Díaz-Quezada, SWilson, DIPérez-Correa, JR2026-02-122026-02-122024-10-28Computers and Chemical Engineering, ISSN: 0098-1354 (Print), Elsevier BV, 192, 108910-108910. doi: 10.1016/j.compchemeng.2024.1089100098-1354http://hdl.handle.net/10292/20634This study addresses water scarcity in Chilean distilleries by developing a model-based engineering workflow. Prolonged droughts, likely driven by global warming, have intensified this problem. The primary challenge is maintaining high-quality spirits while reducing cooling water and energy use during batch distillation in packed columns. This process was modeled using mass and energy balances, resulting in a system of partial differential algebraic equations (PDAE). Our workflow includes mechanistic modeling, disturbance modeling, multiobjective optimization, model predictive control, and Monte Carlo simulations. Our findings show that cooling water consumption can be reduced by up to 35 % and energy consumption by up to 14.4 % while maintaining product quality. The proposed system is robust against operational disturbances and model mismatch, ensuring consistent distillate quality. This research demonstrates the integration of model-based optimization and control strategies in batch distillation processes, which can be replicated in other fruit wine distillation processes for improved sustainability.This is the Preprint version of an article published in Computers and Chemical Engineering © 2024 Elsevier Ltd. The Version of Record can be accessed via subscription at DOI: 10.1016/j.compchemeng.2024.10891040 Engineering4010 Engineering Practice and Education7 Affordable and Clean Energy0904 Chemical Engineering0913 Mechanical EngineeringChemical Engineering4004 Chemical engineeringFruit wineBatch distillationMultiobjective optimizationPartial differential algebraic equation systemsWater consumptionJournal ArticleOpenAccess10.1016/j.compchemeng.2024.108910