Wear Progress Prediction of Carbide Tool in Turning of AISI1045 by Using FEM

Abstract

FEM is a powerful tool for predicting cutting process variables, which are difficult to obtain with experimental methods. In this paper modeling techniques on continuous chip formation using the commercial FEM code ABAQUS are discussed. A combination of three chip formation analysis steps including initial chip formation, chip growth and steady-state chip formation is used to simulate the continuous chip formation process. Furthermore, after introducing a heat transfer analysis, temperature distribution of the cutting insert at steady state is obtained. In this way, cutting process variables e.g. contact pressure (normal stress) at tool/chip and tool/work interface, relative sliding velocity and cutting temperature distribution at steady state are predicted. Many researches show that tool wear rate is dependent on these cutting process variables and their relationship is described by some wear rate models. By implementing a Python-based tool wear estimate program, that launches chip formation and heat transfer analysis, reads predicted cutting process variables, calculates tool wear based on wear rate model and then updates tool geometry, tool wear progress in turning operation is estimated. In addition, the predicted crater wear and flank wear are verified with experimental results.