Optimization of Performance Model of Ethyl Acetate Saponification Using Multiple Regression Analysis

The purpose of the current study is to optimize the batch reactor performance model using multiple regression analysis for saponification of ethyl acetate by sodium hydroxide. Reaction temperature, reactor volume, agitation rate and reactants initial concentration were the main parameters examined including their interaction effect. Selected process response was the reaction conversion with respect of NaOH. Regression analysis was used to screen out the insignificant factors and the reaction temperature and volume were found to have insignificant effect on the response at the 5% selected significance level (alpha = 0.05). As a result of multiple regression analysis, agitation rate and reactants concentration were found to be significant operating parameters. The dependence of reaction conversion (response) on agitation rate and concentration was explained by a second order polynomial model and it was concluded that regression model with second order polynomial was good enough to fit the experimental data. The maximum conversion (99.5%) was obtained under optimum operating conditions of agitation rate (70 rpm) and reactants concentration (0.05 M) as evident from surface contours.