Bringing a predictive maintenance model into production.

The context

An energy company had developed a predictive maintenance model in a lab but was unable to deploy it reliably at scale.

Our approach

Complete MLOps infrastructure on Azure ML, automated training and deployment pipelines, model performance monitoring and integration with SCADA systems.

The results

• Model in production in 8 weeks
• 30% reduction in unplanned failures
• Significant maintenance savings
• Complete governance and traceability

Anonymized client case. Results reported on the Bennen Technologies website.