A framework for model-based optimization of bioprocesses under uncertainty: Lignocellulosic ethanol production case

► We introduce a framework for bioprocess optimization under uncertainties & apply it for bioethanol case. ► We first screen and identify the critical sources of uncertainties using global sensitivity analysis. ► We quantify their impact on process performance via uncertainty analysis. ► We then use stochastic programming to drive the process development forward under uncertainties. ► The four process configurations studied, revealed significant room for further production cost reduction.