Predictive Maintenance: 42% Unplanned Downtime Reduction, 180 Assets Monitored

The Challenge

An automotive component manufacturer with 180 critical production assets needed predictive maintenance to reduce unplanned downtime that was costing €4.2M annually in lost production and emergency repairs across 3 European plants.

The Solution

NINtec deployed vibration, temperature, and acoustic sensors across 180 assets, feeding ML models that predict failure 72 hours in advance with 91% accuracy. Maintenance scheduling optimization reduced spare parts inventory by 25% while improving overall asset availability.

Results

Technology Stack