This study presents a simulation-based approach for analyzing tool wear progression in Ti6Al4V machining using an in-house developed hybrid Smoothed Particle Hydrodynamics–Finite Element Method (SPH-FEM) solver. Cutting experiments are used to examine key wear indicators including crater depth and flank wear land width along with SEM analysis to understand underlying wear mechanisms. Despite the dominance of diffusion-accelerated attritious wear in titanium machining, the phenomenological Usui model is selected for wear simulation. Within a two-dimensional chip formation framework, the wear algorithm is integrated at the end of each time increment to predict wear progression based on tool–chip and tool–workpiece contact conditions. A correlation between relative wear rates and the Arrhenius law coefficient across varying cutting speeds is identified through simulation, providing the foundation for a new calibration method tailored to the Usui wear model. The calibrated models are then applied back within the same simulation framework for validation, demonstrating good predictive accuracy and strong agreement with experimental trends, particularly for crater wear.
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