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September 23, 2021Sensors404 citationsOpen Access

A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics

ZHZiqi HuangYSYang ShenJLJiayi Li

Key Points

  • This survey investigates the integration of AI-driven digital twins in Industry 4.0, focusing on smart manufacturing and robotics.
  • Comprehensive review of over 300 manuscripts on AI-driven digital twin technologies from the past five years.
  • Analysis of integration of these technologies in various industrial applications, including metal machining and 3D printing.
  • Discussion of practical challenges and development prospects for digital twins.
  • Summarizes advancements and current state of AI integration in smart manufacturing and robotics applications.
  • Identifies advantages of AI-driven digital twins for sustainable development.
  • Outlines a pathway for AI integration in multiscale digital twins with various data sources.

Abstract

Digital twin (DT) and artificial intelligence (AI) technologies have grown rapidly in recent years and are considered by both academia and industry to be key enablers for Industry 4.0. As a digital replica of a physical entity, the basis of DT is the infrastructure and data, the core is the algorithm and model, and the application is the software and service. The grounding of DT and AI in industrial sectors is even more dependent on the systematic and in-depth integration of domain-specific expertise. This survey comprehensively reviews over 300 manuscripts on AI-driven DT technologies of Industry 4.0 used over the past five years and summarizes their general developments and the current state of AI-integration in the fields of smart manufacturing and advanced robotics. These cover conventional sophisticated metal machining and industrial automation as well as emerging techniques, such as 3D printing and human-robot interaction/cooperation. Furthermore, advantages of AI-driven DTs in the context of sustainable development are elaborated. Practical challenges and development prospects of AI-driven DTs are discussed with a respective focus on different levels. A route for AI-integration in multiscale/fidelity DTs with multiscale/fidelity data sources in Industry 4.0 is outlined.

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Cite This Study

Huang et al. (2021) studied this question.

synapsesocial.com/papers/69de6f31741e97d2d4e93b55https://doi.org/10.3390/s21196340
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