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Unlocking the power of industrial artificial intelligence towards Industry 5.0: Insights, pathways, and challenges

Leng, Jiewu (författare)
Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing, and State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou 510006, China
Zhu, Xiaofeng (författare)
Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing, and State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou 510006, China
Huang, Zhiqiang (författare)
Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing, and State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou 510006, China
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Li, Xingyu (författare)
School of Engineering Technology, Purdue University, West Lafayette, IN 47907, USA
Zheng, Pai (författare)
Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China
Zhou, Xueliang (författare)
Department of Electrical and Information Engineering, HuBei University of Automotive Technology, Shiyan 442002, China
Mourtzis, Dimitris (författare)
Laboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, Rio Patras, 26504, Greece
Wang, Baicun (författare)
State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
Qi, Qinglin (författare)
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Shao, Haidong (författare)
College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China
Wan, Jiafu (författare)
School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510641, China
Chen, Xin (författare)
Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing, and State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou 510006, China
Wang, Lihui (författare)
KTH,Industriella produktionssystem
Liu, Qiang (författare)
Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing, and State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment, Guangdong University of Technology, Guangzhou 510006, China
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 (creator_code:org_t)
Elsevier BV, 2024
2024
Engelska.
Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 73, s. 349-363
Relaterad länk:
https://urn.kb.se/re...
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https://doi.org/10.1...
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  • Forskningsöversikt (refereegranskat)
Abstract Ämnesord
Stäng  
  • With the continuous development of human-centric, resilient, and sustainable manufacturing towards Industry 5.0, Artificial Intelligence (AI) has gradually unveiled new opportunities for additional functionalities, new features, and tendencies in the industrial landscape. On the other hand, the technology-driven Industry 4.0 paradigm is still in full swing. However, there exist many unreasonable designs, configurations, and implementations of Industrial Artificial Intelligence (IndAI) in practice before achieving either Industry 4.0 or Industry 5.0 vision, and a significant gap between the individualized requirement and actual implementation result still exists. To provide insights for designing appropriate models and algorithms in the upgrading process of the industry, this perspective article classifies IndAI by rating the intelligence levels and presents four principles of implementing IndAI. Three significant opportunities of IndAI, namely, collaborative intelligence, self-learning intelligence, and crowd intelligence, towards Industry 5.0 vision are identified to promote the transition from a technology-driven initiative in Industry 4.0 to the coexistence and interplay of Industry 4.0 and a value-oriented proposition in Industry 5.0. Then, pathways for implementing IndAI towards Industry 5.0 together with key empowering techniques are discussed. Social barriers, technology challenges, and future research directions of IndAI are concluded, respectively. We believe that our effort can lay a foundation for unlocking the power of IndAI in futuristic Industry 5.0 research and engineering practice.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Produktionsteknik, arbetsvetenskap och ergonomi (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Production Engineering, Human Work Science and Ergonomics (hsv//eng)

Nyckelord

Collaborative intelligence
Crowd intelligence
Industrial artificial intelligence
Industry 5.0
Self-learning intelligence

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