Ethylene yield in a large-scale olefin plant utilizing regression analysis

Abstract

The research was carried out in a large-scale olefin process to see how different variables affect ethylene yield in an actual fluctuating plant condition. Regression analysis was adopted using Minitab Software Version 18 to create a reliable ethylene yield model. Regression analysis is a robust, practical, and advanced tool that is used in various applications as an alternative to the complex, expensive, and restricted simulation software that is specifically designed for the olefin process. The 1688 data taken from the studied plant underwent outliers and residuals removal utilizing normality and stability tools in Minitab for the analysis to be conducted as normal data. The Regression was conducted a few times until all variables satisfactorily met the multicollinearity criteria with Variance Inflation Factor (VIF) <10 and 95% confidence level criteria with P-Value <0.05. The final Regression model established 4 significant variables which were Hearth Burner Flow, Integral Burner Flow, Super High-Pressure Steam (SHP) Temperature, and Naphtha Feed Flow by factors of-0.001266, 0.04515,-0.0795, and 0.2105, respectively. The maximum ethylene yield was calculated at 31.75% using Response Optimizer with the recommended operating conditions at 9908.50 kg/h Hearth Burner Flow, 600.39 kg/h Integral Burner Flow, 494.65°C SHP Temperature, and 63.50 t/h Naphtha Feed Flow. Polyolefins J (2021) 8: 105-113.