Digital Twins and Cyber–Physical Systems toward Smart Manufacturing and Industry 4.0: Correlation and Comparison
Цифровые двойники и киберфизические системы для интеллектуального производства и Индустрии 4.0: взаимосвязь и сравнение
2019-05-25
SCID: 54.1/9fj6tgfw
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Cyber–physical integrationCyber–physical systemsDigital twinsIndustry 4.0Smart manufacturing
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Abstract (AI)
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.
Key Findings
1
CPS and digital twins share intensive cyber–physical connectivity, real-time interaction, organizational integration, and deep collaboration.
2
Cyber–physical integration is presented as a prerequisite for smart manufacturing, with CPS and digital twins serving as prominent integration approaches.
3
Despite their common foundations, CPS and digital twins differ in origin, development, engineering practices, cyber–physical mapping, and core elements.
4
Feedback loops between physical processes and cyber components enable CPS and digital twins to improve manufacturing efficiency, resilience, and intelligence.
5
IoT, cloud computing, big data analytics, and artificial intelligence are identified as major technologies driving smart manufacturing development.
Research Object
Cyber–physical systems (CPS) and digital twins (DTs) in smart manufacturing
Research Subject
The correlation, differences, and comparative characteristics of CPS and DTs across their origins, development, engineering practices, cyber–physical mapping, and core elements
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2019-05-25
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