The challenge
On a crusher, the wear of the transmission belt settled in quietly, completely escaping the usual maintenance rounds.. Although the machine was still spinning, a loss of grip caused imperceptible micro-slips and dissipated energy in the form of heat, generating a snowball effect that inevitably led to the equipment breaking down completely..

The approach
The RED solution continuously analyzed the electrical power signals from the engine. By transforming these raw signals into a frequency spectrum, the algorithms were able to automatically track the amplitude evolution related to the frequency of the belt’s passage, tracking the mechanical drift over several months before triggering an alert..

The result
The planned maintenance intervention allowed the timing of the replacement of the belt to be ideal, which immediately restored the transmission performance and stopped accelerated wear.. This strategic foresight avoided an emergency shutdown costing €10,000 per hour, offering a net financial impact estimated at €9,000 per incident.

👉 Download the complete Use Case to discover the behind-the-scenes details of this analysis and see how electrical data enables the anticipation of belt problems.