Ontology-Based CAD Analysis with LLMs: Natural Language Querying of Boundary Representations

abstract

CAD models using a boundary representation (BREP) are widely used across industrial applications. However, extracting and interpreting information from these models typically requires expert knowledge. In this paper, we present a GraphRAG-based system that lowers this barrier by enabling natural language access to detailed geometric and topological information. The approach builds upon an ontological representation of geometries, which is accessible via the semantic query language SPARQL. Large language models are used to translate user questions into formal queries and generate natural language replies, allowing for flexible, domain-aware interaction with the geometric data. The effectiveness of the system is demonstrated through a systematic evaluation using diverse CAD models and a range of natural language queries. Our system empowers domain experts to explore and analyze complex CAD models without requiring expertise in query languages or ontology design. By reducing the complexity of geometric information retrieval, the GraphRAG-based system enables more accessible, automated, and intelligent use of CAD data in industrial applications.