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Modeling sourcing strategies to mitigate part obsolescence

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  • Shen, Yuelin
  • Willems, Sean P.

Abstract

Part obsolescence is a common problem across industries, from avionics and military sectors to most original equipment manufacturers serving industrial markets. When a part supplier announces that a part will become obsolete, the OEM can choose from a number of sourcing options. In practice, the three most commonly adopted mitigation strategies are: (1) a lifetime, or life-of-type (LOT), buy from the original supplier; (2) part substitution, which finds a suitable alternative; and (3) line redesign, which modifies the production line to accommodate a new part. We first develop a framework incorporating fixed cost, variable cost, leadtime, demand uncertainty and the discount rate to directly compare and characterize these three sourcing strategies in a static context. We next formulate an integrated sourcing approach that starts with a bridge buy and may continue with part substitution or line redesign when the originals parts are depleted. Through numerical studies, we identify the joint impact of the problem parameters on the static and integrated sourcing strategies and the optimal choice among them. While the integrated sourcing approach outperforms the static ones in many cases it is not a dominant strategy.

Suggested Citation

  • Shen, Yuelin & Willems, Sean P., 2014. "Modeling sourcing strategies to mitigate part obsolescence," European Journal of Operational Research, Elsevier, vol. 236(2), pages 522-533.
  • Handle: RePEc:eee:ejores:v:236:y:2014:i:2:p:522-533
    DOI: 10.1016/j.ejor.2014.01.025
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    References listed on IDEAS

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    Cited by:

    1. Shi, Zhenyang & Liu, Shaoxuan, 2020. "Optimal inventory control and design refresh selection in managing part obsolescence," European Journal of Operational Research, Elsevier, vol. 287(1), pages 133-144.
    2. Yonit Barron, 2016. "Performance analysis of a reflected fluid production/inventory model," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 83(1), pages 1-31, February.
    3. 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).
    4. Yonit Barron, 2016. "Performance analysis of a reflected fluid production/inventory model," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 83(1), pages 1-31, February.
    5. 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.
    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. Barron, Yonit, 2016. "Clearing control policies for MAP inventory process with lost sales," European Journal of Operational Research, Elsevier, vol. 251(2), pages 495-508.
    9. Xiong, Yu & Zhao, Pei & Xiong, Zhongkai & Li, Gendao, 2016. "The impact of product upgrading on the decision of entrance to a secondary market," European Journal of Operational Research, Elsevier, vol. 252(2), pages 443-454.

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