Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/108878
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dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorFu, Ten_US
dc.creatorLiu, Sen_US
dc.creatorLi, Pen_US
dc.date.accessioned2024-09-04T07:42:13Z-
dc.date.available2024-09-04T07:42:13Z-
dc.identifier.issn2095-7513en_US
dc.identifier.urihttp://hdl.handle.net/10397/108878-
dc.language.isoenen_US
dc.publisherHigher Education Pressen_US
dc.rights© The Author(s) 2024. This article is published with open access at link.springer.com and journal.hep.com.cnen_US
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.rightsThe following publication Fu, T., Liu, S. & Li, P. Intelligent smelting process, management system: Efficient and intelligent management strategy by incorporating large language model. Front. Eng. Manag. 11, 396–412 (2024) is available at https://doi.org/10.1007/s42524-024-4013-y.en_US
dc.subjectChatGPTen_US
dc.subjectIntelligent Q & Aen_US
dc.subjectLarge language modelsen_US
dc.subjectProcess managementen_US
dc.subjectSmelting steelen_US
dc.titleIntelligent smelting process, management system : efficient and intelligent management strategy by incorporating large language modelen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage396en_US
dc.identifier.epage412en_US
dc.identifier.volume11en_US
dc.identifier.issue3en_US
dc.identifier.doi10.1007/s42524-024-4013-yen_US
dcterms.abstractIn the steelmaking industry, enhancing production cost-effectiveness and operational efficiency requires the integration of intelligent systems to support production activities. Thus, effectively integrating various production modules is crucial to enable collaborative operations throughout the entire production chain, reducing management costs and complexities. This paper proposes, for the first time, the integration of Vision-Language Model (VLM) and Large Language Model (LLM) technologies in the steel manufacturing domain, creating a novel steelmaking process management system. The system facilitates data collection, analysis, visualization, and intelligent dialogue for the steelmaking process. The VLM module provides textual descriptions for slab defect detection, while LLM technology supports the analysis of production data and intelligent question-answering. The feasibility, superiority, and effectiveness of the system are demonstrated through production data and comparative experiments. The system has significantly lowered costs and enhanced operational understanding, marking a critical step toward intelligent and cost-effective management in the steelmaking domain.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationFrontiers of engineering management, Sept 2024, v. 11, no. 3, p. 396-412en_US
dcterms.isPartOfFrontiers of engineering managementen_US
dcterms.issued2024-09-
dc.identifier.scopus2-s2.0-85198061983-
dc.identifier.eissn2096-0255en_US
dc.description.validate202409 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_TA-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.TASpringer Nature (2024)en_US
dc.description.oaCategoryTAen_US
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