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Spare Parts Inventory Control based on Maintenance Planning

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  • Zhu, S.
  • van Jaarsveld, W.L.
  • Dekker, R.

Abstract

For many maintenance organizations, on-condition maintenance tasks are the most important source of spare part demand. An uneven distribution of maintenance tasks over time is an important cause for intermittency in spare parts demand, and this intermittency complicates spare parts inventory control severely. In an attempt to partially overcome these complications, we propose to use the maintenance plan, i.e. the planned maintenance tasks, as a source of advance demand information. We propose a simple forecasting mechanism to estimate the spare part demand distribution based on the maintenance plan, and develop a dynamic inventory control method based on these forecasts. The value of this approach is benchmarked against state-of-the art time series forecast methods, using data from two large maintenance organizations. We find that the proposed method can yield cost savings of 23 to 51% compared to the traditional methods.

Suggested Citation

  • Zhu, S. & van Jaarsveld, W.L. & Dekker, R., 2019. "Spare Parts Inventory Control based on Maintenance Planning," Econometric Institute Research Papers EI2019-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Handle: RePEc:ems:eureir:114791
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    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. Sedghi, Mahdieh & Kauppila, Osmo & Bergquist, Bjarne & Vanhatalo, Erik & Kulahci, Murat, 2021. "A taxonomy of railway track maintenance planning and scheduling: A review and research trends," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    7. Boram Choi & Jong Hwan Suh, 2020. "Forecasting Spare Parts Demand of Military Aircraft: Comparisons of Data Mining Techniques and Managerial Features from the Case of South Korea," Sustainability, MDPI, vol. 12(15), pages 1-20, July.
    8. Amniattalab, Ayda & Frenk, J.B.G. & Hekimoğlu, Mustafa, 2023. "On spare parts demand and the installed base concept: A theoretical approach," International Journal of Production Economics, Elsevier, vol. 266(C).
    9. Pinçe, Çerağ & Turrini, Laura & Meissner, Joern, 2021. "Intermittent demand forecasting for spare parts: A Critical review," Omega, Elsevier, vol. 105(C).
    10. Yazdekhasti, Amin & sharifzadeh, Shila & Ma, Junfeng, 2022. "A two-echelon two-indenture warranty distribution network development and optimization under batch-ordering inventory policy," International Journal of Production Economics, Elsevier, vol. 249(C).
    11. Farhadi, Mohammad & Shahrokhi, Mahmoud & Rahmati, Seyed Habib A, 2022. "Developing a supplier selection model based on Markov chain and probability tree for a k-out-of-N system with different quality of spare parts," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    12. 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).
    13. Rippe, Christoph & Kiesmüller, Gudrun P., 2023. "The repair kit problem with imperfect advance demand information," European Journal of Operational Research, Elsevier, vol. 304(2), pages 558-576.
    14. Lee, Juseong & Mitici, Mihaela, 2022. "Multi-objective design of aircraft maintenance using Gaussian process learning and adaptive sampling," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    15. Zhu, Sha & van Jaarsveld, Willem & Dekker, Rommert, 2022. "Critical project planning and spare parts inventory management in shutdown maintenance," Reliability Engineering and System Safety, Elsevier, vol. 219(C).

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