(150a) Design of Dynamic Experiments

In this tutorial presentation we describe the first generalization of the Design of Experiments (DoE) methodology, the Design of Dynamic Experiments (DoDE). Its main and powerful characteristic is that it allows the experimental factors to be functions of time instead of constant values. This enables us to consider, for example, time variations in the reaction temperature or time variations in the feeding of a co-reactant. The power of this new methodology is that is offers a unique data-driven avenue for the optimization of processes for which a detailed knowledge-driven model is not at hand. The presentation will include several examples of batch processes including a Dow polymerization reactor and a pharmaceutical hydrogenation reaction. The productive of the Dow process was increased by 19%, shortening the batch time while producing the same amount of product with the desired quality. The selective and economics of the pharmaceutical hydrogenation was increased by 40% by operating the reactor with a decreasing temperature profile.