Optimization of turning parameters while turning Ti-6Al-4V titanium alloy for surface roughness and material removal rate using response surface methodology

The aim of this research is to study the influence of cutting fluid (Straight oil) and various input factors (speed, feed, and depth of cut) on material removal rate and the surface roughness while turning Ti-6Al-4V titanium alloy using a Micromatic automated CNC lathe machine. A mathematical prediction model has been developed to study the influence of above mentioned parameters on material removal rate and surface roughness. The mathematical prediction model uses Response Surface Methodology (RSM). Response surface plots that are generated by the model helps in determining the optimum combination of input factors for best possible material removal rate and surface roughness. The developed prediction model shows that the depth of cut followed by speed are the significant input factor that control material removal rate. Similarly, feed followed by the depth of cut are the critical input factors that influence surface roughness. An increase in material removal rate is observed with an increase in depth of cut and speed. The decrease in surface roughness is noticed with a decrease in feed and depth of cut. A confirmation test is carried out to validate the developed model. An error of less than 5% is observed between the predicted and the experimental value of material removal rate and surface roughness. Copyright (C) 2022 Elsevier Ltd. All rights reserved.