Acoustic Monitoring for Production

Assuring quality, stabilizing processes, understanding artificial intelligence

AI-based acoustic monitoring (amo) can provide great added value in process monitoring, in-line and end-of-line quality control of products, and predictive maintenance applications. In production, problems regarding unexpected machine downtime, production of bad or destroyed products, and low automation rates can be solved using amo.

With amo, we want to optimize the user's production, and with this non-destructive and non-contact testing method, stabilize processes, avoid recourse, and reduce faulty production.

AI hears and classifies faults correctly

The successful application of this innovative test method has already been demonstrated in the in-line quality control of weld seams. Our scientists are currently conducting research on approaches for monitoring different manufacturing processes, including welding and machining. Expert knowledge on suitable sensor setups, sensor data fusion, processing of sensor data without connection to an external cloud, as well as energy-efficient AI models play a significant role in all their approaches.

With our research, we want to shape the production of the future, avoid errors, use resources efficiently and protect our environment.

The new acoustic monitoring is demonstrated on an air-hockey table. Three pucks are used, which are made of different materials and cause different "pling" sounds as soon as they hit the rail of the game table. During play, these acoustic signals occur frequently and irregularly and can be analyzed and classified using machine learning techniques.

We are looking forward to meeting you at our booth!