{"title":"用于智能制造系统的工业生成预训练变压器","authors":"Han Wang, Min Liu, Weiming Shen","doi":"10.1049/cim2.12078","DOIUrl":null,"url":null,"abstract":"<p>Manufacturing enterprises are facing how to utilise industrial knowledge and continuously accumulating massive unlabelled data to achieve human-cyber-physical collaborative and autonomous intelligence. Recently, artificial intelligence-generative content has achieved great performance in several domains and scenarios. A new concept of industrial generative pre-trained Transformer (Industrial-GPT) for intelligent manufacturing systems is introduced to solve various scenario tasks. It refers to pre-training with industrial datasets, fine-tuning with industrial scenarios, and reinforcement learning with domain knowledge. To enable Industrial-GPT to better empower the manufacturing industry, Model as a Service is introduced to cloud computing as a new service mode, which provides a more efficient and flexible service approach by directly invoking the general model of the upper layer and customising it for specific businesses. Then, the operation mechanism of the Industrial-GPT driven intelligent manufacturing system is described. Finally, the challenges and prospects of applying the Industrial-GPT in the manufacturing industry are discussed.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"5 2","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12078","citationCount":"1","resultStr":"{\"title\":\"Industrial-generative pre-trained transformer for intelligent manufacturing systems\",\"authors\":\"Han Wang, Min Liu, Weiming Shen\",\"doi\":\"10.1049/cim2.12078\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Manufacturing enterprises are facing how to utilise industrial knowledge and continuously accumulating massive unlabelled data to achieve human-cyber-physical collaborative and autonomous intelligence. Recently, artificial intelligence-generative content has achieved great performance in several domains and scenarios. A new concept of industrial generative pre-trained Transformer (Industrial-GPT) for intelligent manufacturing systems is introduced to solve various scenario tasks. It refers to pre-training with industrial datasets, fine-tuning with industrial scenarios, and reinforcement learning with domain knowledge. To enable Industrial-GPT to better empower the manufacturing industry, Model as a Service is introduced to cloud computing as a new service mode, which provides a more efficient and flexible service approach by directly invoking the general model of the upper layer and customising it for specific businesses. Then, the operation mechanism of the Industrial-GPT driven intelligent manufacturing system is described. Finally, the challenges and prospects of applying the Industrial-GPT in the manufacturing industry are discussed.</p>\",\"PeriodicalId\":33286,\"journal\":{\"name\":\"IET Collaborative Intelligent Manufacturing\",\"volume\":\"5 2\",\"pages\":\"\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2023-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12078\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Collaborative Intelligent Manufacturing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/cim2.12078\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Collaborative Intelligent Manufacturing","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/cim2.12078","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
Industrial-generative pre-trained transformer for intelligent manufacturing systems
Manufacturing enterprises are facing how to utilise industrial knowledge and continuously accumulating massive unlabelled data to achieve human-cyber-physical collaborative and autonomous intelligence. Recently, artificial intelligence-generative content has achieved great performance in several domains and scenarios. A new concept of industrial generative pre-trained Transformer (Industrial-GPT) for intelligent manufacturing systems is introduced to solve various scenario tasks. It refers to pre-training with industrial datasets, fine-tuning with industrial scenarios, and reinforcement learning with domain knowledge. To enable Industrial-GPT to better empower the manufacturing industry, Model as a Service is introduced to cloud computing as a new service mode, which provides a more efficient and flexible service approach by directly invoking the general model of the upper layer and customising it for specific businesses. Then, the operation mechanism of the Industrial-GPT driven intelligent manufacturing system is described. Finally, the challenges and prospects of applying the Industrial-GPT in the manufacturing industry are discussed.
期刊介绍:
IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly.
The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).