The objective of the present work is to develop models inculcating the effect of operating conditions of neem oil methyl esters (NOME) production in an oscillatory baffled reactor, namely temperature, time of reaction, oil to methanol ratio and catalyst concentration on the estimation of parameters like the viscosity of biodiesel produced by using Artificial Neural Networks technique. Experiments were conducted in the laboratory and the results obtained were used to develop the ANN model using MATLAB. The developed model was in good agreement with the experimental values (error within +1%).Based on the outcome of this demonstrative work, it can be concluded that ANN has a great potential in addressing the estimation of biodiesel properties. It is sincerely felt that the methodology adopted in the present work can be extended to more comprehensive data sets and various data from different experimental reactor design setups. KeywordsNeem Oil Methyl Ester, Oscillatory baffled reactor, artificial neural network.

The objective of present work is to inculcate the effect of the sources of crude as one of the input parameters along with volume fraction, sulfur content & specific gravity of the crude on the estimation of mean average boiling point, molecular weights by developing ANN model. It is further extended to include the effect of time element on these properties of crude for one particular source of crude. Eleven sources of crude have been selected for first part of the work & for the one particular source twenty samples at different time elements have been used. The developed ANN models are observed to be with the average accuracy of prediction within +1 % .Based on the outcome of this demonstrative work, it can be concluded that ANN has a great potential in addressing to the estimation problems related to crude properties. The novel feature of the present work is incorporation of the origin of crude & time elements along with the other properties in the ANN model developed for the prediction of important parameters like mean average boiling point & molecular weight. It is sincerely felt that the methodology adopted in the present work be extended to more comprehensive data sets.