Text2UA: Automatic OPC UA Information Modeling from Textual Data With Large Language Model

Dear Editor, This letter deals with automatically constructing an OPC UA information model (IM) aimed at enhancing data interoperability among heterogeneous system components within manufacturing automation systems. Empowered by the large language model (LLM), we propose a novel multi-agent collaborative framework to streamline the end-to-end OPC UA IM modeling process. Each agent is equipped with meticulously engineered prompt templates, augmenting their capacity to execute specific tasks. We conduct modeling experiments using real textual data to demonstrate the effectiveness of the proposed method, improving modeling efficiency and reducing the labor workload.

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Publication Details

Journal
IEEE/CAA Journal of Automatica Sinica
Published
2025-04-15
DOI
https://doi.org/10.1109/jas.2025.125114
Citations
2
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
4.96
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article

Text2UA: Automatic OPC UA Information Modeling from Textual Data With Large Language Model

Rongkai Wang, Shibo He, Chaojie Gu, Jiming Chen
2 citations
IEEE/CAA Journal of Automatica Sinica
Semantic Web and Ontologies
4.96
article

Text2UA: Automatic OPC UA Information Modeling from Textual Data With Large Language Model

Rongkai Wang, Shibo He, Chaojie Gu, Jiming Chen
article en
2 citations

Abstract

Dear Editor, This letter deals with automatically constructing an OPC UA information model (IM) aimed at enhancing data interoperability among heterogeneous system components within manufacturing automation systems. Empowered by the large language model (LLM), we propose a novel multi-agent collaborative framework to streamline the end-to-end OPC UA IM modeling process. Each agent is equipped with meticulously engineered prompt templates, augmenting their capacity to execute specific tasks. We conduct modeling experiments using real textual data to demonstrate the effectiveness of the proposed method, improving modeling efficiency and reducing the labor workload.

IEEE/CAA Journal of Automatica SinicaVol. 12(10)
State Key Laboratory of Industrial Control Technology (CN), Zhejiang University of Technology (CN)
Quality Education
Openalex Percentile: Top 6%
Semantic Web and Ontologies
4.96
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