Abstract
The waste solvent is frequently generated from the processes that highly rely on solvents. Diethylene glycol monomethyl ether or methyl di glycols (MDG) and N-methyl-2-pyrrolidone (NMP) are representative valuable solvents used broadly and removed as waste solvents during the semiconductor material manufacturing processes. Although waste solvent can be practically retrieved by distillation, azeotropic waste solvent mixture only can be recovered by advanced distillation process. In this study, optimal extractive distillation and extractive-dividing wall column are used to recover waste solvent. The process is optimized by multi-objective optimization using genetic algorithm by linking Aspen Plus® and MATLAB. All optimal cases are compared in terms of energy, exergy, economic and environmental parameter. As a result, the potential energy, total annual cost saving and exergy efficiency for extractive dividing wall column are 26.29%, 24.15% and 21.02%, respectively. Exergy loss that is associated with the number of trays can be significantly reduced by optimization while exergy loss that is associated with remixing only can be significantly reduced by dividing-wall column. Further, multi-objective optimization using a genetic algorithm and a range of population provides various results that determine process selection.
Published Version
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