Validation and optimization of cutting parameters for Ti-6Al-4V turning operation using DEFORM 3D simulations and Taguchi method

• Published in: Manufacturing review (Ulis, France) Vol. 8; p. 5
• Main Authors: Obiko, Japheth Oirere, Mwema, Fredrick Madaraka, Bodunrin, Michael Oluwatosin
• Format: Journal Article
• Language: English
• Published: Les Ulis EDP Sciences 2021
• Subjects: anova; Correlation coefficients; Cutting force; cutting forces; Cutting parameters; Cutting speed; Cutting tools; Deformation; Design of experiments; Feed rate; finite element analysis; Friction; Mechanical properties; Optimization; Powder metallurgy; regression; Regression analysis; Regression models; Signal to noise ratio; Simulation; Software; Taguchi methods; ti-6al-4v machining; Titanium alloys; Titanium base alloys; Turning (machining); Variance analysis
• ISSN: 2265-4224; 2265-4224
• DOI: 10.1051/mfreview/2021001

In this study, we show that optimising cutting forces as a machining response gave the most favourable conditions for turning of Ti-6Al-4V alloy. Using a combination of computational methods involving DEFORM simulations, Taguchi Design of Experiment (DOE) and analysis of variance (ANOVA), it was possible to minimise typical machining response such as the cutting force, cutting power and chip-tool interface temperature. The turning parameters that were varied in this study include cutting speed, depth of cut and feed rate. The optimum turning parameter combinations that would minimise the machining responses were established by using the “smaller the better” criterion and selecting the highest value of Signal to Noise Ratio. Confirmatory simulation revealed that using cutting speed of 120 m/min, 0.25 mm depth of cut and 0.1 mm/rev feed rate, the lowest cutting force of 88.21 N and chip-tool interface temperature of 387.24 °C can be obtained. Regression analysis indicated that the highest correlation coefficient of 0.97 was obtained between cutting forces and the turning parameters. The relationship between cutting forces and the turning parameters was linear since first-order regression model was sufficient.