The system reduces manual BOM (Bill of Material) preparation work by extracting parts and quantities from documents and aligning them with enterprise systems used for procurement and production.
How it works
The system reads drawings, PDFs, and spreadsheets, extracts parts and quantities, standardizes inconsistent naming, and connects the results to enterprise records so BOM preparation requires far less manual work.
Application here
AI reads a CAD assembly, extracts the part hierarchy, and generates a structured engineering BOM linked to PLM.
Business impact
This removes hours of manual BOM work and helps reduce errors before they spread into procurement and production planning.
Limitations
Results depend on CAD model quality and naming consistency. The system cannot infer design intent beyond what is visible in the CAD structure.
In production
This is already used to cut manual BOM preparation effort where teams currently piece together parts data from multiple disconnected documents.
Research
The frontier is moving toward systems that not only read BOM data, but understand component relationships, detect inconsistencies, and connect the result more directly to sourcing and planning work.
Examples
PTC Windchill AI Parts Rationalization (January 2026) automatically extracts eBOM from CAD models and rationalises the structure, identifying duplicate and similar parts (PTC press release, Jan 2026). Autodesk Fusion also offers auto-BOM extraction from 3D models — .