Assessment of cutting tool wear using a numerical FEM simulation model

The advancement of computational modeling techniques, such as FEM, has allowed to simulate complex machining processes with improved accuracy. Wear prediction is a crucial aspect in understanding and optimizing machining processes, as it directly impacts tool life, surface quality and overall machining efficiency. This work focuses on the FEM simulation, specially utilizing the DEFORM software, in conjunction with the Usui wear model, for wear prediction in machining operations. The Usui wear model, a well-established and widely used wear prediction approach, accounts for multiple wear mechanisms that include adhesion, abrasion, and diffusion. By incorporating the Usui wear model into the FEM simulation framework within the DEFORM software, it is possible to understand wear phenomena in machining processes. The integration of Usui wear model algorithms into DEFORM enables the simulation to accurately predict wear rates, distribution patterns, and progression of tool deterioration. This predictive capability facilitates the identification of critical wear zones and guides proactive measures to improve tool life, reduce production costs, and optimize machining productivity. This work presents research focused on wear prediction in cutting processes, utilizing FEM simulation with DEFORM software and incorporating the Usui wear model. Through a comprehensive analysis of wear phenomena, this research aims to optimize cutting parameters, improve tool life, and contribute to the advancement of machining and manufacturing technologies.