# Simulation and Experimental Study on Abrasive–Tool Interaction in Drag Finishing Edge Preparation

## TL;DR

This paper studies how drag finishing affects tool edge preparation using simulations and experiments to optimize cutting tool performance and longevity.

## Contribution

A validated DEM model is introduced to analyze the effects of drag finishing parameters on tool wear and edge geometry.

## Key findings

- Increasing processing time and rotational speed leads to higher tool wear and cumulative energy.
- Rotation direction significantly affects tool wear and edge shape factor K.
- Experimental results align with simulations, confirming the model's predictive accuracy.

## Abstract

Tool edge preparation is the process aimed at eliminating edge defects and optimizing the micro-geometric parameters of cutting tools. Drag finishing, the primary engineering method, subjects tools to planetary motion (simultaneous revolution and rotation) within abrasive media to remove burrs and micro-chips, thereby improving cutting performance and extending tool life. A discrete element method (DEM) model of drag finishing edge preparation was developed to investigate the effects of processing time, tool rotational speed, and rotation direction on abrasive-mediated tool wear behavior. The model was validated through milling cutter edge preparation experiments. Simulation results show that increasing the processing time causes fluctuating changes in average abrasive velocity and contact forces, while cumulative energy and tool wear increase progressively. Elevating tool rotational speed increases average abrasive velocity, contact forces, cumulative energy, and tool wear. Rotation direction significantly impacts tool wear: after 2 s of clockwise (CW) rotation, wear reached 1.45 × 10−8 mm; after 1 s of CW followed by 1 s of counterclockwise (CCW) rotation, wear was 1.25 × 10−8 mm; and after 2 s of CCW rotation, wear decreased to 1.02 × 10−8 mm. Experiments, designed based on simulation trends, confirm that edge radius increases with time and tool rotational speed. After 30 min of processing at 60, 90, and 120 rpm, average edge radius increased to 22.5 μm, 28 μm, and 30 μm, respectively. CW rotation increased the edge shape factor K, while CCW rotation decreased it. The close agreement between experimental and simulation results confirms the model’s effectiveness in predicting the impact of edge preparation parameters on tool geometry. Rotational speed control optimizes edge preparation efficiency, the predominant tangential cumulative energy reveals abrasive wear as the primary material removal mechanism, and rotation direction modulates the shape factor K, enabling symmetric edge preparation.