When Embodied AI Meets Industry 5.0: Human-Centered Smart Manufacturing

被引:0
|
作者
Xu, Jing [1 ]
Sun, Qiyu [1 ]
Han, Qing-Long [2 ]
Tang, Yang [1 ]
机构
[1] East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China
[2] Swinburne Univ Technol, Sch Sci Comp & Engn Technol, Hawthorn, Vic 3122, Australia
基金
中国国家自然科学基金;
关键词
Training; Productivity; Manufacturing industries; Cloud computing; Job shop scheduling; Large language models; Collaboration; Smart systems; Fifth Industrial Revolution; Smart manufacturing; Embodied AI; human-centered manufacturing; Industry; 5.0; internet of things; large multi-mode language models; INTERNET; COMMUNICATION; FUTURE; THINGS; MODEL;
D O I
10.1109/JAS.2025.125327
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
As embodied intelligence (EI), large language models (LLMs), and cloud computing continue to advance, Industry 5.0 facilitates the development of industrial artificial intelligence (IndAI) through cyber-physical-social systems (CPSSs) with a human-centric focus. These technologies are organized by the system-wide approach of Industry 5.0, in order to empower the manufacturing industry to achieve broader societal goals of job creation, economic growth, and green production. This survey first provides a general framework of smart manufacturing in the context of Industry 5.0. Wherein, the embodied agents, like robots, sensors, and actuators, are the carriers for IndAI, facilitating the development of the self-learning intelligence in individual entities, the collaborative intelligence in production lines and factories (smart systems), and the swarm intelligence within industrial clusters (systems of smart systems). Through the framework of CPSSs, the key technologies and their possible applications for supporting the single-agent, multi-agent and swarm-agent embodied IndAI have been reviewed, such as the embodied perception, interaction, scheduling, multi-mode large language models, and collaborative training. Finally, to stimulate future research in this area, the open challenges and opportunities of applying Industry 5.0 to smart manufacturing are identified and discussed. The perspective of Industry 5.0-driven manufacturing industry aims to enhance operational productivity and efficiency by seamlessly integrating the virtual and physical worlds in a human-centered manner, thereby fostering an intelligent, sustainable, and resilient industrial landscape.
引用
收藏
页码:485 / 501
页数:17
相关论文
共 50 条
  • [41] Human-Centered Explainable AI at the Edge for eHealth
    Dutta, Joy
    Puthal, Deepak
    2023 IEEE INTERNATIONAL CONFERENCE ON EDGE COMPUTING AND COMMUNICATIONS, EDGE, 2023, : 227 - 232
  • [42] Review of Human-Centered Explainable AI in Healthcare
    Song, Shuchao
    Chen, Yiqiang
    Yu, Hanchao
    Zhang, Yingwei
    Yang, Xiaodong
    Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics, 2024, 36 (05): : 645 - 657
  • [43] Human-centered redistricting automation in the age of AI
    Cho, Wendy K. Tam
    Cain, Bruce E.
    SCIENCE, 2020, 369 (6508) : 1179 - 1181
  • [44] Operationalizing Human-Centered Perspectives in Explainable AI
    Ehsan, Upol
    Wintersberger, Philipp
    Liao, Q. Vera
    Mara, Martina
    Streit, Marc
    Wachter, Sandra
    Riener, Andreas
    Riedl, Mark O.
    EXTENDED ABSTRACTS OF THE 2021 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI'21), 2021,
  • [45] Human-centered AI through employee participation
    Haipeter, Thomas
    Wannoeffel, Manfred
    Daus, Jan-Torge
    Schaffarczik, Sandra
    FRONTIERS IN ARTIFICIAL INTELLIGENCE, 2024, 7
  • [46] AI and student assessment in human-centered education
    Balducci, Bruno
    FRONTIERS IN EDUCATION, 2024, 9
  • [47] Explaining AI Decisions: Towards Achieving Human-Centered Explainability in Smart Home Environments
    Shajalal, Md
    Boden, Alexander
    Stevens, Gunnar
    Du, Delong
    Kern, Dean-Robin
    EXPLAINABLE ARTIFICIAL INTELLIGENCE, XAI 2024, PT IV, 2024, 2156 : 418 - 440
  • [48] Human-Centered Approaches to Fair and Responsible AI
    Lee, Min Kyung
    Grgic-Hlaca, Nina
    Tschantz, Michael Carl
    Binns, Reuben
    Weller, Adrian
    Carney, Michelle
    Inkpen, Kori
    CHI'20: EXTENDED ABSTRACTS OF THE 2020 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, 2020,
  • [49] Editorial: Human-centered AI: Crowd computing
    Yang, Jie
    Bozzon, Alessandro
    Gadiraju, Ujwal
    Lease, Matthew
    FRONTIERS IN ARTIFICIAL INTELLIGENCE, 2023, 6
  • [50] Towards human-centered artificial intelligence (AI) in architecture, engineering, and construction (AEC) industry
    Rafsanjani, Hamed Nabizadeh
    Nabizadeh, Amir Hossein
    COMPUTERS IN HUMAN BEHAVIOR REPORTS, 2023, 11