Abstract
The present study illustrates about the continuous biodiesel production from rubber seed oil (RSO) as feedstock using calcium oxide (CaO) derived from eggshells as heterogeneous catalyst. Optimization of experimental parameters like methanol: oil molar ratio (mol/mol), residence time (hours) and catalyst concentration (wt % (oil)) using two different optimization tools response surface methodology (RSM) and artificial neural networks (ANN) was investigated. 97.84 % conversion of RSO to biodiesel was observed at optimum process conditions of 9:1 M ratio (mol/mol), 4 (hours) of residence time and 5 (wt % (oil)) catalyst concentration. A compelling design model with methanol: oil molar ratio as the influencing parameter on final response was observed from RSM studies. A mean square error (MSE) value of 4.4 × 10−5 at the best validation performance of 1.3421 at epoch-2 in ANN model was observed. On comparing the coefficient of determination R2 of value 0.9118 obtained from RSM and 0.99 obtained from ANN it was concluded that ANN model fits well with experimental data in continuous biodiesel production from RSO using calcined eggshells as catalyst.
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