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基于MAP的装备保障资源需求预测研究 被引量:1

Prediction of Equipments Spare Parts Demand Based on Markovian Arrival Process
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摘要 针对装备保障资源需求预测难的问题,本文利用EM算法将单装备的保障资源需求点过程拟合为马尔可夫到达过程(MAP)。通过仿真获取整个装备的备件更换时间序列,并举例说明了该方法的有效性。
出处 《航空维修与工程》 2011年第3期78-80,共3页 Aviation Maintenance & Engineering
关键词 保障资源需求 组合维修 PH分布 马尔可夫到达过程 EM算法 spare parts demand combination maintenance phase-type distribution markovian arrival process(MAP) EM algorithm
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参考文献5

  • 1Vaughan T.S. Failure replacement and preventive maintenance spare parts ordering policy[J]. European Journal of Operational Research, 2005. 161(1): 183-190.
  • 2Marseguerra M., Zio E. Optimizing maintenance and repair policies via a combination of genetic algorithms and Monte Carlo simulation[J]. Reliability Engineering and System Safety, 2000. 68(1): 69-83.
  • 3Chelbi A., AR-Kadi D. Analysis of a production/inventory system with randomly failing production unit submitted to regular preventive maintenance[J]. European Journal of Operational Research, 2004. 156(3): 712-718.
  • 4Rezg N., Chelbi A., Xiaolan X. Modeling and optimizing a joint buffer inventory and preventive maintenance strategy for a randomly failing production unit: Analytical and simulation approaches[J]. International Journal of Computer Integrated Manufacturing, 2005.18 (2-3): 225-235.
  • 5Osogami T. Analysis of Multiserver Systems via Dimensionality Reduction of Markov Chains[D]. Carnegie Mellon University, 2005.

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