Experimental development of RSM techniques for surface quality prediction in metal cutting applications

The aim of this work is to analyze the influence of cutting conditions on surface roughness with slot end milling on AL7075-T6. The considered parameters are: cutting speed, feed, depth of cutting and mill radial engage. Response surface models based on experimental data obtained with physical tests have been developed, the authors have performed a consistent set of experimental tests based on design points selected within the four-dimensional design space. Each test has been repeated 3 times to ensure the stability of the collected statistical data. These well distributed results has been subsequently used to create RS models through approximation techniques based on polynomial and neural network methods and to verify their reliability in terms of correct responses behaviour. The obtained results show that the most significant factors affecting the surface roughness are feed and speed.