Digital twin-driven manufacturing cyber-physical system for parallel controlling of smart workshop

With increasing diverse product demands, the manufacturing paradigm has been transformed into a mass-individualized one, among which one bottleneck is to achieve the interoperability between physical world and the digital world of manufacturing system for the intelligent organizing of resources. Thi...

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Vydané v:Journal of ambient intelligence and humanized computing Ročník 10; číslo 3; s. 1155 - 1166
Hlavní autori: Leng, Jiewu, Zhang, Hao, Yan, Douxi, Liu, Qiang, Chen, Xin, Zhang, Ding
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2019
Springer Nature B.V
Predmet:
Artificial Intelligence
Communication
Computational Intelligence
Cyber-physical systems
Decision making
Digital twins
Embedded systems
Engineering
Intelligence
Internet of Things
Manufacturers
Manufacturing
Original Research
Robotics and Automation
User Interfaces and Human Computer Interaction
Workshops
Mass individualization
Smart workpiece
Digital twin
Cyber physical system
Smart manufacturing
Manufacturing cyber-physical system
ISSN:1868-5137, 1868-5145
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Shrnutí:With increasing diverse product demands, the manufacturing paradigm has been transformed into a mass-individualized one, among which one bottleneck is to achieve the interoperability between physical world and the digital world of manufacturing system for the intelligent organizing of resources. This paper presents a digital twin-driven manufacturing cyber-physical system (MCPS) for parallel controlling of smart workshop under mass individualization paradigm. By establishing cyber-physical connection via decentralized digital twin models, various manufacturing resources can be formed as dynamic autonomous system to co-create personalized products. Clarification on the MCPS concept, characteristics, architecture, configuration, operating mechanism and key enabling technologies are elaborated, respectively. A demonstrative implementation of the digital twin-driven parallel controlling of board-type product smart manufacturing workshop is also presented. It addresses a bi-level online intelligence in proactive decision making for the organization and operation of manufacturing resources.
Bibliografia:ObjectType-Article-1
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ISSN:1868-5137
1868-5145
DOI:10.1007/s12652-018-0881-5