good buy? Delaying end-of-life purchases," European Journal of Operational Research, Elsevier, vol. 146(1), pages 216-228, April.
    6. J P J van Kooten & T Tan, 2009. "The final order problem for repairable spare parts under condemnation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(10), pages 1449-1461, October.
    7. Teunter, Ruud H. & Fortuin, Leonard, 1998. "End-of-life service: A case study," European Journal of Operational Research, Elsevier, vol. 107(1), pages 19-34, May.
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    Cited by:

    1. Hu, Qiwei & Boylan, John E. & Chen, Huijing & Labib, Ashraf, 2018. "OR in spare parts management: A review," European Journal of Operational Research, Elsevier, vol. 266(2), pages 395-414.
    2. Saurin, Tarcisio Abreu & Werle, Natalia Jaeger Basso, 2017. "A framework for the analysis of slack in socio-technical systems," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 439-451.
    3. Mabel C. Chou & Chee-Khian Sim & Xue-Ming Yuan, 2020. "Policies for inventory models with product returns forecast from past demands and past sales," Annals of Operations Research, Springer, vol. 288(1), pages 137-180, May.
    4. Ozyoruk, Emin & Erkip, Nesim Kohen & Ararat, Çağın, 2022. "End-of-life inventory management problem: Results and insights," International Journal of Production Economics, Elsevier, vol. 243(C).
    5. Pourakbar, Morteza & Dekker, Rommert, 2012. "Customer differentiated end-of-life inventory problem," European Journal of Operational Research, Elsevier, vol. 222(1), pages 44-53.
    6. Behfard, S. & van der Heijden, M.C. & Al Hanbali, A. & Zijm, W.H.M., 2015. "Last time buy and repair decisions for spare parts," European Journal of Operational Research, Elsevier, vol. 244(2), pages 498-510.
    7. Zaarour, Nizar & Melachrinoudis, Emanuel & Solomon, Marius M., 2016. "Maximizing revenue of end of life items in retail stores," European Journal of Operational Research, Elsevier, vol. 255(1), pages 133-141.
    8. Tianji Yang & Chao Fu & Xinbao Liu & Jun Pei & Lin Liu & Panos M. Pardalos, 2018. "Closed-loop supply chain inventory management with recovery information of reusable containers," Journal of Combinatorial Optimization, Springer, vol. 35(1), pages 266-292, January.
    9. J. B. G. Frenk & Canan Pehlivan & Semih O. Sezer, 2019. "Order and exit decisions under non-increasing price curves for products with short life cycles," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 90(3), pages 365-397, December.
    10. van der Heijden, Matthieu & Iskandar, Bermawi P., 2013. "Last time buy decisions for products sold under warranty," European Journal of Operational Research, Elsevier, vol. 224(2), pages 302-312.
    11. Behfard, S. & Al Hanbali, A. & van der Heijden, M.C. & Zijm, W.H.M., 2018. "Last Time Buy and repair decisions for fast moving parts," International Journal of Production Economics, Elsevier, vol. 197(C), pages 158-173.

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