Abstract: The subject disclosure relates to automatically learning relationships among a plurality of manufacturing tool parameters as applied to arbitrary semiconductor manufacturing tools and a graphical user interface that is supported, at least in part, by an autonomous learning system. The graphical user interface can create one or more matrixes based on received data and can further generate additional matrices by transforming the one or more matrixes. A series of windows can be output, wherein the series of windows, provide performance analysis that comprises a matching between a focus chamber and a reference chamber. In an aspect, the focus chamber and the reference chamber can be different chambers. In another aspect, the focus chamber and the reference chamber can be the same chamber, which provides analysis of the deterioration in performance of the same chamber over time.

Abstract: The subject disclosure relates to automatically learning relationships among a plurality of manufacturing tool parameters as applied to arbitrary semiconductor manufacturing tools and a graphical user interface that is supported, at least in part, by an autonomous learning system. The graphical user interface can create one or more matrixes based on received data and can further generate additional matrices by transforming the one or more matrixes. A series of windows can be output, wherein the series of windows, provide performance analysis that comprises a matching between a focus chamber and a reference chamber. In an aspect, the focus chamber and the reference chamber can be different chambers. In another aspect, the focus chamber and the reference chamber can be the same chamber, which provides analysis of the deterioration in performance of the same chamber over time.

Abstract: The subject disclosure relates to automatically learning relationships among a plurality of manufacturing tool parameters as applied to arbitrary semiconductor manufacturing tools and a graphical user interface that is supported, at least in part, by an autonomous learning system. The graphical user interface can create one or more matrixes based on received data and can further generate additional matrices by transforming the one or more matrixes. A series of windows can be output, wherein the series of windows, provide performance analysis that comprises a matching between a focus chamber and a reference chamber. In an aspect, the focus chamber and the reference chamber can be different chambers. In another aspect, the focus chamber and the reference chamber can be the same chamber, which provides analysis of the deterioration in performance of the same chamber over time.