Kernel Principal Component Chart for Defect Detection
We present a multivariate statistical process control chart using kernel principal component analysis. The proposed control chart is robust to outliers, and its control limits are derived from the eigenanalysis of the Gaussian kernel matrix in the Hilbert feature space. Our experimental results show that the much improved performance of the proposed control in comparison with existing monitoring and controlling charts.