Optimization of the Process Parameters for Hydrotreating Used Cooking Oil by the Taguchi Method and Fuzzy Logic

Abstract

Abstract Hydrotreating process is an alternate approach for producing diesel hydrocarbons from the biomass-based oils. In the present study, used cooking oil was selected for the hydrotreating process due to its high abundance. A batch reactor was used for carrying out the experiments. To increase the reaction rate a manganese, cerium promoted ruthenium-based catalyst supported on Al2O3 was used. The design of experiments was used for optimizing the process parameters. The Taguchi method was selected as it reduces the number of experiments which saves time and money. The study was aimed at increasing the conversion percentage and diesel selectivity and reducing the naphtha selectivity. Since multi-objective optimization was required, fuzzy logic was incorporated which utilizes the human thought logic. The analysis of variance shows that the reaction temperature and reaction pressure significantly affect the output parameters. Higher temperature leads to cracking of the oil resulting in the formation of large amount of lower carbon chains. Moreover, high hydrogen pressure results in increase in the hydrogenation process, thereby increasing the diesel selectivity. The optimized parameters obtained from the study were 360 °C reaction temperature, 40-bar initial reaction pressure, and 200-min reaction time. Confirmation experiment was carried out using these parameters, and the conversion efficiency and diesel selectivity was 89.7% and 88.2%, respectively. The study shows that the combination of Taguchi and fuzzy logic is an effective method for optimizing the process parameters of the hydrotreating process.