AIGC-empowered smart manufacturing: Prospects and challenges

IF 11.4 1区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Robotics and Computer-integrated Manufacturing Pub Date : 2025-06-10 DOI:10.1016/j.rcim.2025.103076

Jiewu Leng , Keyou Zheng , Rongjie Li , Chong Chen , Baicun Wang , Qiang Liu , Xin Chen , Weiming Shen

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Abstract

Generative AI (GenAI), the technology behind Artificial Intelligence Generated Content (AIGC), has emerged as a transformative technology in smart manufacturing. However, its full potential and integration within manufacturing processes remain unexplored. This paper presents a comprehensive framework that aligns a GenAI-centered approach with Product Lifecycle Management (PLM), systematically examining the AIGC landscape and its applications across various manufacturing phases. To ensure accuracy and relevance, a human-in-the-loop pipeline is employed to curate and analyze cutting-edge research. Key contributions of this study include: 1) a holistic perspective on AIGC-empowered smart manufacturing, 2) an in-depth analysis of the current technological landscape, and 3) the identification of critical research challenges and future directions. Additionally, the paper considers Industry 5.0 principles, emphasizing human-centricity, sustainability, and resilience. By fostering discussion and collaboration, this review aims to advance innovation and unlock the full potential of AIGC in smart manufacturing.

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aigc授权的智能制造：前景与挑战

作为人工智能生成内容（AIGC）背后的技术，生成式人工智能（GenAI）已成为智能制造领域的变革性技术。然而，它的全部潜力和在制造过程中的集成仍未得到探索。本文提出了一个综合框架，该框架将以基因人工智能为中心的方法与产品生命周期管理（PLM）相结合，系统地检查了AIGC景观及其在各个制造阶段的应用。为了确保准确性和相关性，我们采用了人在循环的管道来策划和分析前沿研究。本研究的主要贡献包括：1)对aigc驱动的智能制造的整体视角，2)对当前技术格局的深入分析，以及3)确定关键研究挑战和未来方向。此外，本文考虑了工业5.0原则，强调以人为中心、可持续性和弹性。通过促进讨论和合作，本次审查旨在推动创新，并释放AIGC在智能制造中的全部潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Robotics and Computer-integrated Manufacturing 工程技术-工程：制造

CiteScore

24.10

自引率

13.50%

发文量

160

审稿时长

50 days

期刊介绍： The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.