Prognostic control-enhanced maintenance optimization for multi-component systems

被引:15
|
作者
Niu, Gang [1 ]
Jiang, Junjie [1 ,2 ]
机构
[1] Tongji Univ, IRT, Caoan 4800, Shanghai 201804, Peoples R China
[2] CASCO Signal LTD, Block 11,489 North Xizang Rd, Shanghai 200072, Peoples R China
基金
中国国家自然科学基金;
关键词
Local prognostic control; Global maintenance optimization; Multi-component system; RELIABILITY; MANAGEMENT; POLICIES; MODELS;
D O I
10.1016/j.ress.2017.04.011
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In the last decades, the fast evolution of the industrial scenario has boosted the economic relevance of maintenance in all sectors of industry, and interests in maintenance can be expected to continue increasing in the next future. Maintenance has gained in importance as a support function for ensuring equipment availability, quality products, on-time deliveries, and plant safety. This paper presents a novel maintenance optimization strategy for multi component systems that uses local prognostic control to improve health statue of operating systems at component level and solves a global optimal problem to find proper maintenance interval at system-level, the combination of which can increase maintenance economy effectively. The proposed strategy can be demonstrated by a case study of braking system of rail vehicles. Compared with traditional dynamic maintenance methodologies, the results show that the maintenance cost can be reduced significantly when both health-oriented prognostic control and global optimization are utilized together. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:218 / 226
页数:9
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