user

Optimization of Surface Quality and Cutting Efficiency for High-speed Milling Parameters of Titanium Alloy Ti-6Al-4V for Aviation Casting

被引：0
|
作者：
Wang H. [1 ]
Li N.-Q. [1 ,2 ]
Zhao G.-C. [1 ]
Zhou G.-Q. [1 ]
机构：
[1] School of Mechanical Engineering, Liaoning Technical University, Fuxin
[2] Best Machinery Manufacturing Co., Ltd., Fuxin
来源：
Surface Technology | 2022年 / 51卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Casting titanium alloy; Interaction; Milling; Parameter optimization; Response surface; Surface roughness;
D O I：
10.16490/j.cnki.issn.1001-3660.2022.02.033
中图分类号：
学科分类号：
摘要：
The work aims to study the effect law and interaction of high-speed milling parameters on the surface quality of aviation casting titanium alloy Ti-6 Al-4 V,and optimize the surface quality and material removal rate based on high-speed milling parameters.Box-Behnken design and quadratic regression orthogonal test were adopted to establish a significant no-fail regression model of surface roughness and high-speed milling parameters,and then obtain significant differences in the effects of milling. parameters on surface roughness. On this basis, the relationship between interaction of high-speed milling parameters and surface roughness was explored. Based on surface roughness regression model and material removal rate, Genetic Algorithm (GA) was used for multi-objective optimization of high-speed milling parameters. The order of significance of the milling parameters affecting the surface roughness of the aviation casting titanium alloy Ti-6Al-4V specimen was: Cutting depth > feed per tooth > cutting width > spindle speed, in which the interaction of cutting width and spindle speed, feed per tooth and spindle speed was more obvious in interaction. The values of surface roughness and material removal rate were improved by 44% and 70%, respectively after the optimization of milling parameters by GA. Therefore, the surface roughness of the specimen optimized by GA was significantly reduced, the surface toolpath row spacing was narrowed, and the average height of the texture was lowered. The experimental results indicate that the significant no-fail regression model of surface roughness established by response surface has high prediction accuracy, and the milling parameters optimized by GA can effectively improve the surface quality and cutting efficiency, which is a good guideline for ensuring the surface quality of aviation casting titanium alloy Ti-6Al-4V. © 2022, Chongqing Wujiu Periodicals Press. All rights reserved.
引用
收藏
页码：331 / 337and346
相关论文
共 18 条
  • [1] WANG Cheng, LI Kai-fa, YAO Shang-cheng, Et al., Numerical Simulation of Shot Peening of Ti6Al4V Alloy, Journal of Aerospace Power, 36, 3, pp. 449-457, (2021)
  • [2] YANG Yang, SUN Wei, WANG Liang, Et al., High Temperature Tensile Test of TC4 Titanium Alloy Based on Digital Image Correlation Method, Transactions of Materials and Heat Treatment, 42, 2, pp. 44-51, (2021)
  • [3] SUTTER G, LIST G., Very High Speed Cutting of Ti-6Al-4V Titanium Alloy-Change in Morphology and Mechanism of Chip Formation, International Journal of Machine Tools and Manufacture, 66, pp. 37-43, (2013)
  • [4] CHE-HARON C H, JAWAID A., The Effect of Machining on Surface Integrity of Titanium Alloy Ti-6%Al-4%V, Journal of Materials Processing Technology, 166, 2, pp. 188-192, (2005)
  • [5] HATT O, CRAWFORTH P, JACKSON M., On the Mechanism of Tool Crater Wear during Titanium Alloy Machining, Wear, 374, pp. 15-20, (2017)
  • [6] QIN Chang-jiang, HU Zi-hua, YUAN Biao, Et al., Surface Roughness of TC4 Titanium Alloy Machined with Polished Cemented Carbide Inserts under the Condition of Cooling Air at –50 ℃[J], Surface Technology, 49, 4, pp. 364-371, (2020)
  • [7] TAN Liang, LIU Wei-wei, YAO Chang-feng, Et al., Effect of Tool Posture on Surface Integrity in Ball End Milling of Titanium Alloy, Tool Engineering, 49, 12, pp. 39-43, (2015)
  • [8] WANG Xiao-ming, HAN Jiang, Study on Surface Roughness of High Speed Milling of TC4 Titanium Alloy, Machinery Design & Manufacture, 5, pp. 232-236, (2019)
  • [9] LI Cong-bo, CUI Long-guo, LIU Fei, Et al., Multi Objective Optimization Model of NC Machining Parameters for High Efficiency and Low Carbon, Journal of Mechanical Engineering, 49, 9, pp. 87-96, (2013)
  • [10] YANG Hou-chuan, YANG Bao-sheng, DU Xiao-wei, Et al., Research on Surface Roughness and Defect of TB6 Titanium Alloy during Milling, Aeronautical Manufacturing Technology, 5, pp. 60-66, (2017)
12