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Demand Forecasting of Helicopter Aviation Materials Based on Multi-model Reliability Analysis

  • Peng Hui NiuEmail author
  • Wei Hu
  • Dan Lu
Conference paper
  • 34 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1060)

Abstract

In complicated helicopter equipment, different components have different characteristics about fault information. In the reliability and spare parts demand analysis, different analysis methods should be adopted on the basis of preliminary statistical analysis and in combination with the characteristics of equipment and spare parts. For the main problem in the practical work of the aviation units, this paper puts forward a helicopter material demand forecasting method based on multi-model reliability analysis. It mainly focuses on high-incidence trouble components, reliability growth components, and repairable components. Based on the reliability analysis, the accessories’ maintenance cycle could be calculated, and its requirements could be forecast. Some examples show its effectiveness.

Keywords

Multi-model Reliability analysis Aviation material demand forecasting 

References

  1. 1.
    Liu Z, Liu Y. Aeronautic spare parts supervise model based on operating availability & demand analysis. Aeronaut Comput Tech. 2007;37(5):38–41.Google Scholar
  2. 2.
    Yu R, Li J. The decision-making model for the maintenance time in equipment full life cycle based on reliability. Mech Sci Technol Aerosp Eng. 2013;32(4):573–6.Google Scholar
  3. 3.
    Chen J. Estimation of ammo storage life in different areas based on Weibull distribution. Initiators Pyrotech. 2017;10:54–7.Google Scholar
  4. 4.
    Liu J, Chen W, Li X. Reliability growth model based on Duane curve. Environ Technol. 2017;6:43–7.Google Scholar
  5. 5.
    Yang K, Xu L. Research on FFOP prediction approach of the aviation arm based on inhomogeneous Poisson process. Fire Control Command Control. 2015;9:72–6.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Army Aviation Institute of PLATongzhou District, BeijingChina

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