We focus on enhancing P&ID interoperability using large language models to translate or generate XML files interoperable with different software. Our research addresses the challenge of inconsistent data structure and terminology across systems by developing a semantic matching algorithm to harmonize terms automatically. This solution enables seamless data exchange and improved usability across life cycle. 

We focus on semantic data enrichment of digital models by extracting and digitalizing information from legacy data. Our research matches and visualizes this data within 3D digital twins. This approach enables rich data integration, supporting advanced asset management and decision-making.