Condition monitoring and quality forecasting

Does your production process (still) run smoothly? Or do you (already) have to intervene manually? These questions have become part of daily life for people supervising modern production processes. To answer these questions, current information is required, which is typically collected by sensors directly in the process.

The Department of Machine Vision and Signal Processing implements systems for monitoring production processes with applications in condition monitoring and quality forecasting. The use of these systems makes it possible to detect errors in complex situations at an early stage, as well as to set optimal operating points efficiently.

In practice, the reasons for complexity are manifold: Often, the time required to assess the quality of a component is longer than the actual cycle time, making it difficult to detect errors quickly. In addition, if components can only be inspected using a destructive method, they must be assessed on the basis of random sampling. In order to take full advantage of the available sensor data in such cases, digital signal analysis and machine learning techniques are deployed.

The application spectrum of the monitoring systems is broad, ranging from cyclical productions in plastic injection molding and ultrasonic welding operations to continuous processes in process engineering.

Our experts can also provide support, for example, by selecting and integrating sensors in production as well as in efficiently finding a suitable operating point during commissioning.