LAUSR

Abstract Thermal stability of batch processes is a major factor for the safe and efficient production of polymers and pharmaceutical chemicals. The prediction of the thermal stability for such processes was shown in Kahm and Vassiliadis (2018d) to be unreliable with most stability criteria found in literature also presenting a novel criterion, K , which was shown to give reliable stability predictions for single reactions of higher order. This work provides a detailed derivation for the generalization of thermal stability criterion K applied to reaction networks of arbitrary complexity, consisting of parallel and competing reactions of both exothermic and endothermic nature. The generalized thermal stability criterion K is then applied to Model Predictive Control (MPC) frameworks to intensify batch processes in a safe manner, reducing the time required to reach the target conversion. Several illustrative computational case studies are presented, highlighting the proposed methodology and verifying its validity.