Abstract: A method and system for use in monitoring/evaluating industrial processes such as, for example, plasma processes are provided. In one embodiment, a plasma process fault detection module (100) includes multiple sub-modules. A data selection sub-module (101) obtains selected optical emissions spectra (OES) data for each wafer that is processed. A model building/updating sub-module (102) constructs multiple models from the OES data for a number of wafers. A principal component analysis (PCA) analysis sub-module (103) utilizes PCA techniques to determine whether the OES data for a particular wafer differs significantly from an expected normal wafer as represented by the models. A model maintenance sub-module (104) saves and retrieves models for different processes, associating the current wafer with the correct process. A wafer categorization sub-module (105) categorizes each wafer based on a scalar metric characterizing the residual spectrum vector. A data output sub-module (106) outputs the results to a user.

Abstract: The present invention relates to a method and assembly for leak detection in a plasma system. The invention can accomplish not only leak detection, but also leak location while maintaining a plasma within the plasma system. Leak detection for the invention is achieved by obtaining spectral data of the plasma at one or more times while maintaining the plasma within the plasma system and comparing the same to predetermined spectral data of air. Upon a determination that air is present within the plasma system, one or more external surfaces of the plasma system are exposed to a test gas and the spectral data of the plasma is analyzed after each exposure to determine if the test gas is present in the system. If the test gas is present, a determination can be made that the particular external surface to which the test gas was applied is a leak location.