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Spare parts logistics and installed base information

Author

Listed:
  • M N Jalil

    (Erasmus University)

  • R A Zuidwijk

    (Erasmus University)

  • M Fleischmann

    (University of Mannheim)

  • Jo A E E van Nunen

    (Erasmus University)

Abstract

Many of the challenges in spare parts logistics emerge due to the combination of large service networks, and sporadic/slow-moving demand. Customer heterogeneity and stringent service deadlines entail further challenges. Meanwhile, high revenue rates in service operations motivate companies to invest and optimize the service logistics function. An important aspect of the spare parts logistics function is its ability to support customer-specific requirements with respect to service deadlines. To support customer specific operations, many companies are actively maintaining and utilizing installed base data during forecasting, planning and execution stages. In this paper, we highlight the potential economic value of installed base data for spare parts logistics. We also discuss various data quality issues that are associated with the use of installed base data and show that planning performance depends on the quality dimensions.

Suggested Citation

  • M N Jalil & R A Zuidwijk & M Fleischmann & Jo A E E van Nunen, 2011. "Spare parts logistics and installed base information," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 442-457, March.
    • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:3:d:10.1057_jors.2010.38
    DOI: 10.1057/jors.2010.38
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    2. Romeijnders, Ward & Teunter, Ruud & van Jaarsveld, Willem, 2012. "A two-step method for forecasting spare parts demand using information on component repairs," European Journal of Operational Research, Elsevier, vol. 220(2), pages 386-393.
    3. Zhu, Sha & Dekker, Rommert & van Jaarsveld, Willem & Renjie, Rex Wang & Koning, Alex J., 2017. "An improved method for forecasting spare parts demand using extreme value theory," European Journal of Operational Research, Elsevier, vol. 261(1), pages 169-181.
    4. Van der Auweraer, Sarah & Boute, Robert, 2019. "Forecasting spare part demand using service maintenance information," International Journal of Production Economics, Elsevier, vol. 213(C), pages 138-149.
    5. Hekimoğlu, Mustafa & Karlı, Deniz, 2023. "Modeling repair demand in existence of a nonstationary installed base," International Journal of Production Economics, Elsevier, vol. 263(C).
    6. Van der Auweraer, Sarah & Zhu, Sha & Boute, Robert N., 2021. "The value of installed base information for spare part inventory control," International Journal of Production Economics, Elsevier, vol. 239(C).
    7. Daniel Olivotti & Sonja Dreyer & Benedikt Lebek & Michael H. Breitner, 2019. "Creating the foundation for digital twins in the manufacturing industry: an integrated installed base management system," Information Systems and e-Business Management, Springer, vol. 17(1), pages 89-116, March.
    8. Jin, Tongdan & Tian, Yu, 2012. "Optimizing reliability and service parts logistics for a time-varying installed base," European Journal of Operational Research, Elsevier, vol. 218(1), pages 152-162.
    9. Van der Auweraer, Sarah & Boute, Robert N. & Syntetos, Aris A., 2019. "Forecasting spare part demand with installed base information: A review," International Journal of Forecasting, Elsevier, vol. 35(1), pages 181-196.
    10. F. Tevhide Altekin & Ezgi Aylı & Güvenç Şahin, 2017. "After-sales services network design of a household appliances manufacturer," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(9), pages 1056-1067, September.
    11. Stip, J. & Van Houtum, G.J., 2020. "On a method to improve your service BOMs within spare parts management," International Journal of Production Economics, Elsevier, vol. 221(C).

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