Investigation of Biodiesel Production from High Free Fatty Acid through RSM

Background/Objectives: Diesel engine's optional fuel known as Biodiesel holds fatty acids alkyl monoesters from oils of vegetable or fats of animals. It can be formed from renewable sources namely vegetable oils, restaurant waste oil and fry oil. Bio Diesel may be cost effective if produced from feedstock of low cast namely restaurant animal fats, waste oil, and fry oil, which contains of free fatty acids having high amount (FFA). Methods/Statistical Analysis: When processing these oils that are low cost problem occurs and fats are those they regularly possess huge quantity of Free Fatty Acids (FFA) which is impossible for conversion as biodiesel by means of an alkaline catalyst. In this work, a technique has been described for reducing the free fatty acids content of this feedstock's utilizing pretreatment of an acid catalyzed to esterify the free fatty acids earlier to transterifying the triglycerides with catalyst of an alkaline to fulfill the reaction. Chief principle of this work was to expand a two-step production technique of biodiesel from pork waste as a raw material. The variables were methanol to oil ration, base catalyst and acid concentration. With particular attention for optimizing, the first step was the acid catalyst esterification to reduce the free fatty acid content and the second step was alkali catalyzed Transeseterification to convert fatty acid methyl ester. Experiments established the RSM model validity. Maximum percentage of fatty acid methyl ester under optimum conditions of the variables was 93%. Findings: Optimum condition for Transeseterification was 13:1 of methanol to oil, 0.4gm sodium hydroxide concentration and 90min of reaction time. Optimum condition for the acid catalyzed esterification was found to be 1.5v/v. ANOVA analysis has been executed for studying the effect of the variables and response surfaces were plotted. Experiments established the RSM model validity. Applications/Improvements: Experiments are going to be establishing the RSM model validity along with tuning with the help of intelligent algorithms.