Please wait a minute...
Shopping Cart Email List Chinese
Advanced Search Fig/Tab
Frontiers of Mechanical Engineering

ISSN 2095-0233

ISSN 2095-0241(Online)

CN 11-5984/TH

Postal Subscription Code 80-975

2018 Impact Factor: 0.989

Featured Articles  |  Most Downloaded  |  Most Reading
Online Submission Subscribe to Our RSS Content Feed
Front. Mech. Eng.    2024, Vol. 19 Issue (4) : 28    https://doi.org/10.1007/s11465-024-0800-8
Force model in electrostatic atomization minimum quantity lubrication milling GH4169 and performance evaluation
Min YANG1,2, Hao MA1, Zhonghao LI1, Jiachao HAO1, Mingzheng LIU1, Xin CUI1, Yanbin ZHANG1, Zongming ZHOU3, Yunze LONG2, Changhe LI1()
1. School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China
2. College of Physics, Qingdao University, Qingdao 266071, China
3. Hanergy Lubrication Technology Co., Ltd., Qingdao 266200, China
 Download: PDF(5345 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

The nickel-based high-temperature alloy GH4169 is the material of choice for manufacturing critical components in aeroengines, and electrostatic atomization minimum quantity lubrication (EMQL) milling represents a fundamental machining process for GH4169. However, the effects of electric field parameters, jet parameters, nozzle position, and milling parameters on milling performance remain unclear, which constrains the broad application of EMQL in aerospace manufacturing. This study evaluated the milling performance of EMQL on nickel-based alloys using soybean oil as the lubrication medium. Results revealed that compared with conventional pneumatic atomization MQL milling, EMQL reduced the milling force by 15.2%–15.9%, lowered the surface roughness by 30.9%–54.2%, decreased the average roughness spacing by 47.4%–58.3%, and decreased the coefficient of friction and the specific energy of cutting by 55% and 19.6%, respectively. Subsequent optimization experiments using orthogonal arrays demonstrated that air pressure most significantly affected the milling force and specific energy of cutting, with a contribution rate of 22%, whereas voltage had the greatest effect on workpiece surface roughness, contributing 36.71%. Considering the workpiece surface morphology and the potential impact of droplet drift on environmental and health safety, the optimal parameter combination identified were a flow rate of 80 mL/h, an air pressure of 0.1 MPa, a voltage of 30 kV, a nozzle incidence angle of 35°, an elevation angle of 30°, and a target distance of 40 mm. This research aimed to provide technical insights for improving the surface integrity of aerospace materials that are difficult to machine during cutting operations.
Keywords electrostatic atomization      MQL      nickel-based alloys      milling force      surface roughness      force model     
Corresponding Author(s): Changhe LI   
Issue Date: 23 August 2024
 Cite this article:   
Min YANG,Hao MA,Zhonghao LI, et al. Force model in electrostatic atomization minimum quantity lubrication milling GH4169 and performance evaluation[J]. Front. Mech. Eng., 2024, 19(4): 28.
 URL:  
https://academic.hep.com.cn/fme/EN/10.1007/s11465-024-0800-8
https://academic.hep.com.cn/fme/EN/Y2024/V19/I4/28
Fig.1  Force diagram of the milling microelements.
Equipment parameter Unit Value
Spindle power kW 4.2
Spindle torque N·m 1.4
Cutting range mm × mm × mm 100 × 100 × 30
Rated speed r·min−1 24000
Tab.1  Main parameters of the experimental platform
Fig.2  Experimental equipment and measuring device.
Ni C Cr Nb Cu Mo Ti Co Mn Al Fe
50–55 0.08 17–21 5.25 0.3 3.1 0.96 1.0 0.35 0.95 Bal.
Tab.2  Chemical composition of the GH4169 nickel-based alloya)
Tensile strength/MPa Yield strength/MPa Elastic modulus/GPa Hardness (HBS) Density/(g·cm−3)
965 550 199.9 435 8.24
Tab.3  Performance parameters of the GH4169 nickel-based alloy
C14:0 C16:0 C18:0 C18:1 C18:2 C18:3 C20:0 C21:0 SFA MUFA PUFA
0.06 10.30 3.78 22.30 50.84 5.90 0.29 0.36 14.92 22.87 57.83
Tab.4  Contents of various fatty acids in soybean oila)
Milling parameter Unit Value
Milling type – Sideways milling
Milling cutter speed r·min−1 9000
Milling cutter diameter mm 4
Milling cutter helix angle ° 45
Radial depth of cut μm 20
Axial depth of cut mm 10
Feed rate mm·min−1 100
Tab.5  Milling parameters
Group Barometric/MPa Voltage/kV
No. 1 0.05 0
No. 2 0.05 20
No. 3 0.05 30
No. 4 0.05 40
No. 5 0.10 0
No. 6 0.10 20
No. 7 0.10 30
No. 8 0.10 40
No. 9 0.15 0
No. 10 0.15 20
No. 11 0.15 30
No. 12 0.15 40
Tab.6  Experimental scheme of milling lubrication performance
Fig.3  (a) Typical milling force measurement signal diagram. (b) Milling component in the x and y directions and resultant force.
Fig.4  Friction coefficient and cutting specific energy.
Fig.5  Surface profile diagram of Ra and RSm values.
Fig.6  Autocorrelation function curve (ACF) of the workpiece contour surface.
Fig.7  (a–c) Microaction mechanism of charged droplets in the cutting process.
Fig.8  Mechanism of the increasing and decreasing benefits of the electric field.
Fig.9  Laser confocal microscopy.
Factor Unit Level 1 Level 2 Level 3
Flow rate, A mL·h−1 60 80 100
Barometric, B MPa 0.05 0.10 0.15
Voltage, C kV 20 30 40
Angle of incidence, D ° 15 35 55
Azimuthal angle, E ° 30 50 70
Target distance, F mm 30 40 50
Tab.7  Orthogonal experiment factor levels
No. A B C D E F Error Experimental program
1 2 3 4 5 6 7 A B C D E F
1 1 1 1 1 1 1 1 60 0.05 20 15 30 30
2 1 2 2 2 2 2 2 60 0.10 30 35 50 40
3 1 3 3 3 3 3 3 60 0.15 40 55 70 50
4 2 1 1 2 2 3 3 80 0.05 20 35 50 50
5 2 2 2 3 3 1 1 80 0.10 30 55 70 30
6 2 3 3 1 1 2 2 80 0.15 40 15 30 40
7 3 1 2 1 3 2 3 100 0.05 30 15 70 40
8 3 2 3 2 1 3 1 100 0.10 40 35 30 50
9 3 3 1 3 2 1 2 100 0.15 20 55 50 30
10 1 1 3 3 2 2 1 60 0.05 40 55 50 40
11 1 2 1 1 3 3 2 60 0.10 20 15 70 50
12 1 3 2 2 1 1 3 60 0.15 30 35 30 30
13 2 1 2 3 1 3 2 80 0.05 30 55 30 50
14 2 2 3 1 2 1 3 80 0.10 40 15 50 30
15 2 3 1 2 3 2 1 80 0.15 20 35 70 40
16 3 1 3 2 3 1 2 100 0.05 40 35 70 30
17 3 2 1 3 1 2 3 100 0.10 20 55 30 40
18 3 3 2 1 2 3 1 100 0.15 30 15 50 50
Tab.8  Experimental schemea)
No. F/N U/(J·mm−3) Ra/μm S/NF S/NU S/NRa
1 43.68 68.61 0.71 −32.81 −36.73 2.94
2 37.82 59.41 0.44 −31.55 −35.48 7.23
3 44.82 70.40 0.67 −33.03 −36.95 3.49
4 42.97 67.50 0.73 −32.67 −36.59 2.70
5 39.58 62.17 0.40 −31.95 −35.87 8.02
6 40.36 63.40 0.52 −32.12 −36.04 5.73
7 40.87 64.20 0.49 −32.23 −36.15 6.23
8 41.62 65.38 0.62 −32.39 −36.31 4.14
9 43.04 67.61 0.70 −32.68 −36.60 3.11
10 47.26 74.24 0.72 −33.49 −37.41 2.91
11 40.08 62.96 0.49 −32.06 −35.98 6.14
12 44.56 70.00 0.41 −32.98 −36.90 7.74
13 37.88 59.50 0.44 −31.57 −35.49 7.11
14 42.96 67.48 0.53 −32.66 −36.58 5.53
15 39.77 62.47 0.45 −31.99 −35.91 6.92
16 40.73 63.98 0.43 −32.20 −36.12 7.27
17 39.17 61.53 0.32 −31.86 −35.78 9.87
18 45.44 71.38 0.45 −33.15 −37.07 6.94
Tab.9  Experimental results and signal-to-noise (S/N) ratioa)
Fig.10  Effect curve of each factor corresponding to the milling force index.
Fig.11  Effect curve of each factor corresponding to the cutting specific energy index.
Fig.12  Effect curve of each factor corresponding to the roughness index.
Source of variance Factor Square sum Mean square F-value
Force, F/N A 17.96 8.98 1.30
B 25.03 12.51 1.94
C 12.37 6.18 0.85
D 3.09 1.55 0.20
E 18.76 9.38 1.37
F 8.14 4.07 0.54
Error 30.40 15.20 2.49
ST 115.74
Specific cutting energy, U/(J·mm−3) A 44.43 22.22 1.30
B 61.67 30.84 1.94
C 30.55 15.27 0.85
D 7.68 3.84 0.20
E 46.25 23.13 1.36
F 20.11 10.05 0.54
Error 74.92 37.46 2.49
ST 285.61
Surface roughness, Ra/μm A 0.02 0.01 0.50
B 0.04 0.02 1.39
C 0.08 0.04 2.77
D 0.01 0.01 0.06
E 0.04 0.02 1.18
F 0.02 0.01 0.55
Error 0.01 0.01 0.25
ST 0.21
Tab.10  Variance analysis results of the force, specific energy, and surface roughness
Fig.13  Contribution ratio of each factor to the force, specific energy, and surface roughness.
Fig.14  Surface topography of the workpiece under different working conditions.
Abbreviations
ACF Autocorrelation function curve
EMQL Electrostatic atomization minimum quantity lubrication
MQL Minimal quantity lubrication
S/N Signal-to-noise
Variables
dFa(φ, z) Axial force on the micro cutting edge
dFt(φ, z) Tangential force on the micro cutting edge
dFr(φ, z) Radial force on the microdimensional cutting edge
dz Thickness of the cutting edge micro element
F Milling force
F ¯max Mean value
Fmax,i Peak milling force of the ith milling force in the collected data
ft Feed rate
h[φ(z)] Undeformed chip thickness
hc Sampling interval
Kte, Kre, Kae Edge force coefficient in each direction
Ktc, Krc, Kac Coefficient of shear force in all directions
L Sampling length
m Maximum number of transverse displacements
n Number of data obtained
Nm Sampling capacity
Pz Total energy consumed
r Number of transverse displacements
Ra Arithmetic mean deviation of surface profile
RSm Average width of surface contour lines
t Machining time
UW Specific energy
V Milling tool linear speed
Vj Area swept by the milling cutter on the workpiece surface per unit time
Vw Workpiece removal volume
x(t), x(t+τ) Distance between surface contour and centerline at t and t + τ
yi Actual sample data obtained
Yn Height value of the nth contour
Yn+r Height value of the contour at (n + r)th place
Z(x) Arithmetic mean of contour height
αp Radial depth of cut
γ Angle of incision
ωs Angular velocity
η Helix angle
φ0 Angle of radial position of the cutting edge micro element
φex Angle of incision of the tool
φst Angle of incision of the tool
φ(z) Instantaneous tooth position angle
  
1 W Tian, S Chang, C S Zhou, W D Zhang, Z H Feng, X Y Sun, R Su. Microstructure transformation and metallographic analysis of nickel-based wrought superalloy during heat treatment. Heat Treatment of Metals, 2021, 46(8): 30–35 (in Chinese)
2 W H Xu, C H Li, X Cui, Y B Zhang, M Yang, T Gao, M Z Liu, X M Wang, Z M Zhou, S Sharma, Y S Dambatta. Atomization mechanism and machinability evaluation with electrically charged nanolubricant grinding of GH4169. Journal of Manufacturing Processes, 2023, 106: 480–493
https://doi.org/10.1016/j.jmapro.2023.10.037
3 P Gong, Y B Zhang, C J Wang, X Cui, R Z Li, S Sharma, M Z Liu, T Gao, Z M Zhou, X M Wang, Y S Dambatta, C H Li. Residual stress generation in grinding: mechanism and modeling. Journal of Materials Processing Technology, 2024, 324: 118262
https://doi.org/10.1016/j.jmatprotec.2023.118262
4 Y X Song, C H Li, Z M Zhou, B Liu, S Sharma, Y S Dambatta, Y B Zhang, M Yang, T Gao, M Z Liu, X Cui, X M Wang, W H Xu, R Z Li, D Z Wang. Nanobiolubricant grinding: a comprehensive review. Advances in Manufacturing, 2024
5 S G Hu, C H Li, B K Li, M Yang, X M Wang, T Gao, W H Xu, Y S Dambatta, Z M Zhou, P M Xu. Digital twins enabling intelligent manufacturing: from methodology to application. Intelligent and Sustainable Manufacturing, 2024, 1(1): 10007
6 Y S Dambatta, C H Li, M Sayuti, A A D Sarhan, M Yang, B K Li, A X Chu, M Z Liu, Y B Zhang, Z Said, Z M Zhou. Grindability evaluation of ultrasonic assisted grinding of silicon nitride ceramic using minimum quantity lubrication based SiO2 nanofluid. Chinese Journal of Mechanical Engineering, 2024, 37(1): 25
https://doi.org/10.1186/s10033-024-01011-x
7 Y X Shi, B Zhao, W F Ding. Solid additives to increase the service life of ceramic cutting tool: methodology and mechanism. Intelligent and Sustainable Manufacturing, 2024, 1: 10009
8 X F Xu, T Lv, Z Q Luan, Y Y Zhao, M H Wang, X D Hu. Capillary penetration mechanism and oil mist concentration of Al2O3 nanoparticle fluids in electrostatic minimum quantity lubrication (EMQL) milling. The International Journal of Advanced Manufacturing Technology, 2019, 104(5–8): 1937–1951
https://doi.org/10.1007/s00170-019-04023-3
9 J Khosravi, B Azarhoushang, M Barmouz, R Bösinger, A Zahedi. High-speed milling of Ti6Al4V under a supercritical CO2+MQL hybrid cooling system. Journal of Manufacturing Processes, 2022, 82: 1–14
https://doi.org/10.1016/j.jmapro.2022.07.061
10 G Q Gu, D Z Wang, S J Wu, S Zhou, B X Zhang. Research status and prospect of ultrasonic vibration and minimum quantity lubrication processing of nickel-based alloys. Intelligent and Sustainable Manufacturing, 2024, 1: 10006
11 K Kong, Z Q Hu, W Q Yao, S Q Huang, X F Xu. Sizes distribution characteristics of cutting fluid droplets for electrostatic atomization minimum quantity lubrication. Journal of Mechanical & Electrical Engineering, 2013, 30(12): 1472–1476 (in Chinese)
12 M K Patel, T Sharma, M K Nayak, C Ghanshyam. Computational modeling and experimental evaluation of the effects of electrode geometry and deposition target on electrostatic spraying processes. International Journal of Computer Applications, 2015, 124(2): 10–15
https://doi.org/10.5120/IJCA2015905358
13 N S K Reddy, M Yang. Development of an electrostatic lubrication system for drilling of SCM 440 steel. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2009, 224(2): 217–224
https://doi.org/10.1243/09544054JEM1670
14 H Jiang, Y Su. Study on atomization characteristics and machining performance of coaxial electrostatic atomization cutting. Modular Machine Tool & Automatic Manufacturing Technique, 2021, 6: 146–149 (in Chinese)
15 Z C Tang, Y Su. Investigation on co-axial electrostatic atomization cutting. Tool Engineering, 2018, 52(5): 51–55 (in Chinese)
16 M Yang, J C Hao, W T Wu, Z H Li, Y Q Ma, Z M Zhou, T Gao, M Z Liu, X Cui, Y B Zhang, B K Li, X Ma, Y S Dambatta, C H Li. Critical cutting thickness model considering subsurface damage of zirconia grinding and friction–wear performance evaluation applied in simulated oral environment. Tribology International, 2024, 198(10): 109881
17 C H Li. Thermodynamic Mechanism of MQL Grinding with Nano Bio-lubricant. Berlin: Springer, 2024, 43–115
18 S Q Huang, T Lv, X F Xu, Y L Ma, M H Wang. Experimental evaluation on the effect of electrostatic minimum quantity lubrication (EMQL) in end milling of stainless steels. Machining Science and Technology, 2018, 22(2): 271–286
https://doi.org/10.1080/10910344.2017.1337135
19 X F Xu, S Q Huang, M H Wang, W Q Yao. A study on process parameters in end milling of AISI-304 stainless steel under electrostatic minimum quantity lubrication conditions. The International Journal of Advanced Manufacturing Technology, 2017, 90(1): 979–989
https://doi.org/10.1007/s00170-016-9417-3
20 S Q Huang, T Lv, M H Wang, X F Xu. Enhanced machining performance and lubrication mechanism of electrostatic minimum quantity lubrication-EMQL milling process. The International Journal of Advanced Manufacturing Technology, 2018, 94(1): 655–666
https://doi.org/10.1007/s00170-017-0935-4
21 S Q Huang, T Lv, M H Wang, X F Xu. Effects of machining and oil mist parameters on electrostatic minimum quantity lubrication–EMQL turning process. International Journal of Precision Engineering and Manufacturing-Green Technology, 2018, 5(2): 317–326
https://doi.org/10.1007/s40684-018-0034-5
22 T Lv, X F Xu, A B Yu, X D Hu. Oil mist concentration and machining characteristics of SiO2 water-based nano-lubricants in electrostatic minimum quantity lubrication-EMQL milling. Journal of Materials Processing Technology, 2021, 290: 116964
https://doi.org/10.1016/j.jmatprotec.2020.116964
23 A De Bartolomeis, S T Newman, A Shokrani. High-speed milling inconel 718 using electrostatic minimum quantity lubrication (EMQL). Procedia CIRP, 2021, 101: 354–357
https://doi.org/10.1016/j.procir.2021.02.038
24 J Y Xu, L F Li, T Y Lin, M K Gupta, M Chen. Machinability analysis in high-speed milling of AlSi7Mg alloys under EMQL conditions: an approach toward sustainable manufacturing. Journal of Manufacturing Processes, 2022, 81: 1005–1017
https://doi.org/10.1016/j.jmapro.2022.07.010
25 F C Liu, X Z Wu, Y Xia, T Lv, R C Zhang, X D Hu, X F Xu. A novel cold air electrostatic minimum quantity lubrication (CAEMQL) technique for the machining of titanium alloys Ti–6Al–4V. The International Journal of Advanced Manufacturing Technology, 2023, 126(7–8): 3437–3452
https://doi.org/10.1007/s00170-023-11222-6
26 L Y Li, Y B Zhang, X Cui, Z Said, S Sharma, M Z Liu, T Gao, Z M Zhou, X M Wang, C H Li. Mechanical behavior and modeling of grinding force: a comparative analysis. Journal of Manufacturing Processes, 2023, 102: 921–954
https://doi.org/10.1016/j.jmapro.2023.07.074
27 D W Liu, C H Li, A G Qin, B Liu, Y Chen, Y B Zhang. Kinematic analysis and milling force model of rotary surface milling machine of cutting machine. Journal of Mechanical Engineering, 2024, 1–13 (in Chinese)
28 Z Shi, C H Li, D W Liu, Y B Zhang, A G Qin, H J Cao, Y Chen. The instantaneous milling force model and verification of unequal helix angle end mill. Journal of Mechanical Engineering, 2024, 1–14 (in Chinese)
29 R H Zhou. Analytical model of milling forces prediction in five-axis milling process. The International Journal of Advanced Manufacturing Technology, 2020, 108(9): 3045–3054
https://doi.org/10.1007/s00170-020-05582-6
30 C L He, J W Yan, S Q Wang, S Zhang, G Chen, C Z Ren. A theoretical and deep learning hybrid model for predicting surface roughness of diamond-turned polycrystalline materials. International Journal of Extreme Manufacturing, 2023, 5(3): 035102–2632
31 W Y Cui, H Z Chen, J X Zhao, Q S Ma, Q Xu, T B Ma. Progresses on cryo-tribology lubrication mechanisms, detection methods and applications. International Journal of Extreme Manufacturing, 2023, 5: 022004
32 N Chen, M J Chen, C Y Wu, X D Pei, J Qian, D Reynaerts. Research in minimum undeformed chip thickness and size effect in micro end-milling of potassium dihydrogen phosphate crystal. International Journal of Mechanical Sciences, 2017, 134: 387–398
https://doi.org/10.1016/j.ijmecsci.2017.10.025
33 I H Mulyadi, V A Balogun, P T Mativenga. Environmental performance evaluation of different cutting environments when milling H13 tool steel. Journal of Cleaner Production, 2015, 108: 110–120
https://doi.org/10.1016/j.jclepro.2015.07.024
34 Z J Duan, S S Wang, Z H Wang, C H Li, Y H Li, J L Song, J Y Liu, X Liu. Tool wear mechanisms in cold plasma and nano-lubricant multi-energy field coupled micro-milling of Al–Li alloy. Tribology International, 2024, 192: 109337
https://doi.org/10.1016/j.triboint.2024.109337
35 R A Laghari, N He, M Jamil, M K Gupta. Tribological and machining characteristics of milling SiCp/Al MMC composites under sustainable cooling conditions. The International Journal of Advanced Manufacturing Technology, 2023, 128(5–6): 2613–2630
https://doi.org/10.1007/s00170-023-12083-9
36 J G Sun, C H Li, Z M Zhou, B Liu, Y B Zhang, M Yang, T Gao, M Z Liu, X Cui, B K Li, R Z Li, Y S Dambatta, S Sharma. Material removal mechanism and force modeling in ultrasonic vibration-assisted micro-grinding biological bone. Chinese Journal of Mechanical Engineering, 2023, 36(1): 129
https://doi.org/10.1186/s10033-023-00957-8
37 Y Su, Q Lu, T Yu, Z Q Liu, C Y Zhang. Machining and environmental effects of electrostatic atomization lubrication in milling operation. The International Journal of Advanced Manufacturing Technology, 2019, 104(5–8): 2773–2782
https://doi.org/10.1007/s00170-019-04123-0
38 J Q Zhang, B B He, B Zhang. Failure mode change and material damage with varied machining speeds: a review. International Journal of Extreme Manufacturing, 2023, 5: 022003
39 S G Hu, C H Li, Z M Zhou, B Liu, Y B Zhang, M Yang, B K Li, T Gao, M Z Liu, X Cui, X M Wang, W H Xu, Y S Dambatta, R Z Li, S Sharma. Nanoparticle-enhanced coolants in machining: mechanism, application, and prospects. Frontiers of Mechanical Engineering, 2023, 18(4): 53
https://doi.org/10.1007/s11465-023-0769-8
40 da L R R Silva, R S Ruzzi, V C Teles, W F Sales, W L Guesser, A R Machado. Analysis of the coefficient of friction at the workpiece–tool interface in milling of high strength compacted graphite cast irons. Wear, 2019, 426–427: 1646–1657
41 L Zhao, J J Zhang, J G Zhang, H F Dai, A Hartmaier, T Sun. Numerical simulation of materials-oriented ultra-precision diamond cutting: review and outlook. International Journal of Extreme Manufacturing, 2023, 5: 022001
42 M Yang, M Kong, C H Li, Y Z Long, Y B Zhang, S Sharma, R Z Li, T Gao, M Z Liu, X Cui, X M Wang, X Ma, Y Y Yang. Temperature field model in surface grinding: a comparative assessment. International Journal of Extreme Manufacturing, 2023, 5(4): 042011
https://doi.org/10.1088/2631-7990/acf4d4
43 M Q Pham, H S Yoon, V Khare, S H Ahn. Evaluation of ionic liquids as lubricants in micro milling–process capability and sustainability. Journal of Cleaner Production, 2014, 76: 167–173
https://doi.org/10.1016/j.jclepro.2014.04.055
44 G L Zhao, L J Xin, L Li, Y Zhang, N He, H N Hansen. Cutting force model and damage formation mechanism in milling of 70wt% Si/Al composite. Chinese Journal of Aeronautics, 2023, 36(7): 114–128
https://doi.org/10.1016/j.cja.2022.07.018
45 J Q Dang, C G Wang, H H Wang, Q L An, J Wei, B Gao, Z M Liu, M Chen. Deformation behavior and microstructure evolution of 300M ultrahigh strength steel subjected to high strain rate: an analytical approach. Journal of Materials Research and Technology, 2023, 25: 812–831
https://doi.org/10.1016/j.jmrt.2023.05.203
46 C Sun, Y Hong, S C Xiu, L Ma, D W Wang, C W Xu, W Feng. Surface strengthening mechanism of the active grinding carburization. Tribology International, 2023, 185: 108569
https://doi.org/10.1016/j.triboint.2023.108569
47 X M Wang, C H Li, M Yang, Y B Zhang, M Z Liu, T Gao, X Cui, D Z Wang, H J Cao, Y Chen, B Liu. Progress on the physical mechanism of microlubrication processing in nano bio-lubricants. Journal of Mechanical Engineering, 2024, 60(9): 286–322 (in Chinese)
48 X F Bai, J Jiang, C H Li, L Dong, H M Ali, S Sharma. Tribological performance of different concentrations of Al2O3 nanofluids on minimum quantity lubrication milling. Chinese Journal of Mechanical Engineering, 2023, 36(1): 11
https://doi.org/10.1186/s10033-022-00830-0
49 J X Zhang, W Zhang, Z Y Li, F Q Yan, Y H Liu, Y G Zhao. Study on the influence of cutting parameters on specific cutting energy and surface roughness of radial tire mold side plate. Machine Tool and Hydraulic, 2021, 49(14): 36–40 (in Chinese)
50 C LiY C Piao F H ZhangY ZhangY X HuY F Wang. Understand anisotropy dependence of damage evolution and material removal during nanoscratch of MgF2 single crystals. International Journal of Extreme Manufacturing, 2023, 5(1): 015101
51 M Henke, B Lis, T Krystofiak. Evaluation of surface roughness parameters of HDF for finishing under industrial conditions. Materials, 2022, 15(18): 6359
https://doi.org/10.3390/ma15186359
52 J Q Dang, H Zhang, Q L An, W W Ming, M Chen. On the microstructural evolution pattern of 300M steel subjected to surface cryogenic grinding treatment. Journal of Manufacturing Processes, 2021, 68: 169–185
https://doi.org/10.1016/j.jmapro.2021.05.026
53 J Q Dang, H Zhang, Q L An, W W Ming, M Chen. Surface modification of ultrahigh strength 300M steel under supercritical carbon dioxide (scCO2)-assisted grinding process. Journal of Manufacturing Processes, 2021, 61: 1–14
https://doi.org/10.1016/j.jmapro.2020.11.001
54 J Chen, W W Yu, Z Y Zuo, Y G Li, D Chen, Q L An, H W Wang, M Chen. Tribological properties and tool wear in milling of in-situ TiB2/7075 Al composite under various cryogenic MQL conditions. Tribology International, 2021, 160: 107021
https://doi.org/10.1016/j.triboint.2021.107021
55 Q L An, C Y Cai, F Zou, X Liang, M Chen. Tool wear and machined surface characteristics in side milling Ti6Al4V under dry and supercritical CO2 with MQL conditions. Tribology International, 2020, 151: 106511
https://doi.org/10.1016/j.triboint.2020.106511
56 Z R Pan, B Yao, B Q Chen, J S Huang, X F Ma, Q X Lan. Cutting force model of milling titanium alloy with C60 nanofluid minimum quantity lubrication. Journal of Manufacturing Processes, 2023, 105: 295–306
https://doi.org/10.1016/j.jmapro.2023.08.008
57 M Yang, H Ma, J C Hao, Z H Li, R Z Li, Z M Zhou, T Gao, M Z Liu, X Cui, X M Wang, Y B Zhang, Y S Dambatta, Y Z Long, C H Li. Droplet size distribution model of needle electrode electrostatic atomization and milling nickel-based alloy performance evaluation. Journal of Manufacturing Processes, 2024, 119: 682–698
https://doi.org/10.1016/j.jmapro.2024.04.011
58 Y Su, S K Wu, H Jiang. Study on the influence of base fluid type of external fluid on nanofluid coaxial electrostatic atomization cutting. China Mechanical Engineering, 2023, 34(7): 796–802 (in Chinese)
59 Y Su, Z P Chu, L Gong, B Wang, Z Q Liu. Assessment of lubrication property and machining performance of nanofluid composite electrostatic spraying (NCES) using different types of vegetable oils as base fluids of external fluid. Chinese Journal of Mechanical Engineering, 2023, 36(1): 94
https://doi.org/10.1186/s10033-023-00929-y
60 Y Su, X R Hu, D D Zhang, H Jiang, Z Q Liu. Performance evaluation of composite electrostatic spraying (CES) in milling process. The International Journal of Advanced Manufacturing Technology, 2021, 117(1–2): 109–123
https://doi.org/10.1007/s00170-021-07737-5
61 D W Liu, Z L Xu, C H Li, A G Qin, B Liu, Y B Zhang, Y S Dambatta, Q L An. Mathematical model and experimental verification of workpiece surface roughness in face milling. Surface Technology, 2024, 53(4): 125–139 (in Chinese)
62 F Liu, Y Q Shan, Y D Gong, G Q Cai. Cross correlation analysis on surface profile machined with abrasive jet precision finishing with grinding wheel as restraint. Diamond and Abrasive Engineering, 2007, 5: 53–57 (in Chinese)
63 X Li, C M Guan, P Zhao. Influences of milling and grinding on machined surface roughness and fatigue behavior of GH4169 superalloy workpieces. Chinese Journal of Aeronautics, 2018, 31(6): 1399–1405
https://doi.org/10.1016/j.cja.2017.07.013
64 X H Liu. Autocorrelation analysis of aluminum alloy grinding and processing surface. Light Alloy Fabrication Technology, 2010, 38(1): 41–42,59 (in Chinese)
https://doi.org/10.13979/j.1007-7235.2010.01.008
65 M Z Liu, C H Li, Y B Zhang, M Yang, T Gao, X Cui, X M Wang, H N Li, Z Said, R Z Li, S Sharma. Analysis of grain tribology and improved grinding temperature model based on discrete heat source. Tribology International, 2023, 180: 108196
https://doi.org/10.1016/j.triboint.2022.108196
66 J S Wang, F Z Fang, H J An, S Wu, H M Qi, Y X Cai, G Y Guo. Laser machining fundamentals: micro, nano, atomic and close-to-atomic scales. International Journal of Extreme Manufacturing, 2023, 5: 012005
67 S Kieren-Ehses, T Mayer, B Kirsch, J C Aurich. Influence of the parameters of a minimum quantity lubrication system on micro milling process results. The International Journal of Advanced Manufacturing Technology, 2023, 127(11–12): 5279–5292
https://doi.org/10.1007/s00170-023-11333-0
68 W H Huang, J W Yan. Effect of tool geometry on ultraprecision machining of soft-brittle materials: a comprehensive review. International Journal of Extreme Manufacturing, 2023, 5(1): 012003
69 X L Liang, Z Q Liu, B Wang, C J Wang, C F Cheung. Friction behaviors in the metal cutting process: state of the art and future perspectives. International Journal of Extreme Manufacturing, 2023, 5(1): 012002
70 L Fulcheri, V Rohani, F Fabry, N Traisnel. Experimental electrical characterization of a low-current tip–tip arc discharge in helium atmosphere at very high pressure. Plasma Sources Science & Technology, 2010, 19(4): 045010
https://doi.org/10.1088/0963-0252/19/4/045010
71 F F Cai, W Ren, X X Chen. Optimization of high-speed milling parameters of integral impeller based on Taguchi method and variance analysis. Machine Tool and Hydraulics, 2016, 44(2): 4–6,9 (in Chinese)
https://doi.org/10.3969/j.issn.1001-3881.2016.02.002
72 Z Zhou, F Li, H Yang, W Y Gao, L W Miao. Orthogonal experimental study of soil–rock mixtures under the freeze–thaw cycle environment. International Journal of Pavement Engineering, 2021, 22(11): 1376–1388
https://doi.org/10.1080/10298436.2019.1686634
[1] Dongzhou JIA, Keke JIANG, Yanbin ZHANG, Zhenlin LV, Changhe LI. Model for atomization droplet size and energy distribution ratio at the distal end of an electrostatic nozzle[J]. Front. Mech. Eng., 2024, 19(5): 35-.
[2] Xiaojun TAN, Haibing XIAO, Zihong WANG, Wei ZHANG, Zhijuan SUN, Xuyun PENG, Zhongmin LIU, Liang GUO, Qingmao ZHANG. Laser polishing of a high-entropy alloy manufactured by selective laser melting[J]. Front. Mech. Eng., 2024, 19(5): 34-.
[3] Peng LYU, Min LAI, Yifei SONG, Zhifu XUE, Fengzhou FANG. Sub-nanometer finishing of polycrystalline tin by inductively coupled plasma-assisted cutting[J]. Front. Mech. Eng., 2023, 18(3): 35-.
[4] Jiqiang WU, Liqin WANG, Zhen LI, Peng LIU, Chuanwei ZHANG. Thermal analysis of lubricated three-dimensional contact bodies considering interface roughness[J]. Front. Mech. Eng., 2022, 17(2): 16-.
[5] Gang SHEN, Jufan ZHANG, David CULLITON, Ruslan MELENTIEV, Fengzhou FANG. Tribological study on the surface modification of metal-on-polymer bioimplants[J]. Front. Mech. Eng., 2022, 17(2): 26-.
[6] Zequan YAO, Chang FAN, Zhao ZHANG, Dinghua ZHANG, Ming LUO. Position-varying surface roughness prediction method considering compensated acceleration in milling of thin-walled workpiece[J]. Front. Mech. Eng., 2021, 16(4): 855-867.
[7] Mingzheng LIU, Changhe LI, Yanbin ZHANG, Qinglong AN, Min YANG, Teng GAO, Cong MAO, Bo LIU, Huajun CAO, Xuefeng XU, Zafar SAID, Sujan DEBNATH, Muhammad JAMIL, Hafz Muhammad ALI, Shubham SHARMA. Cryogenic minimum quantity lubrication machining: from mechanism to application[J]. Front. Mech. Eng., 2021, 16(4): 649-697.
[8] Zhigang DONG, Qian ZHANG, Haijun LIU, Renke KANG, Shang GAO. Effects of taping on grinding quality of silicon wafers in backgrinding[J]. Front. Mech. Eng., 2021, 16(3): 559-569.
[9] Arun KRISHNAN, Fengzhou FANG. Review on mechanism and process of surface polishing using lasers[J]. Front. Mech. Eng., 2019, 14(3): 299-319.
[10] Rupesh CHALISGAONKAR, Jatinder KUMAR. Optimization of WEDM process of pure titanium with multiple performance characteristics using Taguchi’s DOE approach and utility concept[J]. Front Mech Eng, 2013, 8(2): 201-214.
[11] ZHANG Jianming, ZHANG Weigang, YANG Bing, WANG Yawei. Fluid damping clearance in a control valve of injector[J]. Front. Mech. Eng., 2007, 2(4): 439-441.
[12] LI Xiwen, YANG Shuzi, YANG Mingjin, XIE Shouyong. Cutting Force Model for a Small-diameter Helical Milling Cutter[J]. Front. Mech. Eng., 2007, 2(3): 272-277.
[13] CHEN Hao-sheng, CHEN Da-rong, WANG Jia-dao, LI Yong-jian. Calculated journal bearing lubrication of non-Newtonian medium with surface roughness effects[J]. Front. Mech. Eng., 2006, 1(3): 270-275.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed