Sensitivity Analysis of Reaction Kinetics in Saponification of Ethyl Acetate and Sodium Hydroxide in Continuous Stirred Tank Reactor (CSTR)

Continuous stirred-tank reactors (CSTRs) are integral to industrial chemical processes due to their uniform mixing and steady-state operation. The saponification of ethyl acetate with sodium hydroxide is a widely used model reaction for studying kinetics in CSTRs. Understanding the sensitivity of reaction kinetics to operating conditions is critical for enhancing reactor performance, ensuring consistent product quality, and minimizing inefficiencies. Reaction kinetics in a CSTR are influenced by reactant concentrations, temperature, and flow rate. Misidentifying or poorly optimizing these parameters can result in suboptimal performance and reduced conversion efficiency, posing challenges for industrial applications. This study conducts a detailed sensitivity analysis to identify the key parameters influencing the saponification reaction in a CSTR. It quantifies how variations in these parameters affect conversion efficiency and overall reaction performance, providing actionable insights for process optimisation. A reaction kinetics model was selected and validated using robust pilot-plant experimental data. Parameters, including reactor temperature, were systematically analysed through numerical simulations to assess their sensitivity and impact on system performance. The validated model demonstrated strong agreement with experimental results, yielding RMSE values ranging from 0.0007 to 0.0013 and R² values between 0.9996 and 0.9999 across 30, 40, 50, and 60 °C. Maximum deviation remained below 0.6 %, highlighting the model’s predictive accuracy and industrial applicability. Sensitivity analysis showed the greatest marginal benefit between 30 and 40 °C, with a peak sensitivity ratio of 0.00072, indicating that small temperature adjustments in this range have the greatest impact on the final conversion of ethyl acetate. This study sets itself apart from classical saponification research by integrating pilot-plant data with MATLAB-based analysis, offering a validated dataset and a meaningful contribution to chemical reaction engineering.