航空学报 > 2009, Vol. 30 Issue (5): 861-866

航空装备备件需求量的概率区间计算方法

邱志平,尼早   

  1. 北京航空航天大学 固体力学研究所
  • 收稿日期:2008-03-10 修回日期:2008-06-26 出版日期:2009-05-25 发布日期:2009-05-25
  • 通讯作者: 尼早

Probabilistic Interval Approach for Determining the Demand of Aviation Spares

Qiu Zhiping, Ni Zao   

  1. Institute of Solid Mechanics, Beijing University of Aeronautics and Astronautics
  • Received:2008-03-10 Revised:2008-06-26 Online:2009-05-25 Published:2009-05-25
  • Contact: Ni Zao

摘要: 科学合理地解决备件配置问题一直为人们所瞩目,备件配置数量的多少不仅影响装备的维修甚至影响装备的战备完好率。计算备件需求量的传统模型是概率模型,然而概率模型中的分布参数往往有一定程度的不确定性。本文对概率模型中含有有界不确定参数的备件需求量计算问题进行研究,根据航空装备备件的分类,分别提出了寿命服从指数分布、正态分布和威布尔分布部件的备件需求量的概率区间确定方法。所提出的方法较好地解决了分布参数有界不确定时航空装备备件的配置问题并能够充分保证备件的保障率,进而提高航空综合保障水平。最后,通过数值算例说明了该方法的有效性和实用性。

关键词: 装备, 备件需求量, 分布函数, 泰勒级数, 概率区间模型, 保障率

Abstract: Scientific and proper ration of spares is a significant problem because the amount of spares can not only affect equipment maintenance and overhaul but also its operational readiness. The conventional model for calculating the demand of the spares is the probability model; however, the distribution parameters in the probability model usually contain uncertainties to some extent. This article investigates a new method for calculating the demand of the spares for cases when the distribution parameters in the probability model are uncertainbutbounded. According to the classification of aviation spares, the probabilistic interval approach for determining the demand of aviation spares is proposed for conditions when age distributions are exponential, normal, and Weibull, respectively. The proposed method can solve the ration problem of aviation spares and ensure the satisfaction of supporting rate when the distribution parameters are uncertainbutbounded. Moreover, with this method the level of aviation integrated support can be improved. Finally, a numerical example is considered to illustrate the efficiency and practicability of the proposed method.

Key words: equipment, amount of spares, distribution functions, Taylor series, probabilistic interval model, supporting rate

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