Reliability of operating window identified from process data

This paper discusses data-based operating windows as a tool for process management and development. In particular identification of the operating window and its uncertainty are analyzed. The operating window is determined by maximizing either the mutual information (static) or entropy transfer (dynamic). An industrial example shows that the entropy of the indicator variable is reduced to half by an operating window specified with only few variables, selected amongst over 3000 candidates. Test model based simulations suggest that such few-variable operating windows can be reliably identified from datasets having lengths of a few thousand observations.