AI-Powered Condition Monitoring for Reliable Production

If equipment conditions are not continuously monitored, creeping damage such as wear, bearing problems, or overheating often goes unnoticed for a long time. At the same time, purely cyclical maintenance approaches, a lack of transparency regarding actual load conditions, and the high complexity of modern machines mean that warning signs are detected too late—or not at all.

The consequences are unplanned downtime, safety risks, and high costs for maintenance and repairs.

Condition monitoring refers to the continuous and automated monitoring of machine and plant conditions using sensors and AI-based data analysis. Analyzing the temporal trends in sensor data (e.g., current, vibration, acceleration) enables the early detection of relevant deviations. This makes it possible to:

• Optimize processes
• Prevent failures
• Plan maintenance strategically
• Reduce costs

Companies benefit from higher equipment availability, product quality, process reliability, and efficiency.

Sensors on wear-prone components enable the early detection of patterns and anomalies. With the help of AI-powered forecasts that take time trends and production schedules into account, wear can be predicted with precision.​

These predictions lay the foundation for needs-based and proactive maintenance. Unplanned machine downtime can be reduced, and existing resources can be utilized more efficiently.​

By combining wear predictions, historical quality data, and current process parameters, production processes can be continuously monitored and product quality reliably predicted. Based on this, AI-driven process parameter optimizations can be specifically applied to ensure the desired quality and avoid scrap.​

An exploratory data analysis as part of a proof of concept (PoC) provides initial valuable insights from your existing data. Fraunhofer IPA supports you in taking a holistic view of your specific use case. This involves selecting and integrating sensors, as well as analyzing and providing data within an integrated system for condition monitoring. The PoC starts at 14,400 euros, including exploratory data analysis.