ReviewDigital Twin-driven smart manufacturing: Connotation, reference model, applications and research issues
Introduction
Digital Twin has gained significant impetus as a breakthrough technological development that has the potential to transform the landscape of manufacturing today and tomorrow [1]. Digital Twin [2], acting as a mirror of the real world, provides a means of simulating, predicting and optimizing physical manufacturing systems and processes. Using Digital Twin, together with intelligent algorithms, organizations can achieve data-driven operation monitoring and optimization [3], develop innovative product and services [4], and diversify value creation and business models [5].
Though studies have reported the potential application scenarios of Digital Twin in manufacturing, we identified that current approaches to the implementation of Digital Twin in manufacturing lack a thorough understanding of Digital Twin concept, framework, and development methods, which impedes the development of genuine Digital Twin applications for smart manufacturing. In this study, we discussed the connotations of Digital Twin-driven smart manufacturing in the context of Industry 4.0. The objectives and the contributions of this paper are to provide comprehensive discussions on the impact, reference model, application scenarios and research issues of Digital Twin for achieving smart manufacturing.
The remainder of the paper starts with tracing the vision of Digital Twin and the development to date based on studies from the literature (see Section 2). This is followed by an in-depth discussion on the connotation of Digital Twin-driven smart manufacturing in Section 3, highlighting how Digital Twin will transform the future manufacturing landscape. Section 4 details a Digital Twin reference model and enabling technologies for developing a Digital Twin-driven smart manufacturing solution. An overview of existing Digital Twin applications and some typical application scenarios are presented in Section 5. Section 6 discusses the critical research issues for future research. Section 7 concludes the research work.
Section snippets
Digital Twin overview
This section traces the history of the Digital Twin concept, clarifies its relations with several other tropical concepts in the manufacturing domain, summarizes its research and development progress, and highlights the research gaps.
Digital Twin-driven smart manufacturing
Manufacturing is becoming smart at all levels from the physical device, through factory management, to production networks, gaining abilities to learn, configure and execute with cognitive intelligence. This section outlines the trend of smart manufacturing and discusses the connotation of Digital Twin-driven smart manufacturing, highlighting the impact that Digital Twin may have for future manufacturing.
Digital Twin reference model
Digital Twin reflects the two-way dynamic mapping between a physical object and its virtual model in the cyberspace [24]. A Digital Twin presents a middleware architecture that abstracts its physical counterpart for high-level engineering management systems to make near real-time decisions [25]. Fig. 4 shows a Digital Twin reference model. At the technical core, the development of Digital Twin needs three components: (1) an information model that abstracts the specifications of a physical
Application scenarios
Although Digital Twin is a relatively new concept, some practical applications of Digital Twin have already been developed and reported in the literature. This section briefs the current status of Digital Twin applications. First, an overview of existing Digital Twin applications is provided, and the current status of Digital Twin applications is discussed. Second, three representative Digital Twin applications are introduced to demonstrate the advantages and potential of Digital Twin.
Research issues
Based on the discussions in the above sections, we summarize the following key research issues for advancing the research of Digital Twin-driven smart manufacturing.
Research issue 1: architecture pattern for a Digital Twin
There exist two system architecture patterns, namely server-based and edge-based. In server-based architecture, the data acquired from a physical device is routed back to a centralized server that performs the data analysis and Digital Twin construction. This pattern provides
Conclusions
This paper presents the current status and advancement of Digital Twin-driven smart manufacturing. The core concept, reference model, enabling technologies, application scenarios, and research issues of Digital Twin-driven smart manufacturing are discussed in detail.
With the rapid growth of integrating information technologies and operation technologies in the industry, significant efforts have been made to make manufacturing smart. As a core element of future manufacturing, Digital Twin-driven
References (85)
- et al.
About the importance of autonomy and digital twins for the future of manufacturing
IFAC-PapersOnLine
(2015) - et al.
Toward a digital twin for real-time geometry assurance in individualized production
CIRP Ann. - Manuf. Technol.
(2017) - et al.
Cloud-based manufacturing equipment and big data analytics to enable on-demand manufacturing services
Robot. Comput. Integr. Manuf.
(2019) - et al.
Future modeling and simulation of CPS-based Factories: an example from the automotive industry
IFAC-PapersOnLine
(2016) - et al.
Shaping the digital twin for design and production engineering
CIRP Ann.
(2017) - et al.
The digital twin: realizing the cyber-physical production system for industry 4.0
Procedia CIRP
(2017) - et al.
Smart manufacturing, manufacturing intelligence and demand-dynamic performance
Comput. Chem. Eng.
(2012) - et al.
Energy-efficient cyber-physical production network: architecture and technologies
Comput. Industr. Eng.
(2019) - et al.
A flexible data schema and system architecture for the virtualization of manufacturing machines (VMM)
J. Manuf. Syst.
(2017) - et al.
Resource virtualization: a core technology for developing cyber-physical production systems
J. Manuf. Syst.
(2018)
Beyond the hype: big data concepts, methods, and analytics
Int. J. Inf. Manage.
M2DDM - a maturity model for data-driven manufacturing
Procedia CIRP
Modeling of cloud-based digital twins for smart manufacturing with MT connect
Procedia Manuf.
An application framework of digital twin and its case study
J. Ambient Intell. Humaniz. Comput.
Digital Twin: applying emulation for machine reconditioning
Procedia CIRP
A digital twin based service oriented application for a 4.0 knowledge navigation in the smart factory
IFAC-PapersOnLine
Digital twin for rotating machinery fault diagnosis in smart manufacturing
Int. J. Prod. Res.
A systematic development method for cyber-physical machine tools
J. Manuf. Syst.
Sensor data and information fusion to construct Digital-Twins virtual machine tools for cyber-physical manufacturing
Procedia Manuf.
Digital twin data modeling with AutomationML and a communication methodology for data exchange
IFAC-PapersOnLine
A standards-based approach for linking as-planned to as-fabricated product data
CIRP Ann.
Human intention estimation based on hidden markov model motion validation for safe flexible robotized warehouses
Robot. Comput. Integr. Manuf.
Intelligent control of an assembly station by integration of a digital twin for employees into the decentralized control system
Procedia Manuf.
MTConnect-based cyber-physical machine Tool: a case study
Procedia CIRP
The digital twin paradigm for future NASA and US air force vehicles, in: 53rd AIAA/ASME/ASCE/AHS/ASC structures
Digital twin-driven product design, manufacturing and service with big data
Int. J. Adv. Manuf. Technol.
Reengineering aircraft structural life prediction using a digital twin
Int. J. Aerospace Eng.
Digital twin shop-floor: a new shop-floor paradigm towards smart manufacturing
IEEE Access
Big future for cyber-physical manufacturing systems
Design World
Etienne, Artificial Intelligence and Tutoring Systems : Computational and Cognitive Approaches to the Communication of Knowledge
Human–robot collaboration: a survey
Int. J. Humanoid Rob.
From mass customization to mass personalization: a strategic transformation
Int. J. Flexible Manuf. Syst.
Contextualising manufacturing data for lifecycle decision-making
Int. J. Product Lifecycle Manag.
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Conflict of interest. None.