Systems Engineering and Electronics ›› 2018, Vol. 40 ›› Issue (10): 2270-2275.doi: 10.3969/j.issn.1001-506X.2018.10.17

Previous Articles     Next Articles

Spare parts allocation optimization for extremely low duty equipment storage and use stage#br#

PENG Yingwu1, ZHOU Liang2, WANG Shen3, ZENG Qinghua4   

  1. 1. Academy of Weapon Engineering, Naval University of Engineering, Wuhan 430033, China;
    2. National Key Laboratory for Vessel Integrated Power System Technology, Naval University of
    Engineering, Wuhan 430033, China; 3. Unit 91962 of the PLA Navy, Shanghai 201900, China;
    4. Department of Information Theory, Chinese People's Public Security University, Beijing 100038, China
  • Online:2018-09-25 Published:2018-10-10

Abstract: In view of the unreasonable situation of the equipment spare parts allocation according to the common equipment and the use of duty equipment, the failure of the equipment does not work during the period of failure, and the influence of spare parts on the spare parts allocation during the mission is studied. By introducing a virtual site, the equipment is converted from a period of no use to a condition during the use of the equipment. The reliability model of equipment storage and use during the mission is established based on the reliability of equipment. The optimization model of equipment spare parts configuration is established based on the marginal optimization algorithm with the constraint of equipment reliability. According to the support flow of spare parts, a simulation model is built based on the Monte Carlo method. Analysis of cases shows that for equipment of very low use ratio, spare parts that consider equipment used during component failure are more than those without considering equipment storage failure, and correctness of the model is verified by the simulation method. The model can be used as a reference for the plan making of spare parts to be developed and used in a ship for a long period of time.


[an error occurred while processing this directive]