Comparative Study of Temperature Prediction in the Machining Process of Ti-6Al-4V, Inconel 718 and AISI4340 Using Numerical Analysis

Abstract

In the machining process, heat generation and saturation on the cutting zone due to friction is one of the root causes of premature tool failure during dry cutting of hard-to-machine aerospace materials. Measuring and predicting thermal distribution is challenging because the tool and the workpiece are always in contact during the machining process. In this research, Finite Element Analysis (FEA) was employed to model the thermal distribution of titanium (Ti-6Al-4V), Inconel 718, and steel (AISI4340) during the machining process using three different tools: tungsten carbide, High-Speed Steel (HSS) and sintered silicon carbide. Johnson-Cook strength model and Johnson-Cook failure model were applied during the simulation using Lagrangian formulation in dry cutting. Different machining parameters i.e. cutting speed ranging from 90 to 360 m/min, depth of cut ranging from 0.5 to 2.5 mm, and rake angle ranging from 3 to 20°, were simulated and analysed. Small depth of cut of below 1 mm, low cutting speeds below 90 m/min and large rake angles above 10° are recommended for the dry cutting of these three materials to minimize the heat saturation on the cutting zone. This research provides an understanding of the relationship between material properties and heat saturation in the cutting zone for different materials. The analysis helps in the selection of predictor variables for modelling online temperature prediction using machine learning methods.