Cui Youzheng, Li Xinmiao, Zheng Minli, Mu Haijing, Liu Chengxin, Wang Dongyang, Yan Bingyang, Li Qingwei, Jiang Hui, Wang Fengjuan, Hu Qingming
School of Mechanical and Electronic Engineering, Qiqihar University, Qiqihar 161006, China.
Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin 150080, China.
Materials (Basel). 2025 May 19;18(10):2355. doi: 10.3390/ma18102355.
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.
为了提高模具钢的加工表面质量,本文以Cr12MoV淬火模具钢为研究对象,提出了一种综合考虑刀具振动、偏心以及变形等影响因素的球头铣削表面形貌预测模型。通过设置行距、每齿进给量、切削深度和相位差等关键参数,系统分析了各参数对加工表面残余高度和表面粗糙度的影响。进行了高速铣削实验,并在显微镜下观察和测量了样品的表面形貌。模拟结果与实验数据吻合良好,误差在7%~15%以内,证明了模型的准确性。该研究可为复杂模具表面加工中的表面质量控制和加工参数优化提供理论支持和方法指导。