A Monte Carlo-based error propagation analysis of Simulated Moving Bed systems

A Monte Carlo-based uncertainty analysis for the performance assessment of a Simulated Moving Bed (SMB) system, which is widely employed in the petrochemical, sugar, and pharmaceutical industries, is presented. The error propagation analysis is carried out to predict the performance of the SMB system for two different binary separations: (a) glucose–fructose separation in a pilot-scale SMB unit and (b) separation of p-xylene from xylene isomers in an industrial-scale SMB unit. Existing SMB models in literature, which utilize a linear isotherm for the glucose–fructose separation [D.C.S. Azevedo, A.E. Rodrigues, Fructose–glucose separation in a SMB pilot unit: modelling, simulation, design and operation, AIChE J. 47 (2001) 2042–2051] and a nonlinear isotherm for the separation of xylene isomers [M. Minceva, A.E. Rodrigues, Modeling and simulation of a simulated moving bed for the separation of p-xylene, Ind. Eng. Chem. Res. 41 (2002) 3454–3461], are employed for the analysis. While the purity and productivity of glucose and fructose are chosen as the performance (or output) variables in the former case study, the purity and recovery of p-xylene are chosen as those in the latter. In both cases, the isotherm parameters, often obtained from chromatography experiments with appreciable levels of uncertainty, are chosen as the process (or input) variables. From the sensitivity analysis, simple models are developed to predict the variations in the performance of the SMB as a function of the isotherm parameters.