Prediction of Dry Milling Temperature and Surface Residual Internal Stress of TA11 Titanium Alloy

SHI Zhonglou; YANG Xiangjie; QU Binwen; YANG Xiaoyuan; LI Jiehua

doi:10.3969/j.issn.1674-6457.2026.10.011

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Journal of Netshape Forming Engineering ›› 2026, Vol. 18 ›› Issue (10) : 112-122. DOI: 10.3969/j.issn.1674-6457.2026.10.011

Light Alloy Forming

Prediction of Dry Milling Temperature and Surface Residual Internal Stress of TA11 Titanium Alloy

SHI Zhonglou¹, YANG Xiangjie^2,3,*, QU Binwen¹, YANG Xiaoyuan⁴, LI Jiehua⁵

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Abstract

The work aims to explore the evolution law of surface temperature and residual stress during milling and optimize the milling process parameters to solve the problem of surface quality degradation caused by thermal-mechanical coupling effect in TA11 titanium alloy milling, such as low dimensional accuracy and poor roughness. The dry milling test of bulk titanium alloy (88 mm×30 mm×4 mm) was carried out by orthogonal experimental design, combined with infrared thermal imager and X-ray diffraction (XRD) instrument. The effects of different milling speed (v_c=4 700, 5 300, 5 900, 6 500 r/min), feed per tooth (f_z=0.01, 0.02, 0.03, 0.04 mm/z), milling depth (a_p=0.5, 1.0, 1.5, 2.0 mm) and milling width (a_e=0.2, 0.3, 0.4, 0.5 mm) on the surface temperature and residual internal stress of the sample were studied. Results showed that the milling depth had the most significant effect on the surface temperature, with a contribution rate of 61%, and the feed per tooth had the least effect on it. The milling width had the most significant effect on the residual stress, with a contribution of 43.53%, and the milling depth had the least effect on it. The surface temperature and residual internal stress prediction models based on multiple linear regression were constructed, and the average prediction errors were 2.67% and 5.19%, respectively. After solving by the dung beetle optimization algorithm, the optimal process parameters could reduce the milling temperature by 37.64% and the residual stress by 21.14%. In conclusion, the prediction simulation has high goodness of fit. When the milling speed v_c is 7 085.32 r/min, the feed per tooth f_z is 0.02 mm/z, the milling depth a_p is 0.32 mm, and the milling width a_e is 0.1 mm, the milling temperature is 29.3 ℃, and the surface residual stress is 48 MPa. This parameter combination can effectively suppress surface degradation and significantly improve the milling quality of TA11 titanium alloy.

Key words

TA11 titanium alloy / milling temperature / surface residual internal stress / orthogonal test / prediction model / multi-objective optimization

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SHI Zhonglou, YANG Xiangjie, QU Binwen, YANG Xiaoyuan, LI Jiehua. Prediction of Dry Milling Temperature and Surface Residual Internal Stress of TA11 Titanium Alloy[J]. Journal of Netshape Forming Engineering. 2026, 18(10): 112-122 https://doi.org/10.3969/j.issn.1674-6457.2026.10.011

References

[1] KHAN M A, BRECHTL J, HAMZA M, et al.Influence of High-Strain-Rate Compression and Subsequent Heat Treatment on (TiNbZr)₈₉(AlTa)₁₁ Refractory High-Entropy Alloys: Dynamic-Mechanical Behavior and Microstructural Changes[J]. Materials & Design, 2024, 243: 113062.
[2] 侍中楼, 杨湘杰. TA11钛合金本构及铣削表面质量预测研究[J]. 精密成形工程, 2025, 17(1): 33-42.
SHI Z L, YANG X J.Constitutive Structure and Milling Surface Quality Prediction of TA11 Titanium Alloy[J]. Journal of Netshape Forming Engineering, 2025, 17(1): 33-42.
[3] 陈兵奎. 机械制造技术基础[M]. 重庆: 重庆大学出版社, 2023: 400.
CHEN B K.Fundamentals of Mechanical Manufacturing Technology[M]. Chongqing: Chongqing University Press, 2023: 400.
[4] 丁文锋, 万年, 赵彪, 等. 航空航天先进制造理论与技术研究现状及趋势[J]. 航空学报, 2025, 46(6): 195-231.
DING W F, WAN N, ZHAO B, et al.Research Status and Tendency of Advanced Manufacturing Theory and Technology in Aerospace[J]. Acta Aeronautica et Astronautica Sinica, 2025, 46(6): 195-231.
[5] ZHANG Q, SIVALINGAM V, PRASANTH B M, et al.Experimental Studies and Multi-Response Optimization of Cutting Forces, Vibrations and Groove Width Accuracy in Milling of Cortical Bone[J]. Experimental Techniques, 2026, 50(2): 201-216.
[6] 沈雪红, 张定华, 姚倡锋, 等. 钛合金切削加工表面完整性形成机制研究进展[J]. 航空材料学报, 2021, 41(4): 1-16.
SHEN X H, ZHANG D H, YAO C F, et al.Research Progress on Formation Mechanism of Surface Integrity in Titanium Alloy Machining[J]. Journal of Aeronautical Materials, 2021, 41(4): 1-16.
[7] 范滔, 姚倡锋, 谭靓, 等. γ-TiAl合金的加工特性及能场辅助技术研究进展[J]. 中国机械工程, 2025, 36(4): 636-654.
FAN T, YAO C F, TAN L, et al.Research Progresses for Machining Characteristics and Field-Assisted Techniques of γ-TiAl Alloys[J]. China Mechanical Engineering, 2025, 36(4): 636-654.
[8] 靳淇超, 李军, 叶子银, 等. 基于斜角切削的球头铣刀铣削力建模[J]. 华南理工大学学报(自然科学版), 2026, 54(1): 134-148.
JIN Q C, LI J, YE Z Y, et al.Modeling of Milling Force for Ball End Milling Cutter Based on Oblique Cutting[J]. Journal of South China University of Technology (Natural Science Edition), 2026, 54(1): 134-148.
[9] ZHANG P, CHEN Z M, GUO L W, et al.Machining of Invar 36 Alloy: Chip-Flow Behaviors and Formation Mechanisms[J]. Journal of Manufacturing Processes, 2024, 132: 477-493.
[10] 林忠钦, 于忠奇, 戴冬华, 等. 复杂高筋薄壁构件旋压-增材复合制造技术发展与展望[J]. 航空学报, 2023, 44(9): 1-24.
LIN Z Q, YU Z Q, DAI D H, et al.Development and Prospect of Metal Spinning: Additive Hybrid Manufacturing Technology for Complex Thin-Walled Component with High Ribs[J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(9): 1-24.
[11] LI G Q, ZHANG J J, XIAO G C, et al.The Study on Crack Evolution Mechanism of TiAlN-Coated Tool in Milling TC4 Titanium Alloy[J]. International Journal of Applied Ceramic Technology, 2025, 22(5): e15194.
[12] ZAWADA-MICHAŁOWSKA M, PIEŚKO P. Analysis of Machining Strategies in Terms of Residual Stress and Post-Machining Deformation of Thin-Walled Element[J]. The International Journal of Advanced Manufacturing Technology, 2026, 142(5): 2335-2358.
[13] 靳淇超, 李军, 汪亮亮, 等. 铣削工艺参数对Ti65高温钛合金加工表面完整性的影响[J]. 机械工程材料, 2025, 49(10): 43-47.
JIN Q C, LI J, WANG L L, et al.Effect of Milling Process Parameters on Machined Surface Integrity of Ti65 High Temperature Titanium Alloy[J]. Materials for Mechanical Engineering, 2025, 49(10): 43-47.
[14] 姚倡锋, 李欣悦, 曹艺隆, 等. 铣削工艺参数对GH4169D高温合金表面完整性的影响[J]. 硬质合金, 2024, 41(6): 477-486.
YAO C F, LI X Y, CAO Y L, et al.Effect of Milling Process Parameters on Surface Integrity of GH4169D High-Temperature Alloy[J]. Cemented Carbide, 2024, 41(6): 477-486.
[15] 王荣军, 杜铭轩, 张鹏翀, 等. 铣削工艺参数对AZ31B镁合金表面质量的影响[J]. 材料热处理学报, 2022, 43(11): 151-160.
WANG R J, DU M X, ZHANG P C, et al.Influence of Milling Process Parameters on Surface Quality of AZ31B Magnesium Alloy[J]. Transactions of Materials and Heat Treatment, 2022, 43(11): 151-160.
[16] 郑耀辉, 王朋, 刘娜, 等. 7075铝合金铣削参数优化仿真研究[J]. 机械设计与制造, 2020(5): 171-174.
ZHENG Y H, WANG P, LIU N, et al. Research on Milling Parameters Optimization Simulation of7075 Aluminum Alloy[J]. Machinery Design & Manufacture, 2020(5): 171-174.
[17] 孟庆元. X射线法残余应力测试原理研究[J]. 商品与质量, 2011(S2): 215.
MENG Q Y.Study on the Principle of Residual Stress Measurement by X-Ray Method[J]. The Merchandise and Quality, 2011(S2): 215.
[18] 朱和国, 尤泽升, 刘吉梓, 等. 材料科学研究与测试方法[M]. 4版. 南京: 东南大学出版社, 2019: 414.
ZHU H G, YOU Z S, LIU J Z, et al.Research and Testing Methods of Materials Science[M]. 4th ed. Nanjing: Southeast University Press, 2019: 414.
[19] 郭淼现, 黄超, 郭维诚, 等. 基于盲源分离的精密铣削振动信号分析方法与工艺优化[J]. 机械强度, 2022, 44(2): 271-278.
GUO M X, HUANG C, GUO W C, et al.Analysis Method and Process Optimization of Vibration Signal in Precision Milling Based on Blind Source Separation[J]. Journal of Mechanical Strength, 2022, 44(2): 271-278.
[20] TONG H, LIU C F, GAO J J, et al.Formation Mechanism and Morphology Observation of Chips in High- Speed Milling of Titanium Alloy[J]. Journal of Advanced Manufacturing Systems, 2024, 23(3): 549-575.
[21] 张慧萍, 王博文, 陶一涵. SCCO2-MQL超声振动铣削SiCp/Al复合材料铣削力与表面质量研究[J/OL]. 哈尔滨理工大学学报, 1-12 [2026-03-06]. https://link.cnki.net/urlid/23.1404.N.20250922.1448.002.
ZHANG H P, WANG B W, TAO Y H.Research on Milling Force and Surface Quality of SiCp/Al Composites in SCCO2-MQL Ultrasonic Vibration Milling[J/OL]. Journal of Harbin University of Science and Technology, 1-12 [2026-03-06].
[22] ZHU G X.Prediction of Milling Temperature for Nickel-Based Superalloy GH4169 Using the RIME-BP- NN Model[J]. International Journal of Precision Engineering and Manufacturing, 2026, 27(4): 1387-1401.
[23] YAN Z Y, REN X K, ZHAO H Y, et al.Investigating the Impact of Robotic Milling Parameters on the Surface Roughness of Al-Alloy Fabricated by Wire Arc Additive Manufacturing[J]. Materials, 2024, 17(19): 4845.
[24] 翟冰, 刘心藜, 李宏伟, 等. 表面完整性对钛合金弯扭疲劳寿命的影响[J]. 哈尔滨工业大学学报, 2025, 57(8): 96-104.
ZHAI B, LIU X L, LI H W, et al.Effect of Surface Integrity on Bending and Torsional Fatigue Life of Titanium Alloys[J]. Journal of Harbin Institute of Technology, 2025, 57(8): 96-104.
[25] 赵乾, 郭鑫, 李翔龙, 等. 基于GRA-RBFNN-PSO的燃气轮机叶片用N87耐热钢铣削参数优化[J/OL]. 工程科学与技术, 1-16 [2026-03-06]. https://link.cnki.net/urlid/51.1773.tb.20251114.1711.010.
ZHAO Q, GUO X, LI X L, et al. Optimization of Milling Parameters of N87 Heat-Resistant Steel for Gas Turbine Blades Based on GRA-RBFNN-PSO[J/OL]. Advanced Engineering Sciences, 1-16 [2026-03-06]. https://link.cnki.net/urlid/51.1773.tb.20251114.1711.010.
[26] 张金阳, 许伟春, 王笑含, 等. 铣削工艺优化对镍基高温合金加工残余应力分布影响研究[J]. 中国机械工程, 2024, 35(4): 624-635.
ZHANG J Y, XU W C, WANG X H, et al.Study on Influences of Milling Process Optimization on Residual Stress Distribution for Machining Nickel-Based Superalloys[J]. China Mechanical Engineering, 2024, 35(4): 624-635.
[27] UÇAK N, OUTEIRO J, ÇIÇEK A, et al. Numerical Analysis of the Influence of Sequential Cuts during Micro-Milling of Wrought and LPBF Ti₆Al₄V Alloys[J]. Manufacturing Letters, 2025, 44: 622-630.
[28] VALÍČEK J, HARNIČÁROVÁ M, KUŠNEROVÁ M, et al. Stress-Strain Parameter Prediction Method for AWJ Technology from Surface Topography[J]. The International Journal of Advanced Manufacturing Technology, 2023, 127(5): 2617-2635.
[29] 张朋朋. 大直径薄壁环框零件精密加工工艺研究[J]. 工具技术, 2025, 59(6): 122-127.
ZHANG P P.Research on Precision Machining Technology of Large Thin-Walled Ring Frame[J]. Tool Engineering, 2025, 59(6): 122-127.
[30] 章博阳, 吴柯, 朱博恩, 等. 基于改进蜣螂算法优化核极限学习机的轴承钢磨损量预测[J]. 机械制造, 2025, 63(4): 11-17.
ZHANG B Y, WU K, ZHU B E, et al.Wear Prediction of Bearing Steel Based on KELM Optimized by IDBO[J]. Machinery, 2025, 63(4): 11-17.
[31] 辛博, 曹刚, 秦嘉鑫, 等. 激光定向能量沉积NiCo- FGMs的磨削工艺优化[J]. 东北大学学报(自然科学版), 2025, 46(2): 85-95.
XIN B, CAO G, QIN J X, et al.Grinding Process Optimization of Laser-Directed Energy Deposited NiCo- FGMS[J]. Journal of Northeastern University (Natural Science), 2025, 46(2): 85-95.

Funding

Teaching Reform Research Project of Hubei Province (2024280); Teaching Reform Research Project of Hubei Province (2023287); The 2024 Ministry of Education Industry-University Cooperation and Collaborative Education Project (240900682275011)