Empirical Modelling of Temperature, Contact Length and Friction in Turning

In this paper, empirical models of mean tool-chip cutting temperature, contact length and friction law are developed. They are depend on cutting parameters in turning such as cutting speed, feed rate, depth of cut and cutting angle. The mean friction coefficient itself depends on the empirical models of contact length and mean tool-chip temperature proposed in this present work, the feed rate and the melting temperature. The identification of these models was made by a Python-Sidolo interface. This interface contains two computational steps. The first one is a python script to automatically involves the empirical approach. The second step is determining the constants of the three empirical models with Sidolo. For this purpose, the work of Sidolo consists in comparing the empirical results of temperature, contact length and mean friction coefficient outputs from Python with experimental ones. If this comparison is validated, then the constants are identified, if not a new comparison begins to research them. From the literature (Slusarczyk 2021), this experimental data in orthogonal cutting of titanium alloy grade 2 workpiece with a carbide tool was considered for identification and validation. Good agreement was found between the experimental and model results for a wide range of cutting conditions.