The increasing demands for burr-free workpieces after machining have been called for better its functioning and performance. Deburring is one such operation that is non-value-added and also costly. Hence, controlling burr formation is a highly relevant research topic to industry based applications. The present study investigates the effect of cutting parameters on burr height and surface roughness during drilling of low carbon steels. For this purpose, the low alloy steel specimens were drilled at different cutting parameters, longitudinally using the CNC vertical machining center. Three uncoated 12mm diameter HSS twist drills having drill-point angles of 118°, 100° and 80° have been used to conduct the drilling experiments. The experiments were carried out at (20, 25 and 31)m/min cutting speeds and (0.032, 0.05 and 0.08)mm/rev feed rates with and without using the cutting fluid. The set of experiments revealed that, the increase in feed rate and drill-point angle decreases the burr height. On the other hand, an increase in cutting speed generated less burr height. Additionally, the surface roughness of the drilled specimen was found to increase with increase in drill-point angle and feed rate. The validation of the experimental results is done by using artificial neural networks (ANNs). The neural network algorithm with the three layers is applied to model the minimum values of experimental burr height and surface roughness. The ANN values agreed very well with the experimental results.

burr, surface roughness, drilling, low carbon, artificial neural networks (ANNs).