机器人学
工业4.0
自动化
人工智能应用
背景(考古学)
人工智能
工程类
机器人
计算机科学
制造工程
工程管理
系统工程
数据挖掘
机械工程
生物
古生物学
作者
Ziqi Huang,Yang Shen,Jia-Yi Li,Marcel Fey,Christian Brecher
出处
期刊:Sensors
[Multidisciplinary Digital Publishing Institute]
日期:2021-09-23
卷期号:21 (19): 6340-6340
被引量:35
摘要
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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