1. An automated method for a repeatable process, comprising: measuring raw time series data during the repeatable process using a set of sensors, wherein the raw time series data describes multiple parameters of the repeatable process; receiving, via a first controller, the raw time series data from the set of sensors; stochastically generating candidate features from the raw time series data using the first controller, wherein the candidate features are predictive of a quality of a work piece manufactured via the repeatable process; determining, via an evolutionary programming module, which of the generated candidate features are most predictive of the quality of the work piece; and executing a control action with respect to the repeatable process via a second controller using the most predictive candidate features, including determining the quality of the work piece by applying a rule to the most predictive candidate features and modifying at least one of the work piece and a parameter of the repeatable process based on the determined quality.