Detecting foreign objects plays a central role in quality assurance in Wacker’s material inspection. The goal was to make this inspection more efficient with a camera-based solution and AI.
Finding the Right Startup and Proving the Technology in a Pilot Project
We searched for suitable startups worldwide and selected ANTICIPATE for a pilot project. In the proof of concept, the startup implemented AI software for automated, camera-based quality control that detects errors in real time, faster and more accurately.
ANTICIPATE trained, optimized, and evaluated the AI model for detecting foreign objects. This demonstrated the technology’s effectiveness and its long-term potential.
An Error Detection Rate of at Least 95% and the Path to the Factories
The AI-powered solution raises the error detection rate to at least 95%. It has the potential to reduce dependence on operators for critical quality control tasks.
Following the successful proof of concept, the next step is implementation in the factories.
Key Results
95%
Error detection rate of at least 95% for foreign objects with the AI-powered solution.
