Artificial neural network-based model for quality estimation of refined palm oil

The goal of this study is to develop an accurate artificial neural network (ANN)-based model to predict significant quality of refined palm oil which is Free Fatty Acid (FFA) content. The variables; FFA content, Iodine Value (IV), moisture content, bleaching earth and citric acid dosage as well as the pressure and temperature of the deodorizer is used to build the ANN prediction model. A feed forward neural network was designed using a back-propagation training algorithm. Comparison of ANN predicted result with industrial data was made. It is proven in this study that ANN can be used to estimate the quality of refined palm oil. Therefore, the model can be further implemented in palm oil refinery plant as the prediction system of the refined oil quality.