Abstract
Applying the response surface methodology, first-order empirical models for face milling of low carbon steel were graduated. The models relate some response measures such as surface roughness, power consumption and tool vibration to the cutting conditions, i.e. cutting speed, feed rate and depth of cut. The adequacy of the graduated models was tested using analysis of variance. The models were used to develop constant-response curves and optimization curves. The optimization curves are based on minimization of a cost function describing power consumption and cutting time of the process. The constant-response and optimization curves demonstrate how performance can be improved with proper selection of cutting conditions.