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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2012, Vol. 33 ›› Issue (11): 2018-2027.

• Solid Mechanics and Vehicle Conceptual Design • Previous Articles     Next Articles

Inventory Control of Multi-echelon Maintenance Supply System Under Finite Repair Channel Constraint

RUAN Minzhi1, LI Qingmin2, HUANG Aolin2,3, LI Hua2   

  1. 1. Office of Research & Development, Naval University of Engineering, Wuhan 430033, China;
    2. Department of Weaponry Engineering, Naval University of Engineering, Wuhan 430033, China;
    3. Department of Command and Robotization, School of Electronic Engineering, Naval University of Engineering, Wuhan 430033, China
  • Received:2011-11-27 Revised:2012-02-08 Online:2012-11-25 Published:2012-11-22
  • Supported by:

    General Armament Department Pre-research Foundation (51304010206, 51327020105)

Abstract: Multi-echelon maintenance and supply management is an effective approach to improve support effectiveness, and the preparation and programming of spare parts resources is a critical factor affecting equipment availability as well as combat power. Based on the multi-echelon technique for recoverable item control (METRIC) theory, the assumption for infinite repair channel is relaxed. According to the M/M/C queuing system theory, the computational model of average repair time and the pipeline for spare parts is modified, and an initial stock distribution model is established. Based on the traditional marginal optimization algorithm, a layered method is introduced to improve the traditional algorithm and achieve higher calculation efficiency, and it is analyzed and proved in theory. Example result shows that the calculation result of the improved layered marginal optimization algorithm is identical to that of the traditional marginal algorithm, while the improved algorithm can greatly improve calculation efficiency.

Key words: multi-echelon maintenance supply, finite repair channel, spare part, multi-echelon technique for recoverable item control, support effectiveness, layered marginal optimization

CLC Number: