A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics
Обзор цифровых двойников на основе искусственного интеллекта в промышленности 4.0: интеллектуальное производство и передовая робототехника
2021-09-23
SCID: 54.1/a55txp7e
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AI-driven digital twinsIndustry 4.0advanced roboticshuman-robot interactionsmart manufacturing
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Abstract (AI)
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.
Key Findings
1
AI-driven digital twins integrate infrastructure and data, algorithms and models, and software and services across industrial applications.
2
AI-driven digital twins offer potential benefits for sustainable development, while facing practical challenges across different implementation levels.
3
The review covers smart manufacturing and advanced robotics, including metal machining, industrial automation, 3D printing, and human-robot interaction.
4
The survey outlines a pathway for integrating AI into multiscale and multifidelity digital twins using heterogeneous data sources.
5
The survey reviews over 300 manuscripts from the past five years on AI-driven digital twins for Industry 4.0.
Research Object
AI-driven digital twin technologies in Industry 4.0 for smart manufacturing and advanced robotics
Research Subject
Their development, AI integration, applications, benefits, challenges, and prospects across manufacturing and robotics, including multiscale/multifidelity digital twins and data sources
Publication Details
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2021-09-23
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References available in scid.ai5
Digital Twin in Industry: State-of-the-Art2019
Digital Twin: Enabling Technologies, Challenges and Open Research2020
Digital Twin: Values, Challenges and Enablers From a Modeling Perspective2020
A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.02020
Optimization of global production scheduling with deep reinforcement learning2018