Siemens Healthineers | Power Electronics Analysis in Machine Engineering
Challenges
Siemens Healthineers needed to better understand recurring power electronics failures. Data was fragmented across systems, making root cause analysis complex and limiting visibility into machine performance.
Approach
CBTW aggregated historical data from multiple machines into a unified analysis model. Machine learning algorithms were applied to identify failure patterns, supported by an interactive dashboard to visualize results and engage business stakeholders.
Benefits
The solution enabled a holistic view across systems and explained around two-thirds of historical failure patterns. It identified key issues with savings potential exceeding €100k, while increasing business trust through transparent, explainable insights.




















