Advanced CMP Process Control by Using Machine Learning Image Analysis

Chemical-mechanical polishing closed loop control optimized process with machine learning assisted wafer image analysis algorithm implemented on the inter layer dielectric of 3D NAND ON stacking with poly-silicon stop layer is studied. The grayscale wafer image can be responded for film residue, stop layer damage, wafer edge damage, and thickness variation. Polishing five zones control model is trainned with wafer grayscale value by Python NN model with two hidden layers. The best condition of closed loop feedback control is deduced by machine learning assisted wafer image analysis algorithm.