SP Technologies successfully developed and deployed a cutting-edge Computer Vision system for automated quality control in medical device manufacturing. This 5-month project for a prominent Swiss medical device company focused on enhancing product quality, reducing defects, and improving overall production efficiency.
Key achievements:
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Computer Vision: We designed and implemented a state-of-the-art visual inspection system using deep learning models to detect microscopic defects in medical devices during the manufacturing process.
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Data Processing: Our team developed a robust data pipeline to handle high-resolution image processing in real-time, ensuring seamless integration with the production line.
The system utilized PyTorch for deep learning models and OpenCV for image processing. It was capable of identifying defects with 99.7% accuracy, significantly outperforming manual inspection methods.
This implementation resulted in a 40% reduction in defective products reaching final quality control, a 25% increase in overall production speed, and a 15% decrease in quality control-related costs. The success of this project not only improved the client’s manufacturing processes but also set a new industry standard for quality control in medical device production.