No abstract

In this study, an experimental measurement methodology is implemented that allows obtaining consistent temperature data during the turning operation of semi-hard C20 steel using SNMG carbide insert, allowing us to have better control at the tool-part interface. The interactions of the phenomena influencing the cut led our choices on the development of a correlation model for the analysis and prediction of the relationships between the machining parameters by measurement of the temperature. The measurement procedure implemented for the temperature estimate is based on the use of an FLIR A325sc type infrared camera mounted and protected by a device on the machine tool. The Taguchi method was chosen to find the relationships between the input factors (cutting speed (Vc), feed rate (a), depth of cut (p)), and the output factor (temperature (T)). In the future, we will develop a numerical validation model to simulate the machining process in order to predict temperatures

The deformation of metallic materials during the machining operation requires a significant amount of energy. During the chip formation process and due to the plastic deformation of the metal and the friction along the tool-part interface, the thermal loads generated are strongly impacted by the cutting factors. Thus, the choice of optimized cutting conditions is essential to control the quality of the work required. The aim of the present experimental study is to optimize the cutting parameters using temperature measurements. The average temperature of the cutting tool is studied using a FLIR A325sc type infrared camera. Optimal cutting parameters for each performance metric were obtained using the Taguchi techniques.