Case Study
Ai Architect: Cohu
The AI Architect Quality Control Solution was developed by inmind.ai for Cohu to enhance microchip inspection.
Cohu is a global leader in precision quality control equipment, essential for microchip production in industries such as automotive, electronics, and telecommunications. The COVID-19 pandemic caused supply chain disruptions, leading to a global chip shortage. To optimize yields and reduce waste, manufacturers required more accurate and efficient quality control processes.
Microchip production demands high accuracy, but traditional inspection methods struggled to differentiate surface scratches from true defects. This led to false negatives, where functional chips were mistakenly discarded. Cohu needed an AI-powered solution to enhance inspection accuracy, ensuring that only defective units were rejected while maintaining high production efficiency.
Inmind.ai integrated an AI-driven quality control system into Cohu’s existing hardware. The solution leverages computer vision and deep learning to analyze microchip surfaces, distinguishing between minor imperfections and critical defects. By using a human-in-the-loop validation process, the AI model continuously learns and improves, refining its accuracy over time and adapting to new defect patterns.
The implementation of AI-powered inspection has significantly reduced false rejections, minimizing material waste and improving manufacturing efficiency. Cohu’s production line now benefits from higher accuracy, fewer discarded functional units, and improved cost savings. The AI-driven approach has helped streamline microchip quality control, ensuring greater reliability in global supply chains.