4. Conclusion

In this study, a second order model was developed to investigate the effect of input parameters such as cutting speed, feed, depth of cut and tool nose radius on surface roughness of Ti-6Al-4 V ELI. The model was tested by ANOVA. The developed model was used to predict the values of the optimum process parameters in order to have minimum surface roughness. The optimum values were as follows: for cutting speed 119.59 m/min, feed rate 0.1035 mm/rev, depth of cut 1.1465 mm and nose radius 12 mm. This resulted in a predicted surface roughness of 1.9257 μm. The confirmation test was also conducted, which varies only by 15% that confirms the acceptability of the model. By the experimental investigation, it can be concluded that an increase in tool nose radius reduces the surface roughness, which corresponds with work done by previous researchers. The developed model can be used to formulate an optimization model to predict the optimum input parameters for a desired response. The integration of modern evolutionary optimization methods with the developed model can be the focus of future research.
