Steps Toward Industry 5.0: Building “6S” Parallel Industries With Cyber-Physical-Social Intelligence

Xingxia Wang; Jing Yang; Yutong Wang; Qinghai Miao; Fei-Yue Wang; Aijun Zhao; Jian-Ling Deng; Lingxi Li; Xiaoxiang Na; Ljubo Vlacic

doi:10.1109/JAS.2023.123753

Volume 10 Issue 8

Aug. 2023

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2023 > 10(8): 1692-1703

X. X. Wang, J. Yang, Y. T. Wang, Q. H. Miao, F.-Y. Wang, A. J. Zhao, J.-L. Deng, L. X. Li, X. X. Na, and L. Vlacic, “Steps toward Industry 5.0: Building “6S” parallel industries with cyber-physical-social intelligence,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 8, pp. 1692–1703, Aug. 2023. doi: 10.1109/JAS.2023.123753

Citation:

X. X. Wang, J. Yang, Y. T. Wang, Q. H. Miao, F.-Y. Wang, A. J. Zhao, J.-L. Deng, L. X. Li, X. X. Na, and L. Vlacic, “Steps toward Industry 5.0: Building “6S” parallel industries with cyber-physical-social intelligence,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 8, pp. 1692–1703, Aug. 2023. doi: 10.1109/JAS.2023.123753

Citation:

X. X. Wang, J. Yang, Y. T. Wang, Q. H. Miao, F.-Y. Wang, A. J. Zhao, J.-L. Deng, L. X. Li, X. X. Na, and L. Vlacic, “Steps toward Industry 5.0: Building “6S” parallel industries with cyber-physical-social intelligence,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 8, pp. 1692–1703, Aug. 2023. doi: 10.1109/JAS.2023.123753

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Steps Toward Industry 5.0: Building “6S” Parallel Industries With Cyber-Physical-Social Intelligence

doi: 10.1109/JAS.2023.123753

Funds: This work was partially supported by the Science and Technology Development Fund of Macau SAR (0050/2020/A1)

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Author Bio:
Xingxia Wang is currently pursuing the Ph.D. degree in pattern recognition and intelligent system with the School of Artificial Intelligence, University of Chinese Academy of Sciences, and the State Key Laboratory for Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences. Her research interests include parallel intelligence, CPSS, fault-tolerant control, and multi-agent systems

Jing Yang received the B.E. degree in automation from the Beijing University of Chemical Technology in 2020. She is currently pursuing the Ph.D. degree in social computing with the State Key Laboratory for Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences. Her research interests include artificial intelligence, cyber-physical-social systems, parallel manufacturing and social manufacturing

Yutong Wang (Member, IEEE) is an Assistant Professor at the State Key Laboratory for Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences. She received the Ph.D. degree in control theory and control engineering from University of Chinese Academy of Sciences in 2021. Her research interests cover computer vision and image anomaly detection

Qinghai Miao (Senior Member, IEEE) received the Ph.D. degree in control theory and control engineering from the Graduate University of Chinese Academy of Sciences in 2007. From 2017 to 2018, he was a Visiting Scholar with the School of Informatics, the University of Edinburgh, UK. He is currently an Associate Professor with the School of Artificial Intelligence, University of Chinese Academy of Sciences. His research interests include parallel intelligence, machine learning, computer vision, intelligent transportation systems

Fei-Yue Wang (Fellow, IEEE) received the Ph.D. degree in computer and systems engineering from the Rensselaer Polytechnic Institute, USA, in 1990. He joined The University of Arizona in 1990 and became a Professor and the Director of the Robotics and Automation Laboratory and the Program in Advanced Research for Complex Systems. In 1999, he founded the Intelligent Control and Systems Engineering Center at the Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China, under the support of the Outstanding Chinese Talents Program from the State Planning Council, and in 2002, was appointed as the Director of the Key Laboratory of Complex Systems and Intelligence Science, CAS, and Vice President of Institute of Automation, CAS in 2006. He found CAS Center for Social Computing and Parallel Management in 2008, and became the State Specially Appointed Expert and the Founding Director of the State Key Laboratory for Management and Control of Complex Systems in 2011. His current research focuses on methods and applications for parallel intelligence, social computing, and knowledge automation. He is a Fellow of INCOSE, IFAC, ASME, and AAAS. In 2007, he received the National Prize in Natural Sciences of China, numerous best papers awards from IEEE Transactions, and became an Outstanding Scientist of ACM for his work in intelligent control and social computing. He received the IEEE ITS Outstanding Application and Research Awards in 2009, 2011, and 2015, respectively, the IEEE SMC Norbert Wiener Award in 2014, and became the IFAC Pavel J. Nowacki Distinguished Lecturer in 2021. Since 1997, he has been serving as the General or Program Chair of over 30 IEEE, INFORMS, IFAC, ACM, and ASME conferences. He was the President of the IEEE ITS Society from 2005 to 2007, the IEEE Council of RFID from 2019 to 2021, the Chinese Association for Science and Technology, USA, in 2005, the American Zhu Kezhen Education Foundation from 2007 to 2008, the Vice President of the ACM China Council from 2010 to 2011, the Vice President and the Secretary General of the Chinese Association of Automation from 2008 to 2018, the Vice President of IEEE Systems, Man, and Cybernetics Society from 2019 to 2021. He was the Founding Editor-in-Chief (EiC) of the International Journal of Intelligent Control and Systems from 1995 to 2000, IEEE ITS Magazine from 2006 to 2007, IEEE/CAA Journal of Automatica Sinica from 2014–2017, China’s Journal of Command and Control from 2015–2021, and China’s Journal of Intelligent Science and Technology from 2019 to 2021. He was the EiC of the IEEE Intelligent Systems from 2009 to 2012, IEEE Transactions on Intelligent Transportation Systems from 2009 to 2016, IEEE Transactions on Computational Social Systems from 2017 to 2020. Currently, he is the President of CAA’s Supervision Council, and the EiC of IEEE Transaction on Intelligent Vehicles

Aijun Zhao is a Senior Engineer at North Automatic Control Technology Institute. His main technical directions include automatic systems, artificial intelligence, cyber-physical-social systems, parallel manufacturing, and social manufacturing

Jian-Ling Deng is a Senior Engineer and holds a master degree. He now serves as President of China Huaneng Group Co., Ltd. Before joining China Huaneng Group, he served as Vice President of China Huadian Corporation. He started his career in June 1989, and worked at Beijing Electric Power Test Institute and North China Electric Power Test Institute. Later, he worked as Vice President of North China Electric Power Research Institute, and then as General Manager of Datong No. 2 Power Plant. After that, he served as Deputy Chief Engineer of North China Power Group Corporation and later became Vice President of Gansu Provincial Power Company. Then he served as Deputy Chief Engineer of China Huadian Corporation. After that, he served as Chief Engineer of China Huadian Corporation and concurrently as President of Huadian Fuel Co., Ltd., and President of Huadian Coal Industry Group Co., Ltd

Lingxi Li (Senior Member, IEEE) is a Professor in the Department of Electrical and Computer Engineering at Purdue School of Engineering and Technology, Indiana University-Purdue University Indianapolis (IUPUI), USA. Dr. Li received the Ph.D. degree in electrical and computer engineering from the University of Illinois at Urbana-Champaign in 2008. Dr. Li’s current research focuses on the modeling, analysis, control, and optimization of complex systems, connected and automated vehicles, intelligent transportation systems, digital twins and parallel intelligence, and human-machine interaction. He has authored/co-authored one book and over 140 research articles in refereed journals and conferences. Dr. Li was the recipient of five best paper awards, the 2021 IEEE ITSS Outstanding Application Award, the 2017 Outstanding Research Contributions Award, the 2012 T-ITS Outstanding Editorial Service Award, and multiple university research/teaching awards. He is currently serving as an Associate Editor for five international journals and has served as the General Chair, Program Chair, Program Co-Chair, etc., for 20+ international conferences

Xiaoxiang Na received the B.Sc. and M.Sc. degrees in automotive engineering from the College of Automotive Engineering, Jilin University, in 2007 and 2009, respectively. He received the Ph.D. degree in driver-vehicle dynamics from the Department of Engineering, University of Cambridge, U.K. in 2014. He is currently a University Assistant Professor in Applied Mechanics at the Department of Engineering, University of Cambridge. From 2014 to 2023, he worked as a Research Associate and later Senior Research Associate at the Centre for Sustainable Road Freight (SRF), University of Cambridge. His main research interests include driver-vehicle dynamics, in-service monitoring of heavy goods vehicle (HGV) operations, and assessment and modelling of HGV energy performance

Ljubo Vlacic (Senior Member, IEEE) received the Graduate Diploma degree in electrical engineering and the M.Phil. and Ph.D. degrees in control systems engineering from the University of Sarajevo, Sarajevo, Bosnia and Herzegovina, in 1973, 1976, and 1986, respectively. He also graduated Conservatorium of Music (Violin), the University of Sarajevo in 1976. Professor Emeritus Vlacic is a Control Systems Scientist and a Practitioner, renowned for his contributions to co-operative driverless vehicles and intelligent control systems research and development. He has held a number of leading roles in both industry and academia. He is currently with the Institute for Integrated and Intelligent Systems, Griffith University, Australia. Professor Emeritus Vlacic is a recipient of 22 awards, including the IEE Achievement Medal (world-wide), the Sir Lionel Hooke Award, the Queensland Professional Engineer of the Year Award, the Gold Coast Business Events Ambassador Award, etc. He organised and hosted sixteen national and international scientific conferences. His research achievements made news headlines and were broadcast through media outlets throughout the world. Professor Emeritus Vlacic is currently President-Elect of the IEEE-Intelligent Transportation Systems Society and the Immediate Past Editor-in-Chief of the IEEE Intelligent Transportation Systems Magazine (2017–2022). He played violin with professional symphony orchestra
Corresponding author: Yutong Wang, e-mail: yutong.wang@ia.ac.cn
Received Date: 2023-06-11
Revised Date: 2023-06-21
Accepted Date: 2023-06-29

Available Online: 2023-07-11

Abstract

Abstract

Very recently, intensive discussions and studies on Industry 5.0 have sprung up and caused the attention of researchers, entrepreneurs, and policymakers from various sectors around the world. However, there is no consensus on why and what is Industry 5.0 yet. In this paper, we define Industry 5.0 from its philosophical and historical origin and evolution, emphasize its new thinking on virtual-real duality and human-machine interaction, and introduce its new theory and technology based on parallel intelligence (PI), artificial societies, computational experiments, and parallel execution (the ACP method), and cyber-physical-social systems (CPSS). Case studies and applications of Industry 5.0 over the last decade have been briefly summarized and analyzed with suggestions for its future development. We believe that Industry 5.0 of virtual-real interactive parallel industries has great potentials and is critical for building smart societies. Steps are outlined to ensure a roadmap that would lead to a smooth transition from CPS-based Industry 4.0 to CPSS-based Industry 5.0 for a better world which is Safe in physical spaces, Secure in cyberspaces, Sustainable in ecology, Sensitive in individual privacy and rights, Service for all, and Smartness of all.
- ACP,
- artificial intelligence,
- CPS,
- CPSS,
- Industry 4.0,
- Industry 5.0,
- parallel industries,
- parallel intelligence

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References(96)

References

[1]	M. Minsky, “Steps toward artificial intelligence,” Proc. the IRE, vol. 49, no. 1, pp. 8–30, 1961. doi: 10.1109/JRPROC.1961.287775
[2]	H. Kagermann et al., Recommendations for Implementing the Strategic Initiative Industrie 4.0, 2013.
[3]	F.-Y. Wang, “CAST Lab: A cyber-social-physical approach for traffic control and transportation management,” Intelligent Control and Systems Engineering Center in Chinese Academy of Sciences, Tech. Rep., 1999.
[4]	F.-Y. Wang, “Forward to the past: CASTLab’s cyber-social-physical approach for ITS in 1999,” IEEE Intelligent Transportation Systems Magazine, vol. 16, no. 4, pp. 1–4, 2023.
[5]	F.-Y. Wang, “Industry 4.0: Queen’s new clothes?” China Science Daily, 2014. [Online]. Available: http://news.sciencenet.cn/sbhtmlnews/2014/11/294317.shtm
[6]	F.-Y. Wang, “Parallel networks: From SDN to CPSS-oriented smart networks for IoT,” The 4th Finland-China-Germany Workshop on Mobile Networking, Analytics and Edge Computing, Tech. Rep., Sep, 2017.
[7]	“Industry 5.0: Towards a sustainable, human-centric and resilient European industry,” https://op.europa.eu/en/publication-detail/-/publication/468a892a-5097-11eb-b59f-01aa75ed71a1/.
[8]	F.-Y. Wang, J. Yang, X. Wang et al., “Chat with ChatGPT on Industry 5.0: Learning and decision-making for intelligent industries,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 4, pp. 831–834, 2023. doi: 10.1109/JAS.2023.123552
[9]	Y. Lu, “Industry 4.0: A survey on technologies, applications and open research issues,” Journal of Industrial Information Integration, vol. 6, pp. 1–10, 2017. doi: 10.1016/j.jii.2017.04.005
[10]	P. Skobelev and S. Y. Borovik, “On the way from Industry 4.0 to Industry 5.0: From digital manufacturing to digital society,” Industry 4.0, vol. 2, no. 6, pp. 307–311, 2017.
[11]	V. Özdemir and N. Hekim, “Birth of Industry 5.0: Making sense of big data with artificial intelligence, “the internet of things” and next-generation technology policy,” Omics: A Journal of Integrative Biology, vol. 22, no. 1, pp. 65–76, 2018. doi: 10.1089/omi.2017.0194
[12]	S. Nahavandi, “Industry 5.0: A human-centric solution,” Sustainability, vol. 11, no. 16, p. 4371, 2019. doi: 10.3390/su11164371
[13]	F. Longo, A. Padovano, and S. Umbrello, “Value-oriented and ethical technology engineering in Industry 5.0: A human-centric perspective for the design of the factory of the future,” Applied Sciences, vol. 10, no. 12, p. 4182, 2020. doi: 10.3390/app10124182
[14]	F. Aslam, W. Aimin, M. Li et al., “Innovation in the era of IoT and Industry 5.0: Absolute innovation management (AIM) framework,” Information, vol. 11, no. 2, p. 124, 2020. doi: 10.3390/info11020124
[15]	M. Javaid, A. Haleem, R. P. Singh et al., “Industry 5.0: Potential applications in COVID-19,” Journal of Industrial Integration and Management, vol. 5, no. 4, pp. 507–530, 2020. doi: 10.1142/S2424862220500220
[16]	O. A. ElFar, C.-K. Chang, H. Y. Leong et al., “Prospects of Industry 5.0 in algae: Customization of production and new advance technology for clean bioenergy generation,” Energy Conversion and Management: X, vol. 10, p. 100048, 2021. doi: 10.1016/j.ecmx.2020.100048
[17]	P. K. R. Maddikunta, Q.-V. Pham, B. Prabadevi et al., “Industry 5.0: A survey on enabling technologies and potential applications,” Journal of Industrial Information Integration, vol. 26, p. 100257, 2022. doi: 10.1016/j.jii.2021.100257
[18]	F.-Y. Wang, X. Wang, L. Li, and L. Li, “Steps toward parallel intelligence,” IEEE/CAA J. Autom. Sinica, vol. 3, no. 4, pp. 345–348, 2016. doi: 10.1109/JAS.2016.7510067
[19]	F.-Y. Wang, “Parallel intelligence in metaverses: Welcome to Hanoi!,” IEEE Intelligent Systems, vol. 37, no. 1, pp. 16–20, 2022. doi: 10.1109/MIS.2022.3154541
[20]	F.-Y. Wang, J. J. Zhang et al., “Parallel intelligence: Toward lifelong and eternal developmental AI and learning in cyber-physical-social spaces,” Frontiers of Computer Science, vol. 12, pp. 401–405, 2018. doi: 10.1007/s11704-018-7903-5
[21]	F.-Y. Wang, “The DAO to MetaControl for MetaSystems in Metaverses: The system of parallel control systems for knowledge automation and control intelligence in CPSS,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 11, pp. 1899–1908, 2022. doi: 10.1109/JAS.2022.106022
[22]	F.-Y. Wang, K. M. Carley, D. Zeng, and W. Mao, “Social computing: From social informatics to social intelligence,” IEEE Intelligent systems, vol. 22, no. 2, pp. 79–83, 2007. doi: 10.1109/MIS.2007.41
[23]	F.-Y. Wang, “Toward a paradigm shift in social computing: The ACP approach,” IEEE Intelligent Systems, vol. 22, no. 5, pp. 65–67, 2007. doi: 10.1109/MIS.2007.4338496
[24]	S.-X. Lun, “Research on the classification of parallel execution modes of ACP theory,” Acta Automatica Sinica, vol. 38, no. 10, pp. 1602–1608, 2012. doi: 10.3724/SP.J.1004.2012.01602
[25]	F. Zhu, Y. Lv, Y. Chen et al., “Parallel transportation systems: Toward IoT-enabled smart urban traffic control and management,” IEEE Trans. Intelligent Transportation Systems, vol. 21, no. 10, pp. 4063–4071, 2019.
[26]	F. Zhu, Z. Li, S. Chen et al., “Parallel transportation management and control system and its applications in building smart cities,” IEEE Trans. Intelligent Transportation Systems, vol. 17, no. 6, pp. 1576–1585, 2016. doi: 10.1109/TITS.2015.2506156
[27]	F.-Y. Wang, Y. Gao, X. Shang et al., “Parallel manufacturing and Industries 5.0: From virtual manufacturing to intelligent manufacturing,” Science &Technology Review, vol. 36, no. 21, pp. 10–22, 2018.
[28]	J. Yang, X. Wang, and Y. Zhao, “Parallel manufacturing for industrial metaverses: A new paradigm in smart manufacturing,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 12, pp. 2063–2070, 2022. doi: 10.1109/JAS.2022.106097
[29]	F.-Y. Wang, “Digital agriculture and parallel intelligence: Towards complex adaptive systems for smart agriculture,” CASIA, CASKL-CSIS, Tech. Rep., Octorber 2005.
[30]	X. Wang, M. Kang, H. Sun et al., “DeCASA in agriverse: Parallel agriculture for smart villages in metaverses,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 12, pp. 2055–2062, 2022. doi: 10.1109/JAS.2022.106103
[31]	S. Wang, J. Wang, X. Wang et al., “Blockchain-powered parallel healthcare systems based on the ACP approach,” IEEE Trans. Computational Social Systems, vol. 5, no. 4, pp. 942–950, 2018. doi: 10.1109/TCSS.2018.2865526
[32]	F.-Y. Wang, “Parallel healthcare: Robotic medical and health process automation for secured and smart social healthcares,” IEEE Trans. Computational Social Systems, vol. 7, no. 3, pp. 581–586, 2020. doi: 10.1109/TCSS.2020.2995282
[33]	F.-Y. Wang, “Parallel doctors and parallel hospitals: Impact and perspective of ChatGPT-like AIGC and AGI on medicine and medicare,” Medical Journal of Peking Union Medical College Hospital, vol. 14, no. 4, 2023.
[34]	F.-Y. Wang, “Parallel medicine: From warmness of medicare to medicine of smartness,” Chinese Journal of Intelligent Science and Technology, vol. 3, no. 1, pp. 1–9, 2021.
[35]	X. Gong, X. Liu, S. Jing et al., “Parallel-education-blockchain driven smart education: Challenges and issues,” in Proc. Chinese Automation Congr., 2018, pp. 2390–2395.
[36]	F.-Y. Wang, “Parallel philosophy and intelligent science: From Leibniz’s Monad to Blockchain’s DAO,” Pattern Recognition and Artificial Intelligence, vol. 33, no. 12, pp. 1055–1065, 2020.
[37]	F.-Y. Wang, “Parallel philosophy and intelligent technology: Dual equations and testing systems for parallel industries and smart societies,” Chinese Journal of Intelligent Science and Technology, vol. 3, no. 3, pp. 245–255, 2021.
[38]	F.-Y. Wang, “Parallel philosophy: Origin and goal of intelligent industries and smart economics,” Bulletin of Chinese Academy of Sciences, vol. 36, no. 3, pp. 308–311, 2021.
[39]	F.-Y. Wang, “Artificial intelligence and intelligent transportation: Driving into the 3rd axial age with ITS,” IEEE Intelligent transportation systems magazine, vol. 9, no. 4, pp. 6–9, 2017. doi: 10.1109/MITS.2017.2746407
[40]	H.-S. Tsien, “The sixth industrial revolution and agricultural science and technology,” The Second Academic Committee Meeting of the Chinese Academy of Agricultural Sciences, Tech. Rep., Dec. 23, 1984.
[41]	F.-Y. Wang, “Shadow systems: A new concept for nested and embedded co-simulation for intelligent systems,” Tucson, Arizona, USA: University of Arizona, 1994.
[42]	F.-Y. Wang and X.-C. Huang, “The status quo and future prospective of internet-based intelligent residential systems,” Science and Technology of Household Electric Appliance, vol. 6, pp. 56–61, 2001.
[43]	F.-Y. Wang, “Parallel system methods for management and control of complex systems,” Control and Decision., vol. 19, pp. 485–489, 2004.
[44]	F.-Y. Wang, “The emergence of intelligent enterprises: From CPS to CPSS,” IEEE Intelligent Systems, vol. 25, no. 4, pp. 85–88, 2010. doi: 10.1109/MIS.2010.104
[45]	F.-Y. Wang, “Complexity research and intelligent industries: Parallel times and Industry 5.0,” Control Engineers’ Summit, Tech. Rep., 2014.
[46]	F.-Y. Wang, “X5.0: Parallel intelligence system of parallel times,” Communications of the China Computer Federation, vol. 11, no. 5, pp. 10–14, 2015.
[47]	J.-L. Deng, F.-Y. Wang, Y.-B. Chen et al., “From Industries 4.0 to Energy 5.0: Concept and framework of intelligent energy systems,” Acta Automatica Sinica, vol. 41, no. 12, pp. 2003–2016, 2015.
[48]	MEXT and METI, “The fifth science and technology basic plan,” Japanese Government, Tech. Rep., 2016.
[49]	S. Mystakidis, “Metaverse,” Encyclopedia, vol. 2, no. 1, pp. 486–497, 2022. doi: 10.3390/encyclopedia2010031
[50]	X. Wang, L. Li, Y. Yuan et al., “ACP-based social computing and parallel intelligence: Societies 5.0 and beyond,” CAAI Trans. Intelligence Technology, vol. 1, no. 4, pp. 377–393, 2016. doi: 10.1016/j.trit.2016.11.005
[51]	J. Lu, X. Wang, X. Cheng et al., “Parallel factories for smart industrial operations: From big AI models to field foundational models and scenarios engineering,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 12, pp. 2079–2086, 2022. doi: 10.1109/JAS.2022.106094
[52]	F.-Y. Wang, “The origin and goal of future in CPSS: Industries 5.0 and intelligent industries,” IEEE Int. Conf. on Systems, Man and Cybernetics, Tech. Rep., Oct.07, 2019.
[53]	F.-Y. Wang, Y. Tang, and P. J. Werbos, “Guest editorial: Cyber-physical-social intelligence: Toward metaverse-based smart societies of 6I and 6S,” IEEE Trans. Systems,Man,and Cybernetics: Systems, vol. 53, no. 4, pp. 2018–2024, 2023. doi: 10.1109/TSMC.2023.3243558
[54]	X. Wang, X. Cheng, J. Lu et al., “Metaverses-based parallel oil fields in CPSS: A framework and methodology,” IEEE Trans. Systems,Man,and Cybernetics: Systems, vol. 53, no. 4, pp. 2138–2147, 2023. doi: 10.1109/TSMC.2022.3228934
[55]	F.-Y. Wang, “Vehicle 5.0: From driverless vehicles for ITS in CPS to MetaDriving for smart mobility in CPSS,” IEEE Trans. Intelligent Vehicles, vol. 8, no. 6, pp. 3525–3529, 2023.
[56]	L. Chen et al., “Mining 5.0: Concept and framework for intelligent mining systems in CPSS,” IEEE Trans. Intelligent Vehicles, vol. 8, no. 6, pp. 3530–3536, 2023.
[57]	Y. Lin et al., “Mobility 5.0: Smart logistics and transportation services in cyber-physical-social systems,” IEEE Trans. Intelligent Vehicles, vol. 8, no. 6, pp. 3537–3541, 2023.
[58]	J. Wang, Y. Tian, Y. Wang et al., “A framework and operational procedures for metaverses-based industrial foundation models,” IEEE Trans. Systems,Man,and Cybernetics: Systems, vol. 53, no. 4, pp. 2037–2046, 2023. doi: 10.1109/TSMC.2022.3226755
[59]	Y. Wang, Y. Tian, J. Wang et al., “Integrated inspection of QoM, QoP, and QoS for AOI industries in metaverses,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 12, pp. 2071–2078, 2022. doi: 10.1109/JAS.2022.106091
[60]	Y. Shen, Y. Liu, Y. Tian et al., “Parallel sensing in metaverses: Virtual-real interactive smart systems for “6S” sensing,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 12, pp. 2047–2054, 2022. doi: 10.1109/JAS.2022.106115
[61]	X. Li, P. Ye, J. Li et al., “From features engineering to scenarios engineering for trustworthy AI: I&I, C&C, and V&V,” IEEE Intelligent Systems, vol. 37, no. 4, pp. 18–26, 2022. doi: 10.1109/MIS.2022.3197950
[62]	F.-Y. Wang, “Parallel management: The DAO to smart ecological technology for complexity management intelligence,” Acta Automatica Sinica, vol. 48, no. 11, pp. 2655–2665, 2022.
[63]	X. Li, Y. Tian, P. Ye, H. Duan, and F.-Y. Wang, “A novel scenarios engineering methodology for foundation models in metaverse,” IEEE Trans. Systems,Man,and Cybernetics: Systems, vol. 53, no. 4, pp. 2148–2159, 2023. doi: 10.1109/TSMC.2022.3228594
[64]	X. Li, K. Wang, X. Gu, F. Deng, and F.-Y. Wang, “Paralleleye pipeline: An effective method to synthesize images for improving the visual intelligence of intelligent vehicles,” IEEE Trans. Systems,Man,and Cybernetics: Systems, pp. 1–12, 2023.
[65]	F.-Y. Wang, “The metaverse of mind: Perspectives on DeSci for DeEco and DeSoc,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 12, pp. 2043–2046, 2022. doi: 10.1109/JAS.2022.106106
[66]	F.-Y. Wang, R. Qin et al., “Metasocieties in metaverse: Metaeconomics and metamanagement for metaenterprises and metacities,” IEEE Trans. Computational Social Systems, vol. 9, no. 1, pp. 2–7, 2022. doi: 10.1109/TCSS.2022.3145165
[67]	Q. Miao, W. Zheng, Y. Lv et al., “DAO to HANOI via DeSci: AI paradigm shifts from AlphaGo to ChatGPT,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 4, pp. 877–897, 2023. doi: 10.1109/JAS.2023.123561
[68]	S. Wang, Y. Yuan, X. Wang et al., “An overview of smart contract: Architecture, applications, and future trends,” in Proc. IEEE Intelligent Vehicles Symp., 2018, pp. 108–113.
[69]	Z. Zheng, S. Xie, H.-N. Dai et al., “An overview on smart contracts: Challenges, advances and platforms,” Future Generation Computer Systems, vol. 105, pp. 475–491, 2020. doi: 10.1016/j.future.2019.12.019
[70]	Y. Yuan and F.-Y. Wang, “Towards blockchain-based intelligent transportation systems,” in Proc. IEEE 19th Int. Conf. Intelligent Transportation Systems, 2016, pp. 2663–2668.
[71]	Y. Yuan and F.-Y. Wang, “Blockchain and cryptocurrencies: Model, techniques, and applications,” IEEE Trans. Systems,Man,and Cybernetics: Systems, vol. 48, no. 9, pp. 1421–1428, 2018. doi: 10.1109/TSMC.2018.2854904
[72]	S. Wang, L. Ouyang, Y. Yuan et al., “Blockchain-enabled smart contracts: Architecture, applications, and future trends,” IEEE Trans. Systems,Man,and Cybernetics: Systems, vol. 49, no. 11, pp. 2266–2277, 2019. doi: 10.1109/TSMC.2019.2895123
[73]	F.-Y. Wang and J. J. Zhang, “Transportation 5.0 in CPSS: Towards ACP-based society-centered intelligent transportation,” in Proc. IEEE 20th Int. Conf. Intelligent Transportation Systems, 2017, pp. 762–767.
[74]	Y. Chen, H. Zhang, and F.-Y. Wang, “Society-centered and DAO-powered sustainability in Transportation 5.0: An intelligent vehicles perspective,” IEEE Trans. Intelligent Vehicles, vol. 8, no. 4, pp. 2635–2638, 2023. doi: 10.1109/TIV.2023.3264585
[75]	H. Du, S. Teng, H. Chen et al., “Chat with ChatGPT on intelligent vehicles: An IEEE TIV perspective,” IEEE Trans. Intelligent Vehicles, vol. 8, no. 3, pp. 2020–2026, 2023. doi: 10.1109/TIV.2023.3253281
[76]	C. Zhao, Y. Lv, J. Jin et al., “DeCAST in TransVerse for parallel intelligent transportation systems and smart cities: Three decades and beyond,” IEEE Intelligent Transportation Systems Magazine, vol. 14, pp. 6–17, 2022.
[77]	F.-Y. Wang, “Parallel control and management for intelligent transportation systems: Concepts, architectures, and applications,” IEEE Trans. Intelligent Transportation Systems, vol. 11, pp. 630–638, 2010. doi: 10.1109/TITS.2010.2060218
[78]	N. Zhang, F.-Y. Wang, F. Zhu et al., “DynaCAS: Computational experiments and decision support for ITS,” IEEE Intelligent Systems, vol. 23, no. 6, pp. 19–23, 2008. doi: 10.1109/MIS.2008.101
[79]	F.-Y. Wang, N.-N. Zheng et al., “Parallel driving in CPSS: A unified approach for transport automation and vehicle intelligence,” IEEE/CAA J. Autom. Sinica, vol. 4, no. 4, pp. 577–587, 2017. doi: 10.1109/JAS.2017.7510598
[80]	K. Wang, C. Gou, N. Zheng et al., “Parallel vision for perception and understanding of complex scenes: Methods, framework, and perspectives,” Artificial Intelligence Review, vol. 48, pp. 299–329, 2017. doi: 10.1007/s10462-017-9569-z
[81]	J. Yang, S. Li, X. Wang et al., “DeFACT in ManuVerse for parallel manufacturing: Foundation models and parallel workers in smart factories,” IEEE Trans. Systems,Man,and Cybernetics: Systems, vol. 53, no. 4, pp. 2188–2199, 2023. doi: 10.1109/TSMC.2022.3228817
[82]	T. Bai, Z. Shen, Y. Liu et al., “Parallel machine: A framework for the control and management for intelligent machines,” Chinese Journal of Intelligent Science and Technology, vol. 1, no. 2, pp. 181–191, 2019.
[83]	J. J. Zhang, D. W. Gao, Y. Zhang et al., “Social energy: Mining energy from the society,” IEEE/CAA J. Autom. Sinica, vol. 4, no. 3, pp. 466–482, 2017. doi: 10.1109/JAS.2017.7510547
[84]	T.-X. Bai, S. Wang, Z. Shen et al., “Parallel robotics and parallel unmanned systems: Framework, structure, process, platform and applications,” Acta Automatica Sinica, vol. 43, no. 2, pp. 161–175, 2017.
[85]	L. Chen, W. Yu, D. Cao et al., “Parallel unmanned system,” Unmanned Systems Technology, vol. 1, no. 1, pp. 23–37, 2018.
[86]	J. Yang, X. Wang, Y. Wang et al., “Parallel intelligence and CPSS in 30 years: An ACP approach,” Acta Automatica Sinica, vol. 49, no. 3, pp. 614–634, 2023.
[87]	T. Shen, C. Gou, J. Wang et al., “Parallel medical imaging: An ACP- based approach for intelligent medical image recognition with small samples,” in Proc. IEEE 1st Int. Conf. Digital Twins and Parallel Intelligence, 2021, pp. 226–229.
[88]	F.-Y. Wang, “Digital doctors and parallel healthcare: From medical knowledge automation to intelligent metasystems medicine,” Medical Journal of Peking Union Medical College Hospital, vol. 12, no. 6, pp. 829–833, 2021.
[89]	F.-Y. Wang, C. Gou, J. Wang et al., “Parallel skin: A vision-based dermatological analysis framework,” Journal of Pattern Recognition and Artificial Intelligence, vol. 7, pp. 577–588, 2019.
[90]	F.-Y. Wang, C. Li et al., “Parallel gout: An ACP-based system framework for gout diagnosis and treatment,” Pattern Recognition and Artificial Intelligence, vol. 30, no. 12, pp. 1057–1068, 2017.
[91]	F.-Y. Wang, M. Zhang et al., “Parallel eyes: An ACP-based smart ophthalmic diagnosis and treatment,” Pattern Recognition and Artificial Intelligence, vol. 31, no. 6, pp. 495–504, 2018.
[92]	M. Zhang, L. Chen et al., “Parallel gastrointestine: An ACP-based approach for intelligent operations,” Pattern Recognition and Artificial Intelligence, vol. 32, no. 12, pp. 1061–1071, 2019.
[93]	M. Kang, X.-R. Fan, J. Hua et al., “Managing traditional solar greenhouse with CPSS: A just-for-fit philosophy,” IEEE Trans. cybernetics, vol. 48, no. 12, pp. 3371–3380, 2018. doi: 10.1109/TCYB.2018.2858264
[94]	M. Kang and F.-Y. Wang, “From parallel plants to smart plants: Intelligent control and management for plant growth,” IEEE/CAA J. Autom. Sinica, vol. 4, no. 2, pp. 161–166, 2017. doi: 10.1109/JAS.2017.7510487
[95]	M. Kang, X. Wang, H. Wang et al., “The development of AgriVerse: Past, present, and future,” IEEE Trans. Systems,Man,and Cybernetics: Systems, vol. 53, no. 6, pp. 3718–3727, 2023. doi: 10.1109/TSMC.2022.3230830
[96]	F.-Y. Wang, Q. Miao, X. Li et al., “What does ChatGPT say: The DAO from algorithmic intelligence to linguistic intelligence,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 3, pp. 575–579, 2023. doi: 10.1109/JAS.2023.123486

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通讯作者: 陈斌, bchen63@163.com

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沈阳化工大学材料科学与工程学院沈阳 110142

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There has been a recent surge in intense discussions and studies on Industry 5.0, garnering the interest of researchers, entrepreneurs, and policymakers from various sectors worldwide. However, a consensus has yet to be reached regarding the specific characteristics of Industry 5.0. This paper defines Industry 5.0 from its philosophical and historical origin and evolution
The new thinking of Industry 5.0 on virtual-real duality and human-machine interaction is presented in this paper. Its new theory and technology, which are based on Parallel Intelligence (PI), Artificial Societies, Computational Experiments, and Parallel Execution (the ACP method), and Cyber-Physical-Social Systems (CPSS), are introduced
Some case studies and applications of Industry 5.0 over the last decade have been briefly summarized and analyzed, providing valuable insights and suggestions for its future development

Steps Toward Industry 5.0: Building “6S” Parallel Industries With Cyber-Physical-Social Intelligence

doi: 10.1109/JAS.2023.123753

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通讯作者: 陈斌, bchen63@163.com

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