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An Adaptive Spare Parts Demand Forecasting Method Based on Degradation Modeling

In: Data-Driven Remaining Useful Life Prognosis Techniques

Author

Listed:
  • Xiao-Sheng Si

    (Xi’an Institute of High-Technology)

  • Zheng-Xin Zhang

    (Xi’an Institute of High-Technology)

  • Chang-Hua Hu

    (Xi’an Institute of High-Technology)

Abstract

System prognostics and health management (PHM) is a new health management methodology proposed for complex engineering systems to reduce maintenance costs, improve the system operating reliability and safety, and mitigate the failure risk [1, 2]

Suggested Citation

  • Xiao-Sheng Si & Zheng-Xin Zhang & Chang-Hua Hu, 2017. "An Adaptive Spare Parts Demand Forecasting Method Based on Degradation Modeling," Springer Series in Reliability Engineering, in: Data-Driven Remaining Useful Life Prognosis Techniques, chapter 0, pages 405-417, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-662-54030-5_15
    DOI: 10.1007/978-3-662-54030-5_15
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    Cited by:

    1. 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.
    2. 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.

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