Optimal experimental design for process optimization with stochastic binary outcomes

Abstract

Effective control of the end-use properties in order to guarantee product quality is of paramount importance. This is especially valuable for products such as medicament, polymers and nanomaterials. There are plenty of innovative processes whose principles of operation are unknown and for which is not possible to develop reliable models due to time and cost. Despite this, it is important to know the optimum operating zone where the process should work to ensure that the end product meets the required properties. To address this issue, a run-to-run optimization approach is proposed to find the reduced region of operation which guarantees obtaining end-use properties with high probability when a first-principles model for the batch process is not available a priori. In order to evaluate the effectiveness of the methodology to find optimal policies for runs involving stochastic binary outcomes, the well-known example of the emulsion polymerization of styrene has been addressed. Results obtained demonstrated that the proposed method is a powerful tool for optimal design of experiments aiming to guarantee end-use product properties.