Optimized maintenance cycles and resource planning

Predictive Maintenance Software mit KI

No more inefficient maintenance cycles and expensive repairs: Our predictive maintenance software detects early on when your machines are behaving differently — and prevents failures before they occur.

Real-time insights into machine states: AI condition analyses and automated notifications

Optimization of maintenance cycles, prevention of failures & reduction of maintenance costs

Ready for immediate use & scalable: Without additional hardware & expensive IT investments

Download Use Case Portfolio

Start quick product tour

Zugriff auf Live Daten per Maschinenüberwachung

Cost savings

Maximize machine availability & reduce maintenance costs

Staff relief

Real-time insights into your machines without maintenance personnel

Easy integration

Seamless integration with
existing IT systems

Scalability

Algorithm expandable on other machines

More efficient maintenance, higher machine availability

When machines stop unplanned, entire production chains start to falter — including delivery delays, stress and expensive repairs.

Our predictive maintenance software detects critical deviations early on — and shows them in real time on an intuitive dashboard. This allows you to plan maintenance measures proactively, save resources and prevent downtimes before they happen.

Features of our predictive maintenance software

Visualization of historical and real-time sensor data

With our dashboard, you can keep track of important machine KPIs such as vibration, temperature or speed.

Context-dependent precise machine monitoring

When monitoring, our software takes actual operating conditions, such as product recipes, into account.

AI-powered fault detection & forecasting

Our AI detects relevant discrepancies and potential errors before problems arise.

Individually configurable alerts

You receive automated email alerts in real time as soon as there are critical machine deviations.

"Thanks to the early warning from aiomatic, we were able to detect a gearbox failure in time. As a result, we were able to maintain operations over the weekend with reduced output and prepare for the necessary repair, instead of being surprised by a sudden imminent failure."

Ben Thurnwald

Managing Director at Hansaport