Publication

Abstract : Investigations on changes in surface roughness during machining of Ti6Al4V alloys are crucial for ensuring the quality, performance, and functionality of machined components in industries such as aerospace and biomedical. This work examined the effect of machining parameters like spindle speed, feed rate, and depth of cut on surface roughness characteristics (Ra). Using response surface methodology, central composite design, and face-centered design, 20 trials were generated in Minitab 18, and experiments were conducted. Analysis of Variance (ANOVA) was performed for Ra, and significant parameters based on the p-value were found. ANOVA study revealed that the R-sq. value for Ra was 0.9553. Response optimizer was used to obtain an optimal combination of machining parameters to achieve the best Ra value. Single Objective Optimization process of machining parameters yielded CS = 611.62 rpm, FR = 30 mm/min, and DoC = 0.3 mm for achieving the minimum value of Ra. Confirmation experiments were carried out to validate the predicted results and found that both values were in good agreement (<4%). A finite element model was developed to simulate the orthogonal turning process and validated using cutting force, obtained from the optimal combination. From the validated model, the variance of equivalent plastic strain was captured as a measure of surface roughness. The strong agreement between numerical and experimental results indicates that this modelling approach can be confidently applied in future studies to predict surface finish trends under different machining conditions.