Improved process monitoring with Independent Components

We propose a method for process monitoring of a semiconductor manufacturing process. Independent Component Analysis (ICA) is applied to characterize E-test parameter data. We calculate angular confidence intervals for the model, eliminate marginally significant components, and implement control charts for significant components of interest. Alarms are generated off of deviations in the charted components. Alarms are easily used in process diagnosis based on the interpretation of the independent components.