# Simulation Prediction and Experimental Research on Surface Morphology of Ball Head Milling Processing

## TL;DR

This paper improves surface quality in die steel machining by developing a model that predicts surface morphology during ball head milling.

## Contribution

A new prediction model for ball head milling surface morphology that integrates tool vibration, eccentricity, and deformation.

## Key findings

- The model accurately predicts residual height and surface roughness with 7%–15% error compared to experiments.
- Key parameters like feed per tooth and cutting depth significantly affect surface quality.
- Simulation results align well with high-speed milling experiments, validating the model's accuracy.

## Abstract

With the aim of improving the machined surface quality of die steel, this paper takes Cr12MoV quenched die steel as the research object and proposes a ball head milling surface morphology prediction model that comprehensively considers influencing factors, including tool vibration, eccentricity, as well as deformation. By setting key parameters, such as line spacing, feed per tooth, cutting depth, and phase difference, the system analyzed the influence of each parameter on the residual height and surface roughness of the machined surface. High-speed milling experiments were conducted, and the surface morphology of the samples was observed and measured under a microscope. The simulation results show good agreement with the experimental data, with errors within 7%~15%, proving the accuracy of the model. This study can provide theoretical support and methodological guidance for surface quality control and processing parameter optimization in complex mold surface machining.