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

TLDR

Smart manufacturing is driven by IoT, cloud computing, big data analytics, and AI, with cyber‑physical integration—via CPS and digital twins—providing real‑time feedback loops that enhance efficiency, resilience, and intelligence, though CPS and DTs differ in origin, development, and core elements. The study aims to highlight the differences and correlations between cyber‑physical systems and digital twins. The authors review and analyze CPS and digital twins from multiple perspectives to elucidate their differences and correlations.

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.