Development of Edge AI Solution for Real-Time Quality Control in Electronics Manufacturing

As a startup in the Hardware & Electronics industry, we recognize the critical need for efficient and accurate quality control mechanisms in manufacturing. Our project aims to build an Edge AI solution that integrates with existing production lines to provide real-time defect detection using computer vision. By deploying machine learning models at the edge, this system will minimize latency issues, allowing for immediate feedback and corrective actions. We plan to utilize state-of-the-art technologies such as YOLO for object detection, TensorFlow and PyTorch for model development, and deploy models using hardware accelerators for optimized performance. This project will focus on developing a robust pipeline for image acquisition, preprocessing, model inference, and result visualization. The successful implementation of this solution will lead to significant reductions in production costs and improvements in product quality, providing a competitive advantage in the electronics market. We anticipate a 4-6 week development timeline with high urgency due to the pressing need for enhanced quality measures.