[en] Milling of hardened carbon steels like SKD11 generates complex physical interactions that can affect tool wear, surface quality, and process stability. This study presents a multiphysics experimental approach aimed at better understanding these physical interactions. The first objective is to monitor key features in real-time, including cutting force, vibration, cutting temperature, and sound signal, during the milling process. An integrated setup involving infrared thermography and thermocouples, a piezoelectric dynamometer, sound and vibration emission sensors was used, and data were collected under two different cutting conditions. The second measurement objective is to inspect the end-of-process features such as surface quality, tool wear, and chip formation. Tool wear was measured by different methods at the end of the cut in order to show the strong correlation between cutting forces, temperature, sound signal, and vibration patterns of the machining process. The results of this study are focused mainly on the design approach rather than on detailed numerical details. The tooth-passing frequency analyzed from the cutting-force signal was correlated with the sound signal. Cutting strategies affect the surface quality under the same cutting conditions. This work provides guidance on eliminating redundant measurements for multiphysics investigations of the milling process, and accounts for all features, in contrast to previous experimental studies. Besides those findings, there are some issues that need to be improved, such as repositioning the thermocouples, elongating the cutting path to inspect the tool state and surface quality; more cutting conditions should also be applied.
Disciplines :
Mechanical engineering
Author, co-author :
Nguyen Duc Thinh ; Université de Liège - ULiège > Urban and Environmental Engineering ; Université de Liège - ULiège > Faculté des Sciences Appliquées > Doct. sc. ingé/ tech. (archi. gén. civ. géol.) ; Université de Liège - ULiège > Faculté des Sciences Appliquées > Form. doct. sc. ingé. & techn. (archi., gén. civ. - paysage) ; Vietnamese-German University > Faculty of Engineering ; University of Technology of Tarbes, Toulouse University > Laboratoire Genie de Production
Chi, Nguyen Quoc; Ho Chi Minh City University of Technology,Faculty of Mechanical Engineering,Ho Chi Minh City,Vietnam
Xuan, Tran Van; Thu Dau Mot University,Institute of Engineering and Technologies,Ho Chi Minh City,Vietnam
Huy, Phung Thanh; Ho Chi Minh City University of Technology,Faculty of Mechanical Engineering,Ho Chi Minh City,Vietnam
Anh, Nguyen Duy; Ho Chi Minh City University of Technology,Faculty of Mechanical Engineering,Ho Chi Minh City,Vietnam
Keller, Clement; University of Technology of Tarbes, Toulouse University Tarbes,Laboratoire Genie de Production,France
Wagner, Vincent; University of Technology of Tarbes, Toulouse University Tarbes,Laboratoire Genie de Production,France
Duchene, Laurent ; Université de Liège - ULiège > Département ArGEnCo > Analyse multi-échelles dans le domaine des matériaux et structures du génie civil
Language :
English
Title :
A Multiphysics Approach Based on Using Thermal, Mechanical, and Acoustic Measurements in Milling of SKD11 Carbon Steel
Publication date :
12 November 2025
Event name :
28th International Conference on Mechatronics Technology (ICMT)
Event date :
12 - 15 / Nov. / 2025
By request :
Yes
Audience :
International
Main work title :
2025 28th International Conference on Mechatronics Technology (ICMT)
Main work alternative title :
[en] ICMT 2025 Proceedings
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), Piscataway, New Jersey, Unknown/unspecified
Core-Tech4.0: A data-driven multiphysics modeling and digital twin-based platform to optimize the production in small and medium-sized mechanical manufacturing enterprises
Mac, T.-B.; Dinh, V.-C.; Banh, T.-L.; Nguyen, D.-T. Cutting Force Model for Thermal-Assisted Machining of Tool Steel Based on the Taguchi Method. Metals 2018, 8, 992. https://doi.org/10.3390/met8120992.
S. A. Nipu, R. Karim, A. Rahma, M. Moon, I. A. Choudhury, J. B. Omar, M. S. Khushbu, ‘Turning SKD11 Hardened Steel: An Experimental Study of Surface Roughness and Material Removal Rate Using Taguchi Method’, Adv. Mater. Sci. Eng., vol. 2023, pp. 1–13, Dec. 2023, doi: 10.1155/2023/6421918.
A. Abdeltawab, Z. Xi, and Z. Longjia, ‘Tool wear classification based on maximal overlap discrete wavelet transform and hybrid deep learning model’, Int. J. Adv. Manuf. Technol., vol. 130, no. 5–6, pp. 2381–2406, Jan. 2024, doi: 10.1007/s00170-023-12797-w.
Q. Yao, B. Wu, M. Luo, and D. Zhang, ‘On-line cutting force coefficients identification for bull-end milling process with vibration’, Measurement, vol. 125, pp. 243–253, Sep. 2018, doi: 10.1016/j.measurement.2018.04.084.
Y. J. Lee and H.-S. Yoon, ‘Modeling of cutting tool life with power consumption using Taylor’s equation’, J. Mech. Sci. Technol., vol. 37, no. 6, pp. 3077–3085, Jun. 2023, doi: 10.1007/s12206-023-0531-5.
X.-W. Liu, K. Cheng, A. P. Longstaff, M. H. Widiyarto, and D. Ford, ‘Improved dynamic cutting force model in ball-end milling. Part I: theoretical modelling and experimental calibration’, Int. J. Adv. Manuf. Technol., vol. 26, no. 5–6, pp. 457–465, Sep. 2005, doi: 10.1007/s00170-003-2014-2.
X. Zhang, J. Zhang, B. Pang, and W. Zhao, ‘An accurate prediction method of cutting forces in 5-axis flank milling of sculptured surface’, Int. J. Mach. Tools Manuf., vol. 104, pp. 26–36, May 2016, doi: 10.1016/j.ijmachtools.2015.12.003.
R. Zhou, ‘Analytical model of workpiece surface temperature prediction in 4-axis milling process’, Int. J. Adv. Manuf. Technol., vol. 111, no. 7–8, pp. 2155–2162, Dec. 2020, doi: 10.1007/s00170-020-06255-0.
W. Akhtar and I. Lazoglu, ‘A novel analytical algorithm for prediction of workpiece temperature in end milling’, CIRP Ann., vol. 71, no. 1, pp. 57–60, 2022, doi: 10.1016/j.cirp.2022.03.039.
Y. Feng, L. Zheng, M. Wang, B. Wang, J. Hou, and T. Yuan, ‘Research on cutting temperature of work-piece in milling process based on WPSO’, Int. J. Adv. Manuf. Technol., vol. 79, no. 1–4, pp. 427–435, Jul. 2015, doi: 10.1007/s00170-015-6808-9.
Y. Peng, Q. Song, R. Wang, X. Yang, Z. Liu, and Z. Liu, ‘A tool wear condition monitoring method for non-specific sensing signals’, Int. J. Mech. Sci., vol. 263, p. 108769, Feb. 2024, doi: 10.1016/j.ijmecsci.2023.108769.
M. Janota, P. Kolář, J. Falta, and T. Kozlok, ‘Calibration Method for In-Process Identification of Tangential Specific Cutting Force in Milling’, Machines, vol. 10, no. 11, p. 1095, Nov. 2022, doi: 10.3390/machines10111095.
Q. An, L. Fu, and H. Zhang, ‘Multidimensional Force Sensor Dynamic Compensation Based on Multistrategy Improved Sparrow Search Algorithm’, IEEE Sens. J., vol. 24, no. 3, pp. 3046–3057, Feb. 2024, doi: 10.1109/JSEN.2023.3334214.
A. A. Sultan and A. C. Okafor, ‘Effects of geometric parameters of wavy-edge bull-nose helical end-mill on cutting force prediction in end-milling of Inconel 718 under MQL cooling strategy’, J. Manuf. Process., vol. 23, pp. 102–114, Aug. 2016, doi: 10.1016/j.jmapro.2016.05.015.
W. Baohai, C. Di, H. Xiaodong, Z. Dinghua, and T. Kai, ‘Cutting tool temperature prediction method using analytical model for end milling’, Chin. J. Aeronaut., vol. 29, no. 6, pp. 1788–1794, Dec. 2016, doi: 10.1016/j.cja.2016.03.011.
L. Liu, D. Qu, J. Wang, J. Zhang, H. Cao, and X. Dong, ‘Thermal-field analytical modeling of machined surface layer in high-speed-dry milling UD-CF/PEEK considering thermal anisotropy and nonlinear thermal conductivity’, Compos. Part Appl. Sci. Manuf., vol. 176, p. 107864, Jan. 2024, doi: 10.1016/j.compositesa.2023.107864.
Ş. Şirin, M. Sarıkaya, Ç. V. Yıldırım, and T. Kıvak, ‘Machinability performance of nickel alloy X-750 with SiAlON ceramic cutting tool under dry, MQL and hBN mixed nanofluid-MQL’, Tribol. Int., vol. 153, p. 106673, Jan. 2021, doi: 10.1016/j.triboint.2020.106673.
B. Peng, T. Bergs, D. Schraknepper, T. Smigielski, and F. Klocke, ‘Development and validation of a new friction model for cutting processes’, Int. J. Adv. Manuf. Technol., vol. 107, no. 11–12, pp. 4357–4369, Apr. 2020, doi: 10.1007/s00170-019-04709-8.
Y. Chen, J. Lu, Q. Deng, J. Ma, and X. Liao, ‘Modeling study of milling force considering tool runout at different types of radial cutting depth’, J. Manuf. Process., vol. 76, pp. 486–503, Apr. 2022, doi: 10.1016/j.jmapro.2022.02.037.
A. P. Kulkarni, G. G. Joshi, A. Karekar, and V. G. Sargade, ‘Investigation on cutting temperature and cutting force in turning AISI 304 austenitic stainless steel using AlTiCrN coated carbide insert’, Int. J. Mach. Mach. Mater., vol. 15, no. 3/4, p. 147, 2014, doi: 10.1504/IJMMM.2014.060546.
J. Shinozuka, K. Utsumi, A. Basti, T. Obikawa, ‘Measurement of Temperature Distribution on the Tool Rake Face with a Cutting Tool with Built-in Thin Film Thermocouples’, Trans. Jpn. Soc. Mech. Eng. C, 2006, doi: 10.1299/kikaic.72.1687.
Y. Chen, J. Lu, Q. Deng, J. Ma, and X. Liao, ‘Modeling study of milling force considering tool runout at different types of radial cutting depth’, J. Manuf. Process., vol. 76, pp. 486–503, Apr. 2022, doi: 10.1016/j.jmapro.2022.02.037.