Cognitive Maintenance for High-End Equipment and Manufacturing

被引:0
|
作者
Wang, Yi [1 ]
Wang, Kesheng [2 ,3 ]
Dai, Guohong [3 ]
机构
[1] Plymouth Univ, Sch Business, Plymouth, Devon, England
[2] Norwegian Univ Sci & Technol, Dept Mech & Ind Engn, Trondheim, Norway
[3] Changzhou Univ, Changzhou, Peoples R China
关键词
Cognitive maintenance; Industry; 4.0; High-end equipment; Predictive maintenance; Data analysis; Green monitor; Smart manufactory; INDUSTRY; 4.0;
D O I
10.1007/978-981-13-2375-1_49
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Traditionally, In order to predict impending failures and mitigate downtime in their manufacturing facilities, we have to combine many techniques, both quantitative and qualitative, such as smart sensors, high-end intelligent equipment, smart networks, Internet of Thing (IOT), Artificial Intelligence (AI), business analysis decision-making and Internet of service IOS. Based on Industry 4.0 concept, Cognitive Maintenance (CM) or Intelligent Predictive Maintenance (IPdM) systems, which uses intelligent data analysis and decision making techniques, offers the maintenance professionals in high-end equipment the potential to optimize maintenance tasks in real time, maximizing the useful life of their equipment and manufacturing assets while still avoiding disruption to operations. In this paper, we will present the impact of CM to highend equipment, the framework of Cognitive Maintenance (CM) system and a case study. Some lessons learned from the implementation of CM system in industry are discussed.
引用
收藏
页码:394 / 400
页数:7
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