Radial Basis Function Network for Endpoint Detection in Plasma Etch Process

Abstract

In the semiconductor manufacturing process, the endpoint of plasma etch process can be determined by the graphics based detection in order to avoid the loss of over-etching and under-etching. Our approach in current study can be conducted as one way to real-time monitor and judge the endpoint instead of observing it manually. When the endpoint occurs, this system can improve the etch processes and provide instant shutdown recommendations. This method makes use of Radial Basis Function (RBF) network’s functional approximation in time-series modeling and in pattern classification. By training with enough samples, the judge will be more accurate. All the samples are probed with optical emission spectroscopy (OES) sensor in real plasma etch process and for both network training and test.