Digital Twins and Cyber–Physical Systems toward Smart Manufacturing and Industry 4.0: Correlation and Comparison

By Fei Tao, Qinglin Qi, Lihui Wang, Andrew Yeh-Ching Nee. Engineering, 2019

1,147 citations recorded by the source corpus.

Abstract 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.

Subfields: Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/3a8968eb9bdc564cda96baaeb6789689eafa713c

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In Industrial and Manufacturing Engineering

Citations in the corpus

Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights (2021, methodology): “A digital copy of the structure in the digital twin domain is created to aggregate, process, and analyze the information and generate new data.(333) In some texts, a digital twin is defined as a digital representation of a realworld object in a CPS context.”
Digital Twin: Enabling Technologies, Challenges and Open Research (2020, background): “Tao presents two review papers, [82] and [81]; the first [82] compares Digital Twins and Cyber-Physical systems within a smart manufacturing environment.”
Digital twin paradigm: A systematic literature review (2021, background): “Sensors and actuators are considered as key elements in CPS (Lee et al., 2015), while models and data are the core components in a DT (Tao et al., 2019).”
Digital Twins: A Survey on Enabling Technologies, Challenges, Trends and Future Prospects (2022, background): “To clear confusion, a study detailing a comparison and correlation between the two paradigms has been conducted in [36].”