Digital maintenance.


Avoid breakdowns and control maintenance intelligently with GNT

Your benefits with GNT Maintenance – predictive, transparent, efficient

Predictive maintenance with a system – more availability, less downtime

With GNT maintenance software, you can plan, document and monitor all maintenance measures in a structured and digital way – from preventive maintenance and condition-based concepts to predictive maintenance based on real-time MDA data. This allows you to increase machine availability, reduce downtime and create maximum transparency in the maintenance process.

Predictive maintenance with AI

Maintenance rethought – data-based, predictive, efficient.

Avoid downtimes, control maintenance cycles intelligently and deploy resources in a targeted manner: With the AI functionalities of the GNT complete solution, you can take your maintenance processes to a new level. The software recognizes typical patterns based on real machine and process data, evaluates fluctuations in real time and predicts impending failures – before they occur.

This means that maintenance measures can be planned at an early stage, unplanned interruptions can be prevented and maintenance intervals can be adjusted as required. Instead of rigid plans, you can act flexibly and with foresight – and thus increase the availability of your machines in the long term.

What our customers say about GNT Systems

Functional highlights of GNT maintenance

Frequently asked questions
on the subject of maintenance

What is predictive maintenance?

Predictive maintenance is a form of condition-based maintenance in which real-time machine data is evaluated in order to detect potential failures at an early stage and prevent them in a targeted manner. The aim is to reduce unplanned downtime, carry out maintenance as required and extend the service life of systems.

Yes, GNT Maintenance is closely linked to machine data acquisition (MDA). This integration makes it possible, for example, to automatically analyze faults, suggest reasons for faults or incorporate maintenance-relevant operating data (e.g. running time, number of cycles) directly into maintenance planning – for greater transparency, fewer breakdowns and targeted intervention.