信息物理系统
工业4.0
云计算
大数据
智能制造
弹性(材料科学)
物联网
分析
计算机科学
数据科学
工程类
制造工程
计算机安全
数据挖掘
物理
操作系统
热力学
作者
Fei Tao,Qinglin Qi,Lihui Wang,A.Y.C. Nee
出处
期刊:Engineering
[Elsevier]
日期:2019-05-25
卷期号:5 (4): 653-661
被引量:872
标识
DOI:10.1016/j.eng.2019.01.014
摘要
State-of-the-art technologies such as the Internet of Things (IoT), cloud computing (CC), big data analytics (BDA), and artificial intelligence (AI) have greatly stimulated the development of smart manufacturing. An important prerequisite for smart manufacturing is cyber–physical integration, which is increasingly being embraced by manufacturers. As the preferred means of such integration, cyber–physical systems (CPS) and digital twins (DTs) have gained extensive attention from researchers and practitioners in industry. With feedback loops in which physical processes affect cyber parts and vice versa, CPS and DTs can endow manufacturing systems with greater efficiency, resilience, and intelligence. CPS and DTs share the same essential concepts of an intensive cyber–physical connection, real-time interaction, organization integration, and in-depth collaboration. However, CPS and DTs are not identical from many perspectives, including their origin, development, engineering practices, cyber–physical mapping, and core elements. In order to highlight the differences and correlation between them, this paper reviews and analyzes CPS and DTs from multiple perspectives.
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