Parallel Factories for Smart Industrial Operations: From Big AI Models to Field Foundational Models and Scenarios Engineering

Briefing: The rapid advancement of fundamental theories and computing capacity has brought artificial intelligence, internet of things, extended reality, and many other new intelligent technologies into our daily lives. Due to the lack of interpretability and reliability guarantees, it is extremely...

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Bibliographic Details
Published in:IEEE/CAA journal of automatica sinica 2022-12, Vol.9 (12), p.2079-2086
Main Authors: Lu, Jingwei, Wang, Xingxia, Cheng, Xiang, Yang, Jing, Kwan, Oliver, Wang, Xiao
Format: Article
Language:English
Subjects:
Artificial intelligence
Cyber-physical-social system (CPSS)
Design factors
Factories
Human factors
Industrial engineering
Industry 5.0
Internet of Things
Manufacturing engineering
Metaverses
Oil fields
Parallel factories
Parallel intelligence
Reliability
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Summary:Briefing: The rapid advancement of fundamental theories and computing capacity has brought artificial intelligence, internet of things, extended reality, and many other new intelligent technologies into our daily lives. Due to the lack of interpretability and reliability guarantees, it is extremely challenging to apply these technologies directly to real-world industrial systems. Here we present a new paradigm for establishing parallel factories in metaverses to accelerate the deployment of intelligent technologies in real-world industrial systems: QAII-1.0. Based on cyber-physical-social systems, QAII-1.0 incorporates complex social and human factors into the design and analysis of industrial operations and is capable of handling industrial operations involving complex social and human behaviors. In QAII-1.0, a field foundational model called EuArtisan combined with scenarios engineering is developed to improve the intelligence of industrial systems while ensuring industrial interpretability and reliability. Finally, parallel oil fields in metaverses are established to demonstrate the operating procedure of QAII-1.0.
ISSN:2329-9266
2329-9274
DOI:10.1109/JAS.2022.106094