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The main objective of the present work is to work on optimisation of process parameters in acid value minimisation of biodiesel produced from rubber seed oil (RSO) using Al 2 O 3 /Calcined Eggshells as a heterogeneous catalyst. Optimisation of process parameters was performed using response surface methodology (RSM) and artificial neural network (ANN). Acid value of raw RSO is reduced from 67.6 (mg KOH/g oil) to 2.97 (mg KOH/g oil) and later it has been reduced to 0.33 (mg KOH/g oil) in the synthesised biodiesel. Form the ANOVA analysis of RSM studies, it is observed that the designed quadratic model and the parameter methanol: oil molar ratio (mol/mol) are significant. ANN model with best validation performance of 0.00065251 at epoch-2 is observed. On comparison of coefficient of regression  R2  value of 0.8885 for RSM studies and 0.9939 for ANN studies it was noticed that ANN is the best fit model with minimum error.

international journal of ambient energy

Process parameter optimisation in acid value minimisation of rubber seed oil conversion to biodiesel using Al 2 O 3 /Calcined Eggshells as catalyst – RSM and ANN studies