Analysis of Recent Research and Innovations in Vibration-Assisted Hybrid Machining Processes
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Hybrid machining processes (HMP) have been developed to double the benefits of advanced or conventional machining processes by combining them. The challenges that occur in machining of intricate shapes and features, micromachining, and machining of very hard and soft materials can be overcome by HMPs. Assistance from external sources like vibrations, abrasives, and magnetic fields can facilitate material removal and enhance machining efficiency. This paper analyses some important recent research and innovations carried out in the domain of vibration-assisted HMPs and presents them to enrich the knowledge of scholars and researchers to establish the field further. The major focus of the article is to highlight the role of vibration assistance in facilitating both conventional and modern machining domains specifically covering electrochemical machining, electric discharge machining, turning, and their variants. Industry 4.0 and Sustainability-oriented innovations in advancing HMPs, involving leveraging digital technologies to enhance productivity while minimizing environmental impact, have also been featured
Bachir, E., & Bejjani, R. (2023). An experimental and FEM study on ultrasonic-assisted turning of titanium alloy. Machining Science and Technology, 27(4), 350–379. https://doi.org/10.1080/10910344.2023.2231066
Bui, V. D., Martin, A., Berger, T., & Bourouga, K. (2020). Analysis of the hybrid electrochemical and ultrasonic-assisted finishing process in precision machining of Ti6Al4V alloy. Precision Engineering, 66, 258–267. https://doi.org/10.1016/j.precisioneng.2020.07.005
Chenxue, W., Sasaki, T., & Hirao, A. (2022). Observation of bubble behavior in EDM with ultrasonic vibration. Procedia CIRP, 113, 267–272. https://doi.org/10.1016/j.procir.2022.09.157
Chu, X., Zeng, X., Zhuang, W., Zhou, W., Quan, X., & Fu, T. (2019). Vibration assisted high-speed wire electric discharge machining for machining surface microgrooves. Journal of Manufacturing Processes, 4, 418–426. https://doi.org/10.1016/j.jmapro.2019.05.026
Deswal, N., & Kant, R. (2022). FE analysis of ultrasonic vibration assisted turning of magnesium AZ31B alloy. Materials Today Proceedings, 62(14), 7473–7479.
Deswal, N., & Kant, R. (2023). Radial direction ultrasonic-vibration and laser assisted turning of Al3003 alloy. Materials Research Express, 10, 044004.
Deswal, N., & Kant, R. (2024). Effect of compressed air cooling on tool wear during ultrasonic-vibration-laser assisted turning of aluminium alloy. Journal of Vibration Engineering and Technology, 12, 5527–5544. https://doi.org/10.1007/s42417-023-01198-8
Dixit, U. S., Pandey, P. M., & Verma, G. C. (2019). Ultrasonic-assisted machining processes: A review. International Journal of Mechatronics and Manufacturing Systems, 12(3/4), 227–254. https://doi.org/10.1504/IJMMS.2019.10022977
El-Hofy, H. (2019). Vibration-assisted electrochemical machining: A review. International Journal of Advanced Manufacturing Technology, 105, 579–593. https://doi.org/10.1007/s00170-019-04209-9
Fang, L. (2022). Design and experimental study on double-excitation three-dimensional ultrasonic elliptical vibration cutting device (Dissertation). Northeastern University, Boston, MA.
Gamidi, K., Tlija, M., & Abu Qudeiri, J. (2024). Surface integrity, tool wear, and chip morphology studies in spot cooled vibration assisted turning of Ti6Al4V alloy. Journal of Materials Engineering and Performance. https://doi.org/10.1007/s11665-024-09736-5
Grover, S., Mangal, S. K., & Singh, S. (2023). Micro-machining and process optimization of ultrasonic assisted rotary µ-electrochemical discharge machining using TOPSIS method. Materials Today Proceedings. In Press. https://doi.org/10.1016/j.matpr.2023.01.001
Grzesik, W., & Ruszaj, A. (2021). Hybrid manufacturing processes: Physical fundamentals, modelling and rational applications. Springer.
Guo, C., Luo, L., Liang, Z., Li, H., Wang, X., & Xu, B. (2024). Comparative study of ultrasonic vibration-assisted die-sinking micro-electric discharge machining on polycrystalline diamond and titanium. Micromachines, 15, 434. https://doi.org/10.3390/mi15040434
He, Y., Zhou, Z., Zou, P., Gao, X., & Ehmann, K. F. (2019). Study of ultrasonic vibration–assisted thread turning of Inconel 718 superalloy. Advances in Mechanical Engineering, 11(10). https://doi.org/10.1177/1687814019883772
Huang, W.-T., Tu, Z.-Y., & Chou, J.-H. (2020). Performance optimization research on ultrasonic vibration assisted turning. In Proceedings of the 2020 International Conference on System Science and Engineering (ICSSE) (pp. 1–4). Kagawa, Japan. https://doi.org/10.1109/ICSSE50014.2020.9219292
Ji, M., Muthuramalingam, T., Saravanakumar, D., Karmiris-Obratański, P., Karkalos, N. E., & Zhang, W. (2023). Predicting depth of cut in vibration-assisted EDM cutting on titanium alloy using adaptive neuro-fuzzy inference system. Measurement, 219, 113245. https://doi.org/10.1016/j.measurement.2023.113245
Jiang, X., Li, Y., Li, D., & Xu, Z. (2023). Influence of machining gap on both sides of blade in vibration-assisted pulsed electrochemical machining. International Journal of Electrochemical Science, 18, 100125. https://doi.org/10.20964/2023.01.13
Kasiviswanathan, S., Gnanasekaran, S., Thangamuthu, M., & Rakkiyannan, J. (2024). Machine-learning- and Internet-of-Things-driven techniques for monitoring tool wear in machining processes: A comprehensive review. Journal of Sensor and Actuator Networks, 13(53). https://doi.org/10.3390/jsan13050053
Kien, H. T., Khoa, D. Q., Tuan, P. H., Khoan, M., & Ba, D. V. (2021). Theoretical and experimental study of vibration-assisted turning. In B. T., Long, Kim, Y. H., Ishizaki, K., Toan, N. D., Parinov, I. A. & Vu, N. P. (Eds.), Proceedings of the 2nd Annual International Conference on Materials, Machining Methods, and Sustainable Development (MMMS2020), 61–68. Springer. https://doi.org/10.1007/978-3-030-69610-8_5
Laghari, R. A., & Mekid, S. (2023). Comprehensive approach toward IIoT based condition monitoring of machining processes. Measurement, 217, 113004.
Lauwers, B., Klocke, F., Klink, A., Tekkaya, A. E., Neugebauer, R., & McIntosh, D. (2014). Hybrid processes in manufacturing. CIRP Annals, 63(2), 561–583. https://doi.org/10.1016/j.cirp.2014.03.014
Lei, J., Shen, H., Wu, H., Pan, W., Wu, X., & Zhao, C. (2024). Ultrasonic vibration-assisted electric discharge machining of enclosed microgrooves with laminated electrodes. Journal of Materials Research and Technology, 30, 9521–9530. https://doi.org/10.1016/j.jmrt.2024.06.035
Li, Z., Tang, J., & Bai, J. (2020). A novel micro-EDM method to improve microhole machining performances using ultrasonic circular vibration (UCV) electrode. International Journal of Mechanical Sciences, 175, 105574. https://doi.org/10.1016/j.ijmecsci.2020.105574
Li, Z., Tang, J., Li, Y., & Bai, J. (2022). Investigation on surface integrity in novel micro-EDM with two-dimensional ultrasonic circular vibration (UCV) electrode. Journal of Manufacturing Processes, 76, 828–840. https://doi.org/10.1016/j.jmapro.2022.03.004
Liu, G., Wang, J., Zheng, J., Ji, M., & Wang, X. (2023). An experimental study on ultrasonic vibration-assisted turning of aluminum alloy 6061 with vegetable oil-based nanofluid minimum quantity lubrication. Lubricants, 11(11), 470. https://doi.org/10.3390/lubricants11110470
Liu, Z., Lang, Z. Q., Gui, Y., Zhu, Y. P., & Laalej, H. (2024). Digital twin-based anomaly detection for real-time tool condition monitoring in machining. Journal of Manufacturing Systems, 75, 163–173. https://doi.org/10.1016/j.jmsy.2024.06.004
Mollik, S., Saleh, T., Bin, N. K. A., & Mohamed Sultan, M. A. (2022). A machine learning-based classification model to identify the effectiveness of vibration for lEDM. Alexandria Engineering Journal, 61, 6979–6989. https://doi.org/10.1016/j.aej.2021.12.048
Mondal, A., Sahoo, S., Roy, P., & Mitra, S. (2020). Vibration assisted electro-discharge machining of Ti6Al4V alloy using conical shaped tool. International Scientific Journal of Machining, Technology, and Materials, 14(2), 70–74.
Muhammad, R. A. (2021). A fuzzy logic model for the analysis of ultrasonic vibration assisted turning and conventional turning of Ti-based alloy. Materials, 14(21), 6572. https://doi.org/10.3390/ma14216572
Nguyen, H. P., Ngo, N. V., & Nguyen, Q. T. (2021). Optimizing process parameters in EDM using low frequency vibration for material removal rate and surface roughness. Journal of King Saud University - Engineering Sciences, 33, 284–291. https://doi.org/10.1016/j.jksues.2020.05.002
Pandey, G. K., Kumar, S., & Yadav, S. (2020). Multi-response optimization of vibration assisted electric discharge drilling process using PCA based GRA approach. Materials Today Proceedings, 22, 2906–2915. https://doi.org/10.1016/j.matpr.2020.03.424
Pandey, S., & Shrivastava, P. K. (2020). Vibration-assisted electric arc machining of 10% B4C/Al metal matrix composite. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 0, 1–15. https://doi.org/10.1177/0954406219890375
Pravin, T., Subramanian, M., & Ranjith, R. (2022). Clarifying the phenomenon of ultrasonic assisted electric discharge machining. Journal of the Indian Chemical Society, 99, 100705. https://doi.org/10.1016/j.jics.2022.100705
Raza, S., Nadda, R., & Nirala, C. K. (2023). Sensors-based discharge data acquisition and response measurement in ultrasonic assisted micro-EDM drilling. Measurement: Sensors, 29, 100858. https://doi.org/10.1016/j.measen.2023.100858
Ren, M., Zhu, D., Chen, L., & Zuo, H. (2024). Simulation and experimental studies on surface quality of vibration-assisted ECM. Materials and Manufacturing Processes, 39(12), 1673–1688. https://doi.org/10.1080/10426914.2024.2362616
Sabyrov, N., Jahan, M. P., Bilal, A., & Perveen, A. (2019). Ultrasonic vibration assisted electro-discharge machining (EDM)—An overview. Materials, 12(3), 522. https://doi.org/10.3390/ma12030522
Shen, Z.-Y., & Tsui, H.-P. (2021). An investigation of ultrasonic-assisted electrochemical machining of micro-hole array. Processes, 9(9), 1615. https://doi.org/10.3390/pr9091615
Shi, W., Zheng, J., & Zhu, L. (2024). Development of a low-frequency vibration–assisted turning device for nickel-based alloys. International Journal of Advanced Manufacturing Technology, 133, 321–333. https://doi.org/10.1007/s00170-024-13705-6
Shitara, T., Fujita, K., & Yan, J. (2020). Direct observation of discharging phenomena in vibration-assisted micro-electric discharge machining. International Journal of Advanced Manufacturing Technology, 108, 1125–1138. https://doi.org/10.1007/s00170-019-04877-7
Singh, R., & Davim, J. P. (2021). Non-conventional hybrid machining processes: Theory and practice. CRC Press.
Singh, T., Dvivedi, A., Shanu, A., & Dixit, P. (2021). Experimental investigations of energy channelization behavior in ultrasonic assisted electrochemical discharge machining. Journal of Materials Processing Technology, 293, 117084. https://doi.org/10.1016/j.jmatprotec.2021.117084
Tan, R., Zhao, X., Guo, S., Zou, X., He, Y., Geng, Y., Hu, Z., & Sun, T. (2020). Sustainable production of dry-ultra-precision machining of Ti–6Al–4V alloy using PCD tool under ultrasonic elliptical vibration-assisted cutting. Journal of Cleaner Production, 248. https://doi.org/10.1016/j.jclepro.2019.119254
Wang, C., Liu, Y., Wang, T., Xu, H., & Wang, K. (2024). A green and precision compound machining method for glass micro components—Ultrasonic assisted electrochemical discharge grinding with multi-hole tube electrode. CIRP Journal of Manufacturing Science and Technology, 52, 129–148. https://doi.org/10.1016/j.cirpj.2023.01.003
Wang, M., Liu, W., Chen, X., Xu, X., & Ma, Y. (2020). Machining performance study in radial ultrasonic-assisted rolling electrochemical micromachining. Procedia CIRP, 93, 793–797. https://doi.org/10.1016/j.procir.2020.04.117
Wang, M., Shang, Y., Liu, C., & Wang, J. (2022). 3D multiphysic simulations of energy field and material process in radial ultrasonic rolling electrochemical micromachining. Chinese Journal of Aeronautics, 35(3), 494–508. https://doi.org/10.1016/j.cja.2021.04.020
Wang, M., Zhang, R., Shang, Y., Zheng, J., Wang, X., & Xu, X. (2023). Micro-milling microstructures in air-shielding ultrasonic-assisted electrochemical machining. Journal of Manufacturing Processes, 97, 171–184. https://doi.org/10.1016/j.jompro.2023.06.027
Wang, Y., Landis, M., Ekaputra, C., Vita, V., & Guo, P. (2024). Solid-state production of uniform metal powders for additive manufacturing by ultrasonic vibration machining. Additive Manufacturing, 81, 103993. https://doi.org/10.1016/j.addma.2024.103993
Wei, S., Zou, P., Duan, J., & Ehmann, K. (2023). Surface integrity in 3D ultrasonic vibration-assisted turning driven by two actuators. Machining Science and Technology, 27(1), 20–41. https://doi.org/10.1080/10910344.2023.2194959
Xu, M., Wei, R., Li, C., & Ko, T. J. (2023). High-frequency electric discharge assisted milling of Inconel 718 under copper-beryllium bundle electrodes. Journal of Manufacturing Processes, 85, 1116–1132. https://doi.org/10.1016/j.jmapro.2022.12.026
Xu, Y., Zhang, J., & Zhang, Q. (2023). Theoretical and experimental investigations of tool wear in ultrasonic vibration-assisted turning of 304 austenitic stainless steel. International Journal of Advanced Manufacturing Technology, 127, 3157–3181. https://doi.org/10.1007/s00170-023-11686-6
Ye, Z., Chen, X., Li, G., Saxena, K. K., Arshad, M. H., & Zhang, Y. (2024). Enhancement mechanism of electrochemical drilling square-small holes with workpiece vibration. Journal of Manufacturing Processes, 113, 197–214. https://doi.org/10.1016/j.jompro.2024.03.027
Yin, Z., Zhang, P., Zhou, P., Zhang, K., Sun, Q., Zhan, Q., & Li, H. (2023). A novel EDM method using longitudinal-torsional ultrasonic vibration (LTV) electrodes to improve machining performance for micro-holes. Journal of Manufacturing Processes, 102, 231–243. https://doi.org/10.1016/j.jmapro.2023.07.023
Zhang, J., Xiang Toh A. Y., Wang H., Lu W. F., & Fuh J. Y. H. (2019). Vibration-assisted conformal polishing of additively manufactured structured surface. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 233(12), 4154–4164. https://doi.org/10.1177/0954406218811359
Zhao, M., Xue, B., Li, B., Zhu, J., & Song, W. (2024). Ensemble learning with support vector machines algorithm for surface roughness prediction in longitudinal vibratory ultrasound-assisted grinding. Precision Engineering, 88, 382–400. https://doi.org/10.1016/j.precisioneng.2024.02.018
Zhu, X., Liu, Y., Zhang, J., Wang, K., & Kong, H. (2020). Ultrasonic-assisted electrochemical drill-grinding of small holes with high-quality. Journal of Advanced Research, 23, 151–161. https://doi.org/10.1016/j.jare.2019.10.002.
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