Statistical Optimization of Process Variables for Biodiesel Production from Lagenaria Siceraria Seed Oil - Usman Rufai Fakai (International Journal of Integrative Research, 2023)
Rising energy demand has led to progressive increase in the cost of fossil fuel globally. The exploration and exploitation of fossil fuel has led to depletion of oil reserves, moreover these fossil fuels are not only expensive but also has severe environmental consequences. Renewable and sustainable energy resources gained greater importance in the current situation to supplement and minimize the environmental pollution load and to compensate the energy demand worldwide. Biodiesel can be produced from myriad sources such as waste or virgin oil, algae, and animal fats. Optimization of process variables to produce biodiesel proves to be economic and effective way of producing biodiesel. In this study RSM based optimization was carried out using five-level, four-factorial central composite design in thirty (30) runs. Design expert version 6.0 was used for the study. The four processing variables under study are A: catalyst concentration, B: methanol to oil molar ratio, C: reaction time and D: temperature. The optimum conditions for maximum biodiesel (88.40%) was; methanol to oil molar ratio (9.07:1), reaction time (70.59min), reaction temperature (53.090C), and amount of catalyst (0.88). The regression equation obtained for the model having a coefficient of correlation (R2), and adjusted coefficient of correlation (R2adj) are “Pred R-Squared" of 0.927 is in reasonable agreement with the "Adj R-Squared" of 0.911. "Adeq Precision" measures the signal to noise ratio.  A ratio greater than 4 is desirable. Ratio of 13.200 reported for this work indicates an adequate signal.