Real‐Time Interactive Navigation on Input‐Output Data Sets in Chemical Processes

Input-output data sets are ubiquitous in chemical process engineering. We introduce a real-time interactive navigation framework that provides several capabilities to the decision maker (DM). Once a surrogate model is trained the DM can perform what-if analyses in both input and output spaces by manipulating sliders. An approximated convex hull spanned in the input space supports both a reliable surrogate prediction and a navigation close to the data set. The framework has been tested on data sets obtained with a flowsheet simulator modeling a real steam methane reforming process.