在下一代智能制造中利用大型语言模型:回顾与展望

IF 14.2 1区 工程技术 Q1 ENGINEERING, INDUSTRIAL
Yunfei Ma , Shuai Zheng , Zheng Yang , Pai Zheng , Jiewu Leng , Jun Hong
{"title":"在下一代智能制造中利用大型语言模型:回顾与展望","authors":"Yunfei Ma ,&nbsp;Shuai Zheng ,&nbsp;Zheng Yang ,&nbsp;Pai Zheng ,&nbsp;Jiewu Leng ,&nbsp;Jun Hong","doi":"10.1016/j.jmsy.2025.07.019","DOIUrl":null,"url":null,"abstract":"<div><div>Industry 5.0, as the guiding ideology of the new generation intelligent manufacturing, points the way for global industrial transformation. It emphasizes the collaborative cooperation between humans, machines and intelligent systems, and places humans at the core of the industrial production process, aiming to create a more flexible, personalized and sustainable production paradigm. Large language model, as an advanced natural language processing technology, has received attention from researchers related to Industry 5.0 due to its ease of use and powerful language processing capability. LLM is considered to be one of the key enabling technologies to drive the development of Industry 5.0 and has great application potential. After a rigorous review of existing approaches, we find there is few existing survey papers that focuses on how LLM will drive the development of Industry 5.0 applications. Therefore, this paper provides a comprehensive review of the application of LLM in the field of Industry 5.0. Firstly, we conduct a literature review to explore the current state of research related to Industry 5.0. Subsequently, we analyze LLM-based technologies, synergizing LLMs with Industry 5.0 enablers and the applications of LLM in various domains of intelligent manufacturing. Finally, we explore the challenges of LLM in real-world scenarios and future research directions in the context of Industry 5.0. It is hoped that this study will contribute to the further development of LLM-based solutions in the context of Industry 5.0 and unite various efforts to achieve the vision of Industry 5.0.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"82 ","pages":"Pages 809-840"},"PeriodicalIF":14.2000,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Leveraging large language models in next generation intelligent manufacturing: Retrospect and prospect\",\"authors\":\"Yunfei Ma ,&nbsp;Shuai Zheng ,&nbsp;Zheng Yang ,&nbsp;Pai Zheng ,&nbsp;Jiewu Leng ,&nbsp;Jun Hong\",\"doi\":\"10.1016/j.jmsy.2025.07.019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Industry 5.0, as the guiding ideology of the new generation intelligent manufacturing, points the way for global industrial transformation. It emphasizes the collaborative cooperation between humans, machines and intelligent systems, and places humans at the core of the industrial production process, aiming to create a more flexible, personalized and sustainable production paradigm. Large language model, as an advanced natural language processing technology, has received attention from researchers related to Industry 5.0 due to its ease of use and powerful language processing capability. LLM is considered to be one of the key enabling technologies to drive the development of Industry 5.0 and has great application potential. After a rigorous review of existing approaches, we find there is few existing survey papers that focuses on how LLM will drive the development of Industry 5.0 applications. Therefore, this paper provides a comprehensive review of the application of LLM in the field of Industry 5.0. Firstly, we conduct a literature review to explore the current state of research related to Industry 5.0. Subsequently, we analyze LLM-based technologies, synergizing LLMs with Industry 5.0 enablers and the applications of LLM in various domains of intelligent manufacturing. Finally, we explore the challenges of LLM in real-world scenarios and future research directions in the context of Industry 5.0. It is hoped that this study will contribute to the further development of LLM-based solutions in the context of Industry 5.0 and unite various efforts to achieve the vision of Industry 5.0.</div></div>\",\"PeriodicalId\":16227,\"journal\":{\"name\":\"Journal of Manufacturing Systems\",\"volume\":\"82 \",\"pages\":\"Pages 809-840\"},\"PeriodicalIF\":14.2000,\"publicationDate\":\"2025-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Manufacturing Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0278612525001943\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Manufacturing Systems","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0278612525001943","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0

摘要

工业5.0作为新一代智能制造的指导思想,为全球产业转型指明了方向。它强调人、机器和智能系统之间的协同合作,将人置于工业生产过程的核心,旨在创造一种更加灵活、个性化和可持续的生产模式。大型语言模型作为一种先进的自然语言处理技术,因其易于使用和强大的语言处理能力而受到了工业5.0相关研究人员的关注。LLM被认为是推动工业5.0发展的关键使能技术之一,具有巨大的应用潜力。经过对现有方法的严格审查,我们发现很少有现有的调查论文关注LLM将如何推动工业5.0应用程序的开发。因此,本文对LLM在工业5.0领域的应用进行了全面的综述。首先,我们对工业5.0相关的研究现状进行了文献综述。随后,我们分析了基于LLM的技术,LLM与工业5.0的协同作用以及LLM在智能制造各个领域的应用。最后,我们探讨了LLM在现实场景中的挑战以及在工业5.0背景下的未来研究方向。希望本研究能为工业5.0背景下基于llm的解决方案的进一步发展做出贡献,并联合各方力量实现工业5.0的愿景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leveraging large language models in next generation intelligent manufacturing: Retrospect and prospect
Industry 5.0, as the guiding ideology of the new generation intelligent manufacturing, points the way for global industrial transformation. It emphasizes the collaborative cooperation between humans, machines and intelligent systems, and places humans at the core of the industrial production process, aiming to create a more flexible, personalized and sustainable production paradigm. Large language model, as an advanced natural language processing technology, has received attention from researchers related to Industry 5.0 due to its ease of use and powerful language processing capability. LLM is considered to be one of the key enabling technologies to drive the development of Industry 5.0 and has great application potential. After a rigorous review of existing approaches, we find there is few existing survey papers that focuses on how LLM will drive the development of Industry 5.0 applications. Therefore, this paper provides a comprehensive review of the application of LLM in the field of Industry 5.0. Firstly, we conduct a literature review to explore the current state of research related to Industry 5.0. Subsequently, we analyze LLM-based technologies, synergizing LLMs with Industry 5.0 enablers and the applications of LLM in various domains of intelligent manufacturing. Finally, we explore the challenges of LLM in real-world scenarios and future research directions in the context of Industry 5.0. It is hoped that this study will contribute to the further development of LLM-based solutions in the context of Industry 5.0 and unite various efforts to achieve the vision of Industry 5.0.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Manufacturing Systems
Journal of Manufacturing Systems 工程技术-工程:工业
CiteScore
23.30
自引率
13.20%
发文量
216
审稿时长
25 days
期刊介绍: The Journal of Manufacturing Systems is dedicated to showcasing cutting-edge fundamental and applied research in manufacturing at the systems level. Encompassing products, equipment, people, information, control, and support functions, manufacturing systems play a pivotal role in the economical and competitive development, production, delivery, and total lifecycle of products, meeting market and societal needs. With a commitment to publishing archival scholarly literature, the journal strives to advance the state of the art in manufacturing systems and foster innovation in crafting efficient, robust, and sustainable manufacturing systems. The focus extends from equipment-level considerations to the broader scope of the extended enterprise. The Journal welcomes research addressing challenges across various scales, including nano, micro, and macro-scale manufacturing, and spanning diverse sectors such as aerospace, automotive, energy, and medical device manufacturing.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信