Plasma Diagnosis by Using Scanning Electron Microscope and Neural Network

신경망과 주사전자현미경을 이용한 플라즈마 진단

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 $SF_6$ 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.