Using digital twin for maintenance applications in manufacturing: State of the Art and Gap analysis

被引：0
|
作者：
Aivaliotis, Panagiotis [1 ]
Georgoulias, Konstantinos [1 ]
Alexopoulos, Kosmas [1 ]
机构：
[1] Univ Patras, Lab Mfg Syst & Automat, Rion 26504, Greece
来源：
2019 IEEE INTERNATIONAL CONFERENCE ON ENGINEERING, TECHNOLOGY AND INNOVATION (ICE/ITMC) | 2019年
基金：
欧盟地平线“2020”;
关键词：
Digital Twin; Predictive Maintenance; METHODOLOGY;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The digital twin concept is more and more appearing in industrial applications including the field of the predictive maintenance. This paper, initially, summarizes and presents studies that use the digital twin concept for digital twin concept for condition monitoring and predictive in manufacturing. Following, the gaps in the existing literature are identified and analyzed and a brief proposition of the way that the already existing state of the art can go further is presented. A future outlook of the research in the particular field is provided.
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页数：5
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