Volume 36, Number 3, June 2018
|Page(s)||536 - 542|
|Published online||08 October 2018|
Spare Ordering Policy Model Based on Complex System Degradation Mechanism
School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, China
2 Key Laboratory of Modern Measurement and Control Technology, Ministry of Education, Beijing Information Science and Technology University, Beijing 100192, China
Security service and effective perception of equipment becomes more and more important, especially for some high-end equipment complex system module degradation condition prediction and efficient spare ordering is the key to guarantee safe operation, improve service quality and reduce maintenance costs. In this paper, therefore, we analyze the characteristics of the complex system and propose an order policy model based on complex system degradation mechanism. The system degradation model is established based on the condition space feature matrix. The system ordering policy model is constructed using the system degradation model and spare random lead-time, whose decision variable is the placing an order time. Based on the proposed system ordering policy model there exists a finite and unique optimum placing an order time that minimizes the expected cost rate. Finally, a case study is presented to verify the effectiveness of the proposed system ordering policy model.
Key words: complex system / condition space / degradation process / random lead-time / condition-based ordering / cost rate
关键字 : 复杂系统 / 状态空间 / 退化过程 / 随机交付时间 / 视情订购 / 费用率
© 2018 Journal of Northwestern Polytechnical University. All rights reserved.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.