In the present study, a Box-Behnken design of experiment strategy is adopted to obtain necessary information from a proposed numerical simulation model using thermal-structural analysis with reduced number of runs. Influence of important process parameters on several output responses has been studied to gain insight into machining performance. The numerical model is validated through conducting necessary experiments. Subsequently, artificial neural network (ANN) is used to establish relation between input parameters and the responses. The model provides an inexpensive and time saving alternative to study the performance of machining before actual cutting operation. The model can be used for selecting ideal process states to improve machining efficiency. Copyright © 2015 Inderscience Enterprises Ltd.