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 preliminary design documents, identifies parts and materials, and assembles a draft bill of materials before formal release.
Business impact
This gives procurement and supply chain teams earlier visibility into likely material and component needs, supporting earlier supplier engagement.
Limitations
Early-design BOMs are inherently incomplete and can change significantly. They are useful for planning, but not for binding procurement commitments.
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 (launched January 2026) automatically groups and rationalises parts in a design BOM, identifying duplicates and suggesting substitutions from a preferred parts list (PTC press release, Jan 2026) — .