Efficient predictive simulation of tool wear in face milling using an advanced 3D numerical approach

Being able to predict tool life and the optimal cutting conditions for any combination of cutting tool system and workmaterial is clearly an up-to-date research issue. This work presents an innovative strategy for predicting efficiently tool wear in face milling operations. The primary objective is to develop a methodology capable of handling complex 3D geometries and tool paths within an industrially acceptable computing time. The approach involves a new 3D multi-scale numerical method based on discretizing the tool cutting edge into 2D elementary sections. A 2D Arbitrary Lagrangian-Eulerian (ALE) finite element cutting model is employed to compute local contact pressure, sliding velocity, and heat flux along each section in parallel. An elementary wear equation is applied to calculate the local wear rate after a given time increment, simulating all 2D worn profiles. These profiles are then merged to generate the updated 3D geometry of the worn tool. An iterative procedure is conducted to simulate the evolution of the cutting tool geometry over an extended cutting period. By achieving a good agreement with experimental results in a reasonable computation time, this strategy demonstrates significant potential for optimizing tool life and performance in milling operations.