Applied Materials, Inc.

Other

Lalitha S Balasubramhanya

Moshe Sarfaty

Dimitris Lymberopoulos

Jed Davidow

A method and apparatus for monitoring a process by employing principal component analysis are provided. Correlated attributes are measured for the process to be monitored (the production process). Principal component analysis then is performed on the measured correlated attributes so as to generate at least one production principal component; and the at least one production principal component is compared to a principal component associated with a calibration process (a calibration principal component). The calibration principal component is obtained by measuring correlated attributes of a calibration process, and by performing principal component analysis on the measured correlated attributes so as to generate at least one principal component. A principal component having a feature indicative of at least one of a desired process state, process event and chamber state then is identified and is designated as the calibration principal component.

Method and apparatus for monitoring a process by employing principal component analysis

A process for controlling a substrate processing operation such as a plasma etch operation. One embodiment of the method of the present invention forms a plasma within a substrate processing chamber to etch a wafer disposed within the chamber. The plasma emission is used by the process as a broadband light source. During the plasma etch process, a plurality of wavelengths of radiation reflected from the surface of the wafer being etched are measured with a spectrometer. These measurements are then compared using pattern recognition techniques to previous measurements taken during a previous plasma etch operation. Certain embodiments of the invention use principal component analysis (PCA) techniques to perform pattern recognition while other embodiment use programmed neural net pattern recognition techniques.

Film thickness control using spectral interferometry

A method and apparatus for monitoring a process by employing principal component analysis are provided. Correlated attributes are measured for the process to be monitored (the production process). Principal component analysis then is performed on the measured correlated attributes so as to generate at least one production principal component; and the at least one production principal component is compared to a principal component associated with a calibration process (a calibration principal component). The calibration principal component is obtained by measuring correlated attributes of a calibration process, and by performing principal component analysis on the measured correlated attributes so as to generate at least one principal component. A principal component having a feature indicative of at least one of a desired process state, process event and chamber state then is identified and is designated as the calibration principal component. Preferably the at least one production principal component is compared to the calibration principal component by computing the inner product of the calibration and production principal components.

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Sunnyvale, CA, United States of America

Lalitha S Balasubramhanya