Hybrid ANN-GA Optimization of Burnishing Parameters for Improving Surface Finish and Hardness in 6061-T6 Aluminum Alloy
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Abstract
Improving surface finish and hardness in 6061-T6 aluminum is crucial for aerospace and automotive applications. This study presents a hybrid Artificial Neural Network–Genetic Algorithm (ANN-GA) model to optimize burnishing parameters—spindle speed, feed rate, and pressure. A full factorial design was used to analyze their effects on surface roughness and hardness. Experiments identified optimal conditions: 500 rpm, 0.3 m/min, and 2.0 GPa, achieving 0.372 µm roughness and 140.30 HV hardness. The ANN-GA model exhibited high predictive accuracy (R² = 0.9513, RMSE = 0.22), and proposed an alternative optimum at 799.02 rpm, 0.31 m/min, and 1.48 GPa. The findings confirm the effectiveness of the ANN-GA in capturing nonlinear interactions and reducing experimental trials. This integrated approach offers a robust tool for optimizing burnishing processes, particularly for high-performance components requiring superior surface integrity.
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
References
El-Axir MH. An investigation into the ball burnishing of aluminium alloy 6061-T6. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. 2007;221(12):1733-1742.
Chomienne V, Valiorgue F, Rech J, Verdu C. Influence of ball burnishing on residual stress profile of a 15-5PH stainless steel. CIRP Journal of Manufacturing Science and Technology. 2016;13:90-96.
Cao C, Zhu J, Tanaka T, Shiou FJ, Sawada S, Yoshioka H. Ball burnishing of Mg alloy using a newly developed burnishing tool with on-machine force control. International Journal of Automation Technology. 2019;13(5):619-630.
Zhou ZY, Zheng QY, Ding C, Peng GJ, Piao ZY. Research on the promotion mechanism of surface burnishing process by two-dimensional ultrasonic vibration. Journal of Materials Research and Technology. 2021;13:1068-1082.
Pookamnerd Y, Thosa P, Charonerat S, Prasomthong S. Development of mechanical property prediction model and optimization for dissimilar aluminum alloy joints with the friction stir welding (FSW) process. EUREKA: Physics and Engineering. 2023;3:112-128.
Randjelovic S, Tadic B, Todorovic PM, Vukelic D, Miloradovic D, Radenkovic M, Tsiafis C. Modelling of the ball burnishing process with a high-stiffness tool. International Journal of Advanced Manufacturing Technology. 2015;81(9-12):1509-1518.
Travieso-Rodríguez JA, Gomez-Gras G, Dessein G, Carrillo F, Alexis J, Jorba-Peiró J, Aubazac N. Effects of a ball-burnishing process assisted by vibrations in G10380 steel specimens. International Journal of Advanced Manufacturing Technology. 2015;81(9-12):1757-1765.
Gómez-Gras G, Travieso-Rodríguez JA, González-Rojas HA, Nápoles-Alberro A, Carrillo FJ, Dessein G. Study of a ball-burnishing vibration-assisted process. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. 2015;229(1):172-177.
Jerez-Mesa R, Landon Y, Travieso-Rodríguez JA, Dessein G, Lluma-Fuentes J, Wagner V. Topological surface integrity modification of AISI 1038 alloy after vibration-assisted ball burnishing. Surface and Coatings Technology. 2018;349:364-377.
Teimouri R, Amini S, Bami AB. Evaluation of optimized surface properties and residual stress in ultrasonic assisted ball burnishing of AA6061-T6. Measurement. 2018;116:129-139.
Teimouri R, Liu Z. An analytical prediction model for residual stress distribution and plastic deformation depth in ultrasonic-assisted single ball burnishing process. International Journal of Advanced Manufacturing Technology. 2020;111(1-2):127-147.
Kanovic Z, Vukelic D, Simunovic K, Prica M, Saric T, Tadic B, Simunovic G. The modelling of surface roughness after the ball burnishing process with a high-stiffness tool by using regression analysis, artificial neural networks, and support vector regression. Metals. 2022;12(2):320.
Labuda W, Wieczorska A, Charchalis A. The influence of the burnishing process on the change in surface hardness, selected surface roughness parameters and the material ratio of the welded joint of aluminum tubes. Materials. 2024;17(1):43.
Cagan SC. Surface quality and environmental impact analysis of ball burnishing on AL8090 aluminum-lithium alloy. Materials. 2025;18(6):1252.
Pimenov DY, Kiran M, Khanna N, Pintaude G, Vasco MC, Da Silva LRR, Giasin K. Review of improvement of machinability and surface integrity in machining on aluminum alloys. International Journal of Advanced Manufacturing Technology. 2023;129(11-12):4743-4759.
Prasomthong S, Kaewchaloon A, Charonerat S. Optimization of friction stir spot welding between aluminium alloys and titanium alloy by the Taguchi method. SNRU Journal of Science and Technology. 2022;14(3):245169.
Cagan SC, Leksycki K. Analysis of surface roughness after ball burnishing of pure titanium under environmentally friendly conditions. Applied Sciences. 2025;15(4):1746.
Kovács ZF, Viharos ZJ, Kodácsy J. Improvements of surface tribological properties by magnetic assisted ball burnishing. Surface and Coatings Technology. 2022;437:128317.
Dzierwa A, Markopoulos AP. Influence of ball-burnishing process on surface topography parameters and tribological properties of hardened steel. Machines. 2019;7(1):11.
Hassan AM. The effects of ball- and roller-burnishing on the surface roughness and hardness of some non-ferrous metals. Journal of Materials Processing Technology. 1997;72(3):385-391.
Hassan AM, Maqableh AM. The effects of initial burnishing parameters on non-ferrous components. Journal of Materials Processing Technology. 2000;102(1-3):115-121.
Ramesh S, Kudva SA, Anne G, Manne B, Arya S. Optimization of ball-burnishing process parameters on surface roughness, micro hardness of Mg-Zn-Ca alloy and investigation of corrosion behavior. Materials Research Express. 2019;6(10):106508.
Swirad S. Changes in areal surface textures due to ball burnishing. Materials. 2023;16(17):5904.
Barahate V, Govande AR, Tiwari G, Sunil BR, Dumpala R. Parameter optimization during single roller burnishing of AA6061-T6 alloy by design of experiments. Materials Today: Proceedings. 2021;50:1967-1970.
Nestler A, Schubert A. Effect of machining parameters on surface properties in slide diamond burnishing of aluminium matrix composites. Materials Today: Proceedings. 2015;2:S156-S161.
Maximov JT, Anchev AP, Duncheva GV, Ganev N, Selimov KF. Influence of the process parameters on the surface roughness, micro-hardness, and residual stresses in slide burnishing of high-strength aluminum alloys. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 2016;39(8):3067-3078.
Yao H, Qiu S, Lv Y, Wei S, Li A, Long Z, Wu W, Shen X. Indoor particulate matter transfer in CNC machining workshop and the influence of ventilation strategies—A case study. Sustainability. 2023;15(7):6227.
Wang M, Liu H, Gu S, Wu Y, Wei Z, Wang J, Xie L, Lu Y, Wang J. Effects of rotational speed on microstructure, exothermic reactions and mechanical properties of Al/Ni energetic structural materials prepared by hot pressing and friction stir processing. Journal of Materials Research and Technology. 2024;29:2597-2607.
Sachin B, Rao CM, Naik GM, Puneet NP. Influence of slide burnishing process on the surface characteristics of precipitation hardenable steel. SN Applied Sciences. 2021;3(2):1-9.
Elsheikh AH, Basem A, Saba A, Faqeha H, Alsaati AA, Maghfuri AM, Abd-Elaziem W, ElAshmawy AA, Ma N. A review on sustainable machining: technological advancements, health and safety considerations, and related environmental impacts. Results in Engineering. 2024;24:103042.
Luo Q, Kitchen M. Microhardness, indentation size effect and real hardness of plastically deformed austenitic Hadfield steel. Materials. 2023;16(3):1117.
Xue Z, Lai M, Xu F, Fang F. Influence factors and prediction model of surface roughness in single-point diamond turning of polycrystalline soft metal. Journal of Materials Processing Technology. 2023;324:118256.
Thorat S, Thakur A. Optimization of burnishing parameters by Taguchi based GRA method of AA 6061 aluminum alloy. Materials Today: Proceedings. 2018;5(2):7394-7403.
