Digital Twin: Enabling Technologies, Challenges and Open Research
Цифровой двойник: обеспечивающие технологии, проблемы и открытые направления исследований
2020-01-01
SCID: 54.1/kxhsjk5a
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Artificial IntelligenceDigital TwinIndustry 4.0Internet of Things (IoT)Smart cities
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Abstract (AI)
Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry. The Digital Twin is defined extensively but is best described as the effortless integration of data between a physical and virtual machine in either direction. The challenges, applications, and enabling technologies for Artificial Intelligence, Internet of Things (IoT) and Digital Twins are presented. A review of publications relating to Digital Twins is performed, producing a categorical review of recent papers. The review has categorised them by research areas: manufacturing, healthcare and smart cities, discussing a range of papers that reflect these areas and the current state of research. The paper provides an assessment of the enabling technologies, challenges and open research for Digital Twins.
Key Findings
1
Artificial intelligence and the Internet of Things are identified as key enabling technologies for Digital Twin systems.
2
Digital Twin technology is characterized by bidirectional, seamless data integration between a physical machine and its virtual counterpart.
3
Industry 4.0 advancements have accelerated Digital Twin development, particularly within manufacturing applications.
4
The paper reviews Digital Twin literature and categorizes recent research across manufacturing, healthcare, and smart-city domains.
5
The review assesses major Digital Twin challenges and identifies open research directions.
Research Object
Digital Twin technology (integration of physical and virtual machines/data)
Research Subject
Enabling technologies, applications, challenges, and open research directions for Digital Twins
Publication Details
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2020-01-01
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References available in scid.ai5
Digital Twin in Industry: State-of-the-Art2019
Deep learning applications and challenges in big data analytics2015
A Review of the Roles of Digital Twin in CPS-based Production Systems2017
Digital Twins and Cyber–Physical Systems toward Smart Manufacturing and Industry 4.0: Correlation and Comparison2019
Leveraging Digital Twin Technology in Model-Based Systems Engineering2019
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