4.7 Article

Condition based maintenance optimization for multi-component systems using proportional hazards model

期刊

RELIABILITY ENGINEERING & SYSTEM SAFETY
卷 96, 期 5, 页码 581-589

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2010.12.023

关键词

Condition based maintenance; Multi-component systems; Proportional hazards model; Economic dependency

资金

  1. Natural Sciences and Engineering Research Council of Canada (NSERC)
  2. U.S. National Science Foundation [CMMI-0954667]
  3. Div Of Civil, Mechanical, & Manufact Inn
  4. Directorate For Engineering [1238304] Funding Source: National Science Foundation
  5. Div Of Civil, Mechanical, & Manufact Inn
  6. Directorate For Engineering [0954667] Funding Source: National Science Foundation

向作者/读者索取更多资源

The objective of condition based maintenance (CBM) is typically to determine an optimal maintenance policy to minimize the overall maintenance cost based on condition monitoring information. The existing work reported in the literature only focuses on determining the optimal CBM policy for a single unit. In this paper, we investigate CBM of multi-component systems, where economic dependency exists among different components subject to condition monitoring. The fixed preventive replacement cost, such as sending a maintenance team to the site, is incurred once a preventive replacement is performed on one component. As a result, it would be more economical to preventively replace multiple components at the same time. In this work, we propose a multi-component system CBM policy based on proportional hazards model (PHM). The cost evaluation of such a CBM policy becomes much more complex when we extend the PHM based CBM policy from a single unit to a multicomponent system. A numerical algorithm is developed in this paper for the exact cost evaluation of the PHM based multi-component CBM policy. Examples using real-world condition monitoring data are provided to demonstrate the proposed methods. (C) 2011 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据