Fraunhofer-Gesellschaft
In feasibility studies with selected companies in industrial manufacturing, it has already been proven by Fraunhofer IDMT that AI-based methods can be profitably used for acoustic quality control. Based on the results obtained, the IDMT-ISAAC software is now being developed, which wants to provide quality assurance specialists with a tool that reliably supports them in testing processes - even without having any knowledge of AI themselves. Users can train their own AI models with IDMT-ISAAC and thus traceably improve and automate their quality assurance.
The software IDMT-ISAAC can be used for testing tasks where more accurate results and a faster testing time should be achieved. Also limits in existing quality assurance can be overcome with AI.
For such cases, Fraunhofer IDMT offers a demonstration version of the software and invites industrial partners to make contact for the application-oriented further development of the software IDMT-ISAAC.
Acoustic quality control can be used, among other things, to detect material defects or in the inline monitoring of manufacturing processes, such as welding, without any contact to the workpiece or the machine. The process is also non-destructive, thus reducing the amount of expensive test scrap. If errors are detected acoustically during the process, the process can be aborted, adjusted, and restarted in a timely manner. This contributes to resource efficiency and production optimization.
Fraunhofer IDMT extends the offer of Fraunhofer’s business unit Vision with AI-based acoustic monitoring and thus wants to contribute to supplementing optical inspection processes and optimizing industrial QA processes. In the BMBF-funded innovation forum »Acoustic Monitoring of Manufacturing Processes«, everything revolves around the topic of quality assurance with AI. The focus lies on acoustic approaches, but also users from the field of optical testing are invited to contribute their experiences with AI-based imaging technologies and to benefit from the latest findings in the field of acoustic signal analysis with AI.