  In this study, an Artificial Neural Network (ANN) approach is utilized to
perform a parametric study on the process of extraction of lubricants from
heavy petroleum cuts. To train the model, we used field data collected from an
industrial plant. Operational conditions of feed and solvent flow rate,
Temperature of streams and mixing rate were considered as the input to the
model, whereas the flow rate of the main product was considered as the output
of the ANN model. A feed-forward Multi-Layer Perceptron Neural Network was
successfully applied to capture the relationship between inputs and output
parameters.
