This conference paper was submitted for presentation at the NAFEMS World Congress 2025, held in Salzburg, Austria from May 19–22, 2025.

Abstract

Modeling chip formation is essential to any finite element (FE) approach to simulate metal cutting processes. The intricate behavior of the chip, particularly its extreme deformation, combined with the high strain rates across the primary, secondary, and tertiary deformation zones, poses significant challenges in maintaining simulation stability. A central issue is the potential development of highly distorted elements, leading to premature termination of the simulation. The Arbitrary Lagrangian-Eulerian (ALE) method has emerged as a widely used technique in metal cutting simulations to address these issues. This method is particularly effective in managing mesh distortion issues fostered by the high strain rates during metal cutting. By combining the strengths of both Lagrangian and Eulerian frameworks, the ALE method allows for a more robust representation of chip formation. Following this approach, the relevant part of the workpiece can be delimited by Eulerian, Lagrangian, or sliding surfaces, thus achieving model reduction while still capturing critical details of the cutting mechanism. Despite the effectiveness of the ALE approach in preventing mesh distortion, challenges remain, particularly in metal cutting setups with non-constant chip thickness. In contrast to turning processes, milling yields non-constant chip thicknesses due to following a trajectory during the tool's engagement with the workpiece. This transient behavior leads to difficulties using standard adaptive mesh algorithms. They often fail to prevent premature simulation termination. Previous studies have introduced approaches to stabilize the mesh quality within the chip formation zone. These models, validated through experimental data such as measured residual stresses on the tool rake face and online temperature measurements from instrumented end mills, have shown promise in addressing the mesh stability issue. The published approach involves the imposition of kinematic ALE mesh constraints. On the one hand, these constraints modify the behavior of the mesh by ensuring that nodes in the workpiece outside the process zone follow the movement of the cutting tool edge. On the other hand, the mesh within the process zone is constantly updated to maintain a high-quality mesh and preserve simulation accuracy. This kinematic approach allows for a realistic simulation of the milling process kinematics. It represents the movement of the tool relative to the workpiece without the need for transformations of the movement path or the introduction of an artificial initial chip thickness. This method allows the simulation to follow the tool's trajectory for the first time, improving the model's accuracy and stability. Building on these advancements, this work introduces an expanded and novel strategy that further improves the stability and accuracy of the simulation. An initial mesh pattern is defined based on the specific parameters of the cutting process, ensuring that the mesh is well-suited to the expected conditions from the outset. Additionally, the strategy incorporates time-dependent ALE mesh constraints, which guide the evolution of the mesh as the cutting process progresses. These constraints ensure that nodes and their associated elements are dynamically repositioned to follow the cutting tool's movement and the chip root's changing geometry, which becomes thinner as the climb milling process advances. The simulation maintains mesh compatibility and stability over time by adjusting nodes appropriately throughout the process. The focus lies on the model-building and model-reduction aspects of chip formation. Integrating new techniques into existing FE models provides a more robust and reliable method for simulating chip formation in metal cutting processes, improving accuracy and computational efficiency.