Patent ID: 8223329

Claim:
An endpoint detection method comprising: processing, by an optical emission spectrometer (OES) data operation unit, reference OES data by normalization and principal component analysis (PCA) and generating linear reference loading vectors, rate values of reference principal components, and reference ranking values; making a support vector machine (SVM) learn on the basis of the linear reference loading vectors, the rate values of the reference principal components, the reference ranking values, and the reference OES data; selecting, by a data selector, part of process OES data on the basis of the reference ranking values; periodically generating a prediction product value using the learning SVM and the selected process OES data; and detecting, by an endpoint determiner, a process wafer etch or deposition endpoint on the basis of the prediction product value and outputting a detection signal, wherein the reference OES data are data obtained by converting, by a spectrometer, first lights of a whole wavelength emitted from the inside of a plasma reaction chamber during a reference wafer etch or deposition process, and the process OES data are data obtained by converting, by the spectrometer, second lights of a whole wavelength emitted from the inside of the plasma reaction chamber during a process wafer etch or deposition process executed after the reference wafer etch or deposition process, wherein the linear reference loading vectors each correspond to one-dimensional function values expressed by the reference OES data, and wherein the reference ranking values represent a ranking for the intensity of the first lights of the whole wavelength.