Meet us at the Fraunhofer "Smart Maintenance Community" booth
Let us show you the solution to your QA problem with our technology: AI-based acoustic monitoring in production – contact-free, non-destructive and robust. The system works in near real time, even in harsh environments, and detects and classifies conditions based on sound.
The production of fuel cell stacks is currently a major challenge for manufacturers. The cost of manufacturing the components and assembling the stacks is high, and there is still no stable production process, let alone reliable quality assurance. In order to meet the growing demand for fuel cells and to make the large-scale production of stacks more efficient, it is necessary to further develop and automate the production processes. This is where automated acoustic monitoring comes in.
What has already been proven in welding processes such as MIG and MAG is now to be applied to quality assurance in fuel cell production: During production, microphones continuously record process sounds. AI algorithms analyze this audio data in near real time, and the system immediately reports deviations in the process. Potential problems such as material defects, tool wear, or assembly errors can be detected and corrected early on. Where conventional inspection methods reach their limits, the additional use of space-saving and cost-effective acoustic sensors provides a complementary measurement option that can be reliably evaluated using AI.
Fraunhofer IDMT: Where AI means Audio Intelligence
Fraunhofer Institute for Digital Media Technology IDMT