Modeling and Optimization of Ultrasonic Vibration-Assisted Machining Devices: A Review

Ali Radhwan; Ziad Al Sarraf

doi:10.71229/fvj49t54

Authors

Ali Radhwan Yousif Department of Mechanical Engineering, University of Mosul, Mosul, Iraq.
Ziad Shakeeb Al Sarraf Department of Mechanical Engineering, University of Mosul, Mosul, Iraq.

DOI:

https://doi.org/10.71229/fvj49t54

Keywords:

Acoustic horn, Sonotrode, Finite element analysis (FEA), Ultrasonic vibration assisted machining (UVAM), Harmonic response

Abstract

It is currently becoming popularly accepted that ultrasonic vibration-assisted machining (UVAM) represents a promising option for machining difficult-to-machine materials like titanium alloys, advanced ceramics, and fiber-reinforced composites. The problems associated with these materials include high cutting forces, tool wear, and poor surface integrity. This is because ultrasonic vibration-assisted machining entails the application of high frequency and low amplitude vibrations on the tool or workpiece through the acoustic horn which acts as the main medium that transfers vibrational energy generated by the piezoelectric transducer to the cutting area.

This research will summarize 34 papers which were published between 2000 and 2025 on the topic of UVAM simulation and optimization. Some of the aspects that will be considered include the use of Webster's horn equation and other mathematical modeling approaches in determining the ideal horn design and also the use of finite element analysis (FEA) in ANSYS Workbench in terms of modal analysis, harmonic analysis, and stress analysis. In addition, some of the advanced optimization techniques such as Response Surface Methodology, Genetic Algorithm, and Artificial Neural Network will also be discussed.

Some of the applications that will be covered include the manufacturing industry, biomedical engineering, food processing, welding, and additive manufacturing among others. There will be simulative results that indicate significant reductions in cutting forces and improvement in surface roughness compared to conventional machining processes. Some of the reports about reduction in cutting forces are between approximately 20% and 50% while for surface roughness, there is up to 4 times improvement compared to traditional machining. However, thermal drifts and alignment issues remain problems to contend with hence future work must focus on multi-physics simulations.

References

[1] Luo, H., Wang, Y., Guo, J., Huang, Y., Dong, Z., Kang, R., & Sun, J. (2025). Optimization design and analysis of single-sided blade for ultrasonic cutting of Nomex honeycomb core. Mechanics of Advanced Materials and Structures. https://doi.org/10.1080/15376494.2025.2476455

[2] El-Asfoury, M. S., Baraya, M., El Shrief, E., Abdelgawad, K., Sultan, M., & Abass, A. (2024). AI-based prediction of ultrasonic vibration-assisted milling performance. Sensors, 24(17), 5509. https://doi.org/10.3390/s24175509

[3] Zhang, M., Li, Y., & Wang, X. (2024). Simulation and experimental research on the longitudinal-torsional composite ultrasonic vibration cutting. Applied Sciences, 14(10), 4056. https://doi.org/10.3390/app14104056

[4] Thoe, T. B., Aspinwall, D. K., & Wise, M. L. H. (1998). Review on ultrasonic machining. International Journal of Machine Tools and Manufacture, 38(4), 239–255. https://doi.org/10.1016/S0890-6955(97)00036-9

[5] Mughal, K. H., Qureshi, M. A. M., Wasim, A., & Mufti, M. A. (2024). Rotary ultrasonic assisted machining of aramid fiber-reinforced polymer composite: A numerical and experimental investigation. The International Journal of Advanced Manufacturing Technology, 130, 3201–3218. https://doi.org/10.1007/s00170-024-12345-x

[6] Satpute, V., Gunda, S., Bhatt, A., & Bhatt, B. (2024). A comprehensive experimental investigation into vibration-assisted machining (VAM) techniques for monocrystalline silicon. Journal of Manufacturing Processes, 112, 91–108. https://doi.org/10.1016/j.jmapro.2024.01.052

[7] Ahmad, S., Hanif, M. A., Baig, M. Z., & Mufti, R. A. (2024). Harmonic excitation response of standard ultrasonic horns: A comparative FEA study. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 46(3), 127. https://doi.org/10.1007/s40430-024-04893-3

[8] Hahn, M., Cho, Y., & Kim, S. (2021). Optimal design and experimental verification of ultrasonic cutting horn for ceramic composite material. Machines, 9(4), 80. https://doi.org/10.3390/machines9040080

[9] Amin, S. G., Ahmed, M. H. M., & Youssef, H. A. (1995). Computer-aided design of acoustic horns for ultrasonic machining using finite-element analysis. Journal of Materials Processing Technology, 55(3–4), 254–260. https://doi.org/10.1016/0924-0136(95)02015-2

[10] Yang, J. (2005). An introduction to the theory of piezoelectricity. Springer.

[11] Patel, L. K., Singh, A. K., & Kumar, R. (2020). Design, analysis and comparison of different acoustic horns for ultrasonic machining. Materials Today: Proceedings, 28(3), 2031–2037. https://doi.org/10.1016/j.matpr.2020.01.412

[12] He, T., Ye, X. Q., & Zhao, Y. (2014). Optimization design for ultrasonic horn with large amplitude based on genetic algorithm. Journal of Applied Mathematics, 2014, 1–8. https://doi.org/10.1155/2014/710564

[13] Lucas, M., MacBeath, A., McCulloch, E., & Cardoni, A. (2006). A finite element model for ultrasonic cutting. Ultrasonics, 44(Suppl. 1), e503–e509. https://doi.org/10.1016/j.ultras.2006.05.115

[14] Kinsler, L. E., Frey, A. R., Coppens, A. B., & Sanders, J. V. (2000). Fundamentals of acoustics (4th ed.). John Wiley & Sons.

[15] Webster, A. G. (1919). Acoustical impedance, and the theory of horns and of the phonograph. Proceedings of the National Academy of Sciences, 5(7), 275–282. https://doi.org/10.1073/pnas.5.7.275

[16] Bathe, K. J. (2014). Finite element procedures (2nd ed.). K. J. Bathe.

[17] ANSYS Inc. (2024). ANSYS Mechanical APDL theory reference (Release 2024 R2). ANSYS Inc.

[18] Goldberg, D. E. (1989). Genetic algorithms in search, optimization, and machine learning. Addison-Wesley.

[19] Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2016). Response surface methodology: Process and product optimization using designed experiments (4th ed.). John Wiley & Sons.

[20] Deb, K. (2001). Multi-objective optimization using evolutionary algorithms. John Wiley & Sons.

[21] Ashby, M. F. (2017). Materials selection in mechanical design (5th ed.). Butterworth-Heinemann.

[22] Zheng, L., Chen, W., & Huo, D. (2020). Review of vibration devices for vibration-assisted machining. The International Journal of Advanced Manufacturing Technology, 108(5), 1631–1651. https://doi.org/10.1007/s00170-020-05483-8

[23] Brehl, D. E., & Dow, T. A. (2008). Review of vibration-assisted machining. Precision Engineering, 32(3), 153–172. https://doi.org/10.1016/j.precisioneng.2007.08.003

[24] Kumar, S., Wu, C. S., Padhy, G. K., & Ding, W. (2017). Application of ultrasonic vibrations in welding and metal processing: A status review. Journal of Manufacturing Processes, 26, 295–322. https://doi.org/10.1016/j.jmapro.2017.02.027

[25] Sinn, G., Zettl, B., Mayer, H., & Stanzl-Tschegg, S. (2005). Ultrasonic-assisted cutting of wood. Journal of Materials Processing Technology, 170(1–2), 42–49. https://doi.org/10.1016/j.jmatprotec.2005.04.076

[26] Nath, C., & Rahman, M. (2008). Effect of machining parameters in ultrasonic vibration cutting. International Journal of Machine Tools and Manufacture, 48(9), 965–974. https://doi.org/10.1016/j.ijmachtools.2008.01.013

[27] Alam, K., Mitrofanov, A. V., & Silberschmidt, V. V. (2011). Experimental investigations of forces and torque in conventional and ultrasonically-assisted drilling of cortical bone. Medical Engineering & Physics, 33(2), 234–239. https://doi.org/10.1016/j.medengphy.2010.10.003

[28] Zhong, Z. W., & Lin, G. (2006). Ultrasonic assisted turning of an aluminium-based metal matrix composite reinforced with SiC particles. The International Journal of Advanced Manufacturing Technology, 27(11–12), 1077–1081. https://doi.org/10.1007/s00170-004-2320-3

[29] Shen, X. H., Zhang, J., Xing, D. X., & Zhao, Y. (2012). A study of surface roughness variation in ultrasonic vibration-assisted milling. The International Journal of Advanced Manufacturing Technology, 58(5–8), 553–561. https://doi.org/10.1007/s00170-011-3399-y

[30] Liang, Z., Wang, X., Wu, Y., Xie, L., Jiao, L., & Zhao, W. (2013). Experimental study on brittle-ductile transition in elliptical ultrasonic assisted grinding (EUAG) of monocrystal sapphire using single diamond abrasive grain. International Journal of Machine Tools and Manufacture, 71, 41–51. https://doi.org/10.1016/j.ijmachtools.2013.04.004

[31] Liu, J., Zhang, D., Qin, L., & Yan, L. (2012). Feasibility study of the rotary ultrasonic elliptical machining of carbon fiber reinforced plastics (CFRP). International Journal of Machine Tools and Manufacture, 53(1), 141–150. https://doi.org/10.1016/j.ijmachtools.2011.10.007

[32] Zahn, S., Schneider, Y., Scharfe, D., & Rohm, H. (2005). Ultrasonic cutting of foods—Effect of excitation magnitude and cutting velocity on the cutting work. Ultrasonics Sonochemistry, 12(4), 329–334. https://doi.org/10.1016/j.ultsonch.2004.03.009

[33] Ter Haar, G. (2016). HIFU tissue ablation: Concept and devices. Advances in Experimental Medicine and Biology, 880, 3–20. https://doi.org/10.1007/978-3-319-22536-4_1

[34] Friel, R. J., & Harris, R. A. (2013). Ultrasonic additive manufacturing—A hybrid production process for novel functional products. Procedia CIRP, 6, 35–40. https://doi.org/10.1016/j.procir.2013.03.004