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Supply Chain & Procurement · Service
Generative AI / BOM Automation
Spare parts and service BOM alignment
Live Adjacent medium effect
Core capability
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 improves spare-part identification and keeps service BOMs more consistent with engineering and production systems.
Business impact
This reduces wrong-part shipments and helps speed up service turnaround by improving part matching.
Limitations
Results depend on master-data quality. Legacy products with weak documentation are harder to align, and ambiguous matches may still need manual review.
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
ASML: Method to Improve Service BOMs in Spare Parts Management
Description: ASML, a semiconductor‑equipment OEM, deployed a data‑driven method that detects mismatches between installed machine configurations and service BOMs by cross‑checking multiple machine data sources, then generates alerts for service‑BOM corrections; this has been run in production and reduced spare‑part non‑availabilities by about 4–5% per year.



Configuration Management to Improve the Service BOM for ASML
Description: ASML redesigned its service BOM structure to tie spare‑part entries directly to machine‑type and engineering data, using configuration‑management rules and automated checks so that each installed machine has a unique, up‑to‑date service BOM; the new approach has been implemented in production and cut operational costs by around 0.9 million euros annually.



AI‑BOM Builder in Australian Job‑Shop Manufacturing (ECi Solutions / JobBOSS²)
Description: Australian job‑shop manufacturers use an AI‑driven BOM builder inside an ERP to parse CAD files and engineering drawings, automatically recognize materials and parts, and map them into structured BOMs for procurement and production; the system runs in production and reduces manual BOM creation time and entry errors.
https://research.tue.nl/en/publications/on-a-method-to-improve-your-service-boms-within-spare-parts-manag/https://research.tue.nl/en/publications/configuration-management-improve-the-service-bom-for-asmlhttps://www.ecisolutions.com/en-au/blog/manufacturing/m1/the-power-of-ai-bom-builder/
Sources
PTC Servigistics — ; Syncron —
https://www.ptc.com/en/products/servigisticshttps://www.syncron.com/solutions/service-parts-planning/