Built an intelligent quality control system that automatically detects defective screws on a production line using deep learning. The model learns what a "good" part looks like and flags any deviation, replacing slow, error-prone manual inspection with real-time, automated analysis. Achieved 99% accuracy with near-perfect precision and recall. Includes a clean web interface where users can upload an image and instantly get a defect classification with a confidence score.