固体力学与飞行器总体设计

装备自主维修保障的维修与库存联合优化

  • 徐玉国 ,
  • 邱静 ,
  • 刘冠军
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  • 1. 国防科学技术大学 机电工程与自动化学院 装备综合保障技术重点实验室, 湖南 长沙 410073;
    2. 装甲兵工程学院 技术保障工程系, 北京 100072
徐玉国 男,博士研究生。主要研究方向:预测维修决策与优化、维修保障网络建模与分析。Tel:0436-3260166 E-mail:mountren@126.com;邱静 男,博士,教授,博士生导师。主要研究方向:测试性、装备维修保障、故障诊断与预测。Tel:0731-84573305 E-mail:qiujing@nudt.edu.cn

收稿日期: 2012-10-15

  修回日期: 2013-01-21

  网络出版日期: 2013-02-18

基金资助

国家自然科学基金(51175502)

Joint Optimization of Maintenance and Inventory in Equipment Autonomic Logistics

  • XU Yuguo ,
  • QIU Jing ,
  • LIU Guanjun
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  • 1. Laboratory of Science and Technology on Integrated Logistics Support, College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073, China;
    2. Department of Technical Support Engineering, Academy of Armored Force Engineering, Beijing 100072, China

Received date: 2012-10-15

  Revised date: 2013-01-21

  Online published: 2013-02-18

Supported by

National Natural Science Foundation of China(51175502)

摘要

装备自主维修保障系统(ALS)的核心是在网络化维修保障体系内由装备剩余使用寿命评估(RULE)信息驱动维修保障决策,其能有效降低装备寿命周期成本、提高装备使用可用度。在分析RULE特性与ALS运行机制的基础上研究了ALS中装备维修和备件供应等各类成本的产生机理,以单位时间成本最小为目标提出了基于RULE的维修与库存联合优化模型,应用Monte Carlo仿真方法设计了求解最优维修保障成本的算法,并分析了RULE的漏检率与虚警率对维修保障效能的影响。

本文引用格式

徐玉国 , 邱静 , 刘冠军 . 装备自主维修保障的维修与库存联合优化[J]. 航空学报, 2013 , 34(8) : 1864 -1873 . DOI: 10.7527/S1000-6893.2013.0072

Abstract

The core of an autonomic logistics system (ALS) is to accomplish optimal maintenance and support decision driven by the remaining useful life estimation (RULE) information under a networked logistics architecture, which can decrease life cycle cost and improve average operational availability. First, the characteristics of RULE and the operational mechanism of ALS are presented, and the cost generation mechanisms of equipment maintenance and spare part replenishment of ALS are analyzed. Then, a joint optimization model of maintenance and inventory based on RULE is proposed to minimize the long-term average cost rate. Finally the arithmetic for optimal logistics strategies is designed using Monte Carlo simulation methods which can measure the effect of miss detection rate and false alarm rate of RULE on logistics performance.

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