Integrated Inspection of QoM, QoP, and QoS for AOI Industries in Metaverses

• Published in: IEEE/CAA journal of automatica sinica Vol. 9; no. 12; pp. 2071 - 2078
• Main Authors: Wang, Yutong, Tian, Yonglin, Wang, Jiangong, Cao, Yansong, Li, Shixing, Tian, Bin
• Format: Journal Article
• Language: English
• Published: Piscataway Chinese Association of Automation (CAA) 01.12.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); State Key Laboratory for Management and Control of Complex Systems,Chinese Academy of Sciences,Beijing 100190,China%Department of Engineering Science,Faculty of Innovation Engineering,Macau University of Science and Technology,Macau 999078,China%North Automatic Control Technology Institute in Taiyuan,Shanxi,China%State Key Laboratory for Management and Control of Complex Systems,Chinese Academy of Sciences,Beijing 100190,and also with the Oinodao Academy of Intelligent Industries,Shandong 266109,China
• Subjects: Automated Optical Inspection; Cryptography; Data retrieval; Digital twins; Industrial development; Inspection; Manufacturing; Metaverses; Quality Inspection; Transformers; Workflow; Transformers; Quality Inspection; Automated Optical Inspection; Metaverses
• ISSN: 2329-9266; 2329-9274
• DOI: 10.1109/JAS.2022.106091

Briefing: With the rapid development of information technologies such as digital twin, extended reality, and blockchain, the hype around "metaverse" is increasing at astronomical speed. However, much attention has been paid to its entertainment and social functions. Considering the openness and interoperability of metaverses, the market of quality inspection promises explosive growth. In this paper, taking advantage of metaverses, we first propose the concept of Automated Quality Inspection (AutoQI), which performs integrated inspection covering the entire manufacturing process, including Quality of Materials, Quality of Manufacturing (QoM), Quality of Products, Quality of Processes (QoP), Quality of Systems, and Quality of Services (QoS). Based on the scenarios engineering theory, we discuss how to perform interactions between metaverses and the physical world for virtual design instruction and physical validation feedback. Then we introduce a bottomup inspection device development workflow with productivity tools offered by metaverses, making development more effective and efficient than ever. As the core of quality inspection, we propose Quality Transformers to complete detection task, while federated learning is integrated to regulate data sharing. In summary, we point out the development directions of quality inspection under metaverse tide.