1. A method for updating a data set defining a set of process runs, each process run having a set of data corresponding to a set of variables for a wafer processing operation, comprising: receiving a data set; performing scaling to the data set; performing principal component analysis to the scaled data set to generate a model; receiving new data; projecting the new data to the model; identifying outlier data points based on the projecting; examining a contribution plot corresponding to one of the outlier data points; identifying a variable that corresponds to the one outlier data point which provides a high contribution in the contribution plot; determining that the variable is unimportant; creating a desensitizing set of data for the variable based on a standard deviation of the data set and a randomization of the new data; and augmenting the data set with the desensitizing set of data.