Skip to content

Track record · Wind-turbine construction

E-BOM vs. M-BOM: an end to costly assembly errors

At a wind-turbine manufacturer (over 3,500 employees, more than 4 billion euros in revenue, 730 new installations in one year) engineering and manufacturing BOMs between Siemens Teamcenter and SAP S/4HANA regularly diverged. AI-supported matching surfaces the differences before assembly starts.

The challenge

The problem

Missing or wrong parts due to inconsistent E-BOM to M-BOM transitions: manual checking was time-consuming and error-prone, the systems barely comparable.

The consequences: expensive re-procurement on site, delayed commissioning and operating problems.

Document AI

The solution

How it was solved

BOM comparison algorithm Automatic matching of the E-BOM (PLM) against the M-BOM (ERP).
PLM/ERP bridge Siemens Teamcenter and SAP S/4HANA are made comparable.
AI-supported validation Historical BOMs provide the pattern for plausible structures.

The results

> 2 Mio. € saved per year through avoided assembly errors
730 new installations per year covered by the process

Technology

Methods used

Stack

  • SAP S/4HANA
  • Siemens Teamcenter
  • Machine Learning
  • Structural matching

Additionally: better traceability of BOM history and less delay in commissioning.

Led by Beyonetix founders and senior engineers. Figures per the respective project report.

A comparable problem in your operation?

We bring this experience to your project. Let's talk.