A Component Selection Method for Prioritized Predictive Maintenance

被引:5
|
作者
Ji, Bongjun [1 ]
Park, Hyunseop [1 ]
Jung, Kiwook [2 ]
Bang, Seung Hwan [1 ]
Lee, Minchul [1 ]
Kim, Jeongbin [1 ]
Cho, Hyunbo [1 ]
机构
[1] Pohang Univ Sci & Technol, Dept Ind & Management Engn, Pohang, South Korea
[2] LG Elect, Prod Based Technol Dept, Pyeongtaek, South Korea
来源
ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS: THE PATH TO INTELLIGENT, COLLABORATIVE AND SUSTAINABLE MANUFACTURING | 2017年 / 513卷
关键词
Predictive maintenance; Condition-based maintenance; Component prioritization; Machine condition; Intelligent manufacturing; MEDICAL EQUIPMENT; SYSTEM;
D O I
10.1007/978-3-319-66923-6_51
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Predictive maintenance is a maintenance strategy of diagnosing and prognosing a machine based on its condition. Compared with other maintenance strategies, the predictive maintenance strategy has the advantage of lowering the maintenance cost and time. Thus, many studies have been conducted to develop a predictive maintenance model based on a growth of prediction methodology. However, these studies tend to focus on building the predictive model and measuring its performance, rather than selecting the appropriate components for predictive maintenance. Nevertheless, selecting the predictive maintenance policy and target component are as important as model selection and performance measurement. In this paper, a selection method is proposed to improve component selection by referencing current literature and industry expert knowledge. The results of this research can serve as a foundation for further studies in this area.
引用
收藏
页码:433 / 440
页数:8
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