Predictive maintenance for hydraulic presses

Four hydraulic presses failed unexpectedly about twice a quarter on average — and every stoppage cost several thousand euros. There was no condition monitoring.

RALUS retrofitted the presses with vibration, pressure and temperature sensors. An anomaly model learned the normal operating profile and reports deviations early to the maintenance manager via a Teams alert.

In the first year: 67% fewer unplanned breakdowns and 29% lower maintenance costs thanks to condition-based rather than calendar-based maintenance.