Application of statistical clustering to mathematical description and control of continuous processes with discrete event output

Abstract

Statistical clustering is used for the mathematical description of continuous manufacturing processes with discrete event outputs. The resultant mathematical model defines the correspondence between various outcomes of the process and particular regions in the space of process variables. An adaptive version of the clustering model intended for online implementation is presented. Prediction, regime selection, and control procedures, utilizing the clustering model, are formulated.<>