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 extracts the bill of materials from engineering documents and aligns it with supplier catalogs and the ERP system.
Business impact
This reduces manual data-entry errors and improves procurement readiness for pilot builds.
Limitations
Accuracy depends on document quality. Misaligned part numbers or outdated information can still create procurement mistakes in pilot builds.
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
Azure AI Document Intelligence is used by manufacturers to automatically extract BOMs from prototype PDF drawings and supplier catalogues, achieving ~90 % extraction accuracy on standardised formats (Microsoft documentation) — .