Other

Piotr Smolinski

David M Katz

Thomas A Hill

Steven Hillion

Siva Ramalingam

A process control tool for processing wide data from automated manufacturing operations. The tool including a feature selector, an analysis server, and a visualization engine. The feature selector receives process input data from at least one manufacturing process application, wherein the process input data includes a plurality of observations and associated variables, converts the received process input data to a stacked format having one row for each variable in each observation, converts identified categorical variables into numerical variables and identified time-series data into fixed numbers of intervals, computes statistics that measure the strengths of relationships between predictor values and an outcome variable, orders, filters, and pivots the predictor values. The analysis server performs at least one operation to identify interactions between predictor values, e.g. using maximum Likelihood computations or predefined searches, in the filtered predictor values. The visualization engine displays the interactions for use in managing the manufacturing operations.

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Munich, Germany

Piotr Smolinski