Endpoint Detection Using Principle Component Analysis and Local Outlier Factor in the Double Layer Plasma Etching

Abstract

.In plasma etch process, the optical emission spectroscope (OES) is widely used to detect plasma etch endpoint. The OES gathers the intensity of the wavelength from the radicals in the plasma chamber. In addition, the OES is very sensitive to the external elements or a particles, which means that there are diverse noise in OES data. Therefore, it is necessary to choose meaningful data, reduce noise, and reduce the quantity of data. In this paper, a new method to detect endpoint of double layer plasma etching is proposed. This algorithm uses data from OES and utilizing principle component analysis (PCA) and local outlier factor (LOF).