Recognise early instead of unplanned downtime: Unplanned downtimes do not fit into any production routine. That's why we rely on the following in maintenance Predictive maintenance with Siemens Senseye.

The approach behind this is clear: we don't just react when a system comes to a standstill. Instead, we recognise anomalies at an early stage and can plan measures when they fit into the production process. This creates more safety in maintenance and helps to avoid interruptions in a targeted manner.

What predictive maintenance means in practice

In traditional maintenance, action is often taken when a fault has already occurred or a maintenance interval has been reached. Predictive maintenance extends this approach. System status data is continuously analysed so that deviations become visible at an early stage.

The video shows an example of possible bearing damage. The anomaly is recognised in good time before an unplanned failure occurs. This means that the measure can be scheduled and implemented in a suitable maintenance window.

This is precisely where the decisive advantage lies: maintenance is not just reactive or rigidly interval-based, but forward-looking.

More reliability in day-to-day production

For us, predictive maintenance is not an end in itself. The decisive factor is the benefit in everyday life.

If abnormalities are recognised at an early stage, they can be:

• Reduce unplanned downtimes
• Better planning of maintenance work
• Use resources in a more targeted manner
• Keep processes more stable

This strengthens reliability in production. And this reliability also has an effect where it is important for our customers: in quality and delivery service.

Digital support for maintenance

With Siemens Senseye we supplement our maintenance with a data-based view of the system status. This does not replace the technical expertise in operation, but complements it in a meaningful way.

Experience, process understanding and digital support intertwine. This allows us to categorise developments earlier and act in a more targeted manner.

A further step in the further development of our processes

At SAGER, we are constantly developing our processes further. Predictive maintenance is an example of how digital solutions can bring concrete benefits in the production environment.

It is not about simply collecting data. The key is to draw the right conclusions from this data and derive measures that create added value in everyday life.

Conclusion

With predictive maintenance, we are specifically strengthening our maintenance where it counts in day-to-day production: with predictability, reliability and early action.

In this way, we create an additional basis for stable processes, which ultimately also benefits our customers.

Would you like to gain more insights into our production and processes? Then follow us on LinkedIn or come for a Factory tour over.