Table of Contents
Processes, Volume 6, Issue 10 (October 2018)
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Cover Story (view full-size image) Model-based design tools have been widely applied to improve the performance of (bio)chemical and [...] Read more. Model-based design tools have been widely applied to improve the performance of (bio)chemical and pharmaceutical processes. However, the reliability of these designs is subject to model uncertainties, i.e., epistemic deficiencies or intrinsic randomness. Neglecting model uncertainties might lead to suboptimal process designs or even malfunctions. In this work, we propose a comprehensive and efficient robust process design approach including (1) parameter uncertainties and correlations, (2) parameter sensitivity analysis, and (3) and the formulation of robust inequality and equality constraints. In simulation studies, we demonstrate the robustification strategy successfully on the design of (bio)chemical and pharmaceutical processes. View this paper.