This project aims at developing an in line, learning based quality control for laminate welding. The mechanical analysis relies upon the compression ratio before and after the welding operation. The aesthetic analysis relies upon an anomaly detection module based on computer vision techniques & active learning. This new in line weld quality control, with an intuitive setup and calibration will reduce the number of customer complaints and defective production batches.