Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/108878
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Industrial and Systems Engineering | en_US |
| dc.creator | Fu, T | en_US |
| dc.creator | Liu, S | en_US |
| dc.creator | Li, P | en_US |
| dc.date.accessioned | 2024-09-04T07:42:13Z | - |
| dc.date.available | 2024-09-04T07:42:13Z | - |
| dc.identifier.issn | 2095-7513 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/108878 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Higher Education Press | en_US |
| dc.rights | © The Author(s) 2024. This article is published with open access at link.springer.com and journal.hep.com.cn | en_US |
| dc.rights | This 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.rights | The 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.subject | ChatGPT | en_US |
| dc.subject | Intelligent Q & A | en_US |
| dc.subject | Large language models | en_US |
| dc.subject | Process management | en_US |
| dc.subject | Smelting steel | en_US |
| dc.title | Intelligent smelting process, management system : efficient and intelligent management strategy by incorporating large language model | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 396 | en_US |
| dc.identifier.epage | 412 | en_US |
| dc.identifier.volume | 11 | en_US |
| dc.identifier.issue | 3 | en_US |
| dc.identifier.doi | 10.1007/s42524-024-4013-y | en_US |
| dcterms.abstract | In 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.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Frontiers of engineering management, Sept 2024, v. 11, no. 3, p. 396-412 | en_US |
| dcterms.isPartOf | Frontiers of engineering management | en_US |
| dcterms.issued | 2024-09 | - |
| dc.identifier.scopus | 2-s2.0-85198061983 | - |
| dc.identifier.eissn | 2096-0255 | en_US |
| dc.description.validate | 202409 bcch | en_US |
| dc.description.oa | Version of Record | en_US |
| dc.identifier.FolderNumber | OA_TA | - |
| dc.description.fundingSource | Self-funded | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.TA | Springer Nature (2024) | en_US |
| dc.description.oaCategory | TA | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| s42524-024-4013-y.pdf | 2.34 MB | Adobe PDF | View/Open |
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