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http://dx.doi.org/10.9713/kcer.2014.52.5.564

Comparison of Sampling and Estimation Methods for Economic Optimization of Cumene Production Process  

Baek, Jong-Bae (Department of Safety Engineering, Korea National University of Transportation)
Lee, Gibaek (Department of Chemical and Biological Engineering, Korea National University of Transportation)
Publication Information
Korean Chemical Engineering Research / v.52, no.5, 2014 , pp. 564-573 More about this Journal
Abstract
Economic optimization of cumene manufacturing process to produce cumene from benzene and propylene was studied. The chosen objective function was the operational profit per year that subtracted capital cost, utility cost, and reactants cost from product revenue and other benefit. The number of design variables of the optimization are 6. Matlab connected to and controlled Unisim Design to calculate operational profit with the given design variables. As the first step of the optimization, design variable points was sampled and operational profit was calculated by using Unisim Design. By using the sampled data, the estimation model to calculate the operational profit was constructed, and the optimization was performed on the estimation model. This study compared second order polynomial and support vector regression as the estimation method. As the sampling method, central composite design was compared with Hammersley sequence sampling. The optimization results showed that support vector regression and Hammersley sequence sampling were superior than second order polynomial and central composite design, respectively. The optimized operational profit was 17.96 MM$ per year, which was 12% higher than 16.04 MM$ of base case.
Keywords
Optimization; Response Surface Method; Central Composite Design; Hammersley Sequence Sampling; Support Vector Regression;
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Times Cited By KSCI : 3  (Citation Analysis)
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