Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/113293
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dc.contributorDepartment of Industrial and Systems Engineering-
dc.contributorResearch Institute for Advanced Manufacturing-
dc.contributorResearch Centre for Digital Transformation of Tourism-
dc.creatorYuan, Zen_US
dc.creatorLi, Men_US
dc.creatorLiu, Cen_US
dc.creatorHan, Fen_US
dc.creatorHuang, Hen_US
dc.creatorDai, HNen_US
dc.date.accessioned2025-06-02T06:57:31Z-
dc.date.available2025-06-02T06:57:31Z-
dc.identifier.issn0278-6125en_US
dc.identifier.urihttp://hdl.handle.net/10397/113293-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2025 The Authors. Published by Elsevier Ltd on behalf of The Society of Manufacturing Engineers. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.rightsThe following publication Yuan, Z., Li, M., Liu, C., Han, F., Huang, H., & Dai, H. N. (2025). Chat with MES: LLM-driven user interface for manipulating garment manufacturing system through natural language. Journal of Manufacturing Systems, 80, 1093-1107 is available at https://doi.org/10.1016/j.jmsy.2025.02.008.en_US
dc.subjectHuman-computer interactionen_US
dc.subjectInteractive Manufacturing Execution Systemen_US
dc.subjectLarge language modelen_US
dc.subjectLLM-Agenten_US
dc.subjectText2SQLen_US
dc.titleChat with MES : LLM-driven user interface for manipulating garment manufacturing system through natural languageen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1093en_US
dc.identifier.epage1107en_US
dc.identifier.volume80en_US
dc.identifier.doi10.1016/j.jmsy.2025.02.008en_US
dcterms.abstractThis paper presents Chat with MES (CWM), an AI agent system, which integrates LLMs into the Manufacturing Execution System (MES), serving as the “ears, mouth, and the brain”. This system promotes a paradigm shift in MES interactions from Graphical User Interface (GUI) to natural language interface”, offering a more natural and efficient way for workers to manipulate the manufacturing system. Compared with the traditional GUI, both the maintenance costs for developers and the learning costs and the complexity of use for workers are significantly reduced. This paper also contributes two technical improvements to address the challenges of using LLM-Agent in serious manufacturing scenarios. The first one is Request Rewriting, designed to rephrase or automatically follow up on non-standardized and ambiguous requests from users. The second innovation is the Multi-Step Dynamic Operations Generation, which is a pre-execution planning technique similar to Chain-of-Thought (COT), used to enhance the success rate of handling complex tasks involving multiple operations. A case study conducted on a simulated garment MES with 55 manually designed requests demonstrates the high execution accuracy of CWM (80%) and the improvement achieved through query rewriting (9.1%) and Multi-Step Dynamic operations generation (18.2%). The source code of CWM, along with the simulated MES and benchmark requests, is publicly accessible.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of manufacturing systems, June 2025, v. 80, p. 1093-1107en_US
dcterms.isPartOfJournal of manufacturing systemsen_US
dcterms.issued2025-06-
dc.identifier.scopus2-s2.0-105000541506-
dc.description.validate202506 bcfc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_TA-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextthe Innovation and Technology Fund, China (No. PRP/015/24TI); the Innovation and Technology Commission of the HKSAR Government through the InnoHK initiative .en_US
dc.description.pubStatusPublisheden_US
dc.description.TAElsevier (2025)en_US
dc.description.oaCategoryTAen_US
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