Digital twins-based smart manufacturing system design in Industry 4.0: A review. (July 2021)
- Record Type:
- Journal Article
- Title:
- Digital twins-based smart manufacturing system design in Industry 4.0: A review. (July 2021)
- Main Title:
- Digital twins-based smart manufacturing system design in Industry 4.0: A review
- Authors:
- Leng, Jiewu
Wang, Dewen
Shen, Weiming
Li, Xinyu
Liu, Qiang
Chen, Xin - Abstract:
- Highlights: Digital twins technologies could promote the smart manufacturing system design (SMSD). A Function-Structure-Behavior-Control-Intelligence-Performance (FSBCIP) framework for SMSD. The definitions, frameworks, models, enabling technologies, cases, and research directions of digital twins-based SMSD. Abstract: A smart manufacturing system (SMS) is a multi-field physical system with complex couplings among various components. Usually, designers in various fields can only design subsystems of an SMS based on the limited cognition of dynamics. Conducting SMS designs concurrently and developing a unified model to effectively imitate every interaction and behavior of manufacturing processes are challenging. As an emerging technology, digital twins can achieve semi-physical simulations to reduce the vast time and cost of physical commissioning/reconfiguration by the early detection of design errors/flaws of the SMS. However, the development of the digital twins concept in the SMS design remains vague. An innovative Function-Structure-Behavior-Control-Intelligence-Performance (FSBCIP) framework is proposed to review how digital twins technologies are integrated into and promote the SMS design based on a literature search in the Web of Science database. The definitions, frameworks, major design steps, new blueprint models, key enabling technologies, design cases, and research directions of digital twins-based SMS design are presented in this survey. It is expected that thisHighlights: Digital twins technologies could promote the smart manufacturing system design (SMSD). A Function-Structure-Behavior-Control-Intelligence-Performance (FSBCIP) framework for SMSD. The definitions, frameworks, models, enabling technologies, cases, and research directions of digital twins-based SMSD. Abstract: A smart manufacturing system (SMS) is a multi-field physical system with complex couplings among various components. Usually, designers in various fields can only design subsystems of an SMS based on the limited cognition of dynamics. Conducting SMS designs concurrently and developing a unified model to effectively imitate every interaction and behavior of manufacturing processes are challenging. As an emerging technology, digital twins can achieve semi-physical simulations to reduce the vast time and cost of physical commissioning/reconfiguration by the early detection of design errors/flaws of the SMS. However, the development of the digital twins concept in the SMS design remains vague. An innovative Function-Structure-Behavior-Control-Intelligence-Performance (FSBCIP) framework is proposed to review how digital twins technologies are integrated into and promote the SMS design based on a literature search in the Web of Science database. The definitions, frameworks, major design steps, new blueprint models, key enabling technologies, design cases, and research directions of digital twins-based SMS design are presented in this survey. It is expected that this survey will shed new light on urgent industrial concerns in developing new SMSs in the Industry 4.0 era. … (more)
- Is Part Of:
- Journal of manufacturing systems. Volume 60(2021)
- Journal:
- Journal of manufacturing systems
- Issue:
- Volume 60(2021)
- Issue Display:
- Volume 60, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 60
- Issue:
- 2021
- Issue Sort Value:
- 2021-0060-2021-0000
- Page Start:
- 119
- Page End:
- 137
- Publication Date:
- 2021-07
- Subjects:
- Digital twins -- Manufacturing system design -- Cyber-physical systems -- Smart manufacturing -- Function-structure-behavior-control-intelligence-performance
Manufacturing processes -- Periodicals
Production engineering -- Data processing -- Periodicals
Robots, Industrial -- Periodicals
Production, Technique de la -- Informatique -- Périodiques
Robots industriels -- Périodiques
Electronic journals
670.42 - Journal URLs:
- http://www.sciencedirect.com/science/journal/02786125 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jmsy.2021.05.011 ↗
- Languages:
- English
- ISSNs:
- 0278-6125
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5011.650000
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