Statistical Optimization of Process Variables for BiodieselProduction from Lagenaria Siceraria Seed Oil

Abstract

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