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.
Authors
- Rongkai Wang (ORCID: https://orcid.org/0000-0001-6719-2703)
- Shibo He (ORCID: https://orcid.org/0000-0002-1505-6766)
- Chaojie Gu (ORCID: https://orcid.org/0000-0003-2153-811X)
- Jiming Chen (ORCID: https://orcid.org/0000-0003-4984-3490)
Institutions
- State Key Laboratory of Industrial Control Technology (CN)
- Zhejiang University of Technology (CN)
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