Mohamad Hafizi Bin Zakria; Mohd Ghazali Mohd Nawawi; Mohd Rizal Abdul Rahman
Abstract
The study was conducted in the actual world-scale olefin plant with a focus on measuring the impact of identified controlled variables at the steam cracker furnace towards the propylene yield. Surface response analysis was conducted in the Minitab software version 20 using the historical data after the ...
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The study was conducted in the actual world-scale olefin plant with a focus on measuring the impact of identified controlled variables at the steam cracker furnace towards the propylene yield. Surface response analysis was conducted in the Minitab software version 20 using the historical data after the clearance of both the outliers and residuals to ensure the analysis was conducted as normal data. Surface response analysis is a robust mathematical and statistical approach that is having a good potential to be systematically utilized in the actual large-scale olefin plant as an alternative to the expensive olefin simulation software for process monitoring. The analysis was conducted to forecast the maximum propylene yield in the studied plant with careful consideration to select only significant variables, represented by a variance inflation factor (VIF) <10 and p-value <0.05 in the analysis of variance (ANOVA) table. The final model successfully concluded that propylene yield in the studied plant was contributed by the factors of 0.00496, 0.00204, and -3.96 of hearth burner flow, dilution steam flow, and naphtha feed flow respectively. The response optimizer also suggested that the propylene yield from naphtha pyrolysis cracking in the studied plant could be maximized at 11.47% with the control setting at 10,004.36 kg/hr of hearth burner flow, 40,960 kg/hr of dilution steam flow, and 63.50 t/hr of naphtha feed flow.
Olefin synthesis
Mohamad Hafizi Zakria; Mohd Ghazali Mohd Nawawi; Mohd Rizal Abdul Rahman; Mohd Anas Saudi
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, ...
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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.
