Shang Peng, Zhang Huaiqing, Liu Xiaopeng, Yang Zhuang, Liu Bingfeng, Liu Teng
School of Mechanical Engineering, Hebei University of Technology, Tianjin 300400, China.
Micromachines (Basel). 2023 Jul 14;14(7):1422. doi: 10.3390/mi14071422.
This study aims to enhance surgical safety and facilitate patient recovery through the investigation of vibration-assisted micro-milling technology for bone-material removal. The primary objective is to reduce cutting force and improve surface quality. Initially, a predictive model is developed to estimate the cutting force during two-dimensional (2D) vibration-assisted micro-milling of bone material. This model takes into account the anisotropic structural characteristics of bone material and the kinematics of the milling tool. Subsequently, an experimental platform is established to validate the accuracy of the cutting-force model for bone material. Micro-milling experiments are conducted on bone materials, with variations in cutting direction, amplitude, and frequency, to assess their impact on cutting force. The experimental results demonstrate that selecting appropriate machining parameters can effectively minimize cutting force in 2D vibration-assisted micro-milling of bone materials. The insights gained from this study provide valuable guidance for determining cutting parameters in vibration-assisted micro-milling of bone materials.
本研究旨在通过研究振动辅助微铣削技术去除骨材料，提高手术安全性并促进患者康复。主要目标是降低切削力并改善表面质量。首先，建立一个预测模型来估计骨材料二维（2D）振动辅助微铣削过程中的切削力。该模型考虑了骨材料的各向异性结构特征和铣刀的运动学。随后，搭建一个实验平台来验证骨材料切削力模型的准确性。对骨材料进行微铣削实验，改变切削方向、振幅和频率，以评估它们对切削力的影响。实验结果表明，选择合适的加工参数可以有效降低骨材料二维振动辅助微铣削中的切削力。本研究获得的见解为确定骨材料振动辅助微铣削中的切削参数提供了有价值的指导。
