Implémentions De l`IA Dans Une Machine D`inspection Par Camera

Abstract

This final year project investigates the use of artificial intelligence (AI) to enhance the inspection process of printed circuit boards (PCBA) at Bomare Company. Utilizing a convolutional neural network (CNN), we developed an AI model capable of accurately distinguishing defective from non-defective PCBA. Trained on a large dataset of images, the model demonstrated excellent performance in terms of accuracy, recall, and AUC score. We also discussed in detail the integration of the model into the production process, highlighting the importance of collaboration among various teams, operator training, and continuous performance monitoring of the model. The potential of AI to improve efficiency, quality, and reduce production costs was underscored, making this technology a viable solution for PCBA inspection in the manufacturing industry.