A new ex-situ model to diagnose a plasma processing equipment was presented. The model was constructed by combining wavelet, scanning electron microscope, ex-situ measurement of etching profile, and neural network. The diagnosis technique was applied ...
A new ex-situ model to diagnose a plasma processing equipment was presented. The model was constructed by combining wavelet, scanning electron microscope, ex-situ measurement of etching profile, and neural network. The diagnosis technique was applied to a tungsten etching process, conducted in a SF? helicon plasma. The wavelet was used to characterize detailed variations of plasma-etched surface, The diagnosis model was constructed with the vertical wavelet component. For comparison, a conventional model was built by using the estimated profile data. Compared to the conventional model, the wavelet-based model, demonstrated a much improved diagnosis.