Statistical Modeling and Optimization of Variables Affecting Surface Hardness and Corrosion Resistance of 316L Stainless Steel in Ultrasonic Shot Peening Process Using Desirability Approach

Document Type : Research Paper

Authors

1 Faculty of Mechanical Engineering, Shahrood University of Technology, Shahrood, Iran

2 Department of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran

Abstract

Ultrasonic shot peening (USP) has been introduced as a novel method for enhancing the mechanical properties of materials. In this process, spherical shots with certain material, diameter, and quantity are energized with ultrasonic vibrations. These shots impact the surface of the workpiece randomly, creating a layer of compressive residual stresses. This study involved treating cylindrical samples of 316L stainless steel with USP, using various combinations of input parameters (ultrasonic power and peening duration) based on the full factorial design (FFD). Subsequently, the surface hardness and corrosion resistance of the samples were evaluated according to standard procedures. The analysis of variance (ANOVA) results indicated that ultrasonic power significantly affects surface hardness, while both peening duration and ultrasonic power were found to significantly affect corrosion resistance. Furthermore, the coefficient of variation for the models of surface hardness and corrosion resistance was 72.78% and 91.61%, respectively. Given the high signal-to-noise ratios, the regression models are suitable for predicting these response parameters (surface hardness and corrosion resistance). Finally, the optimal combination of the USP input parameters was determined using the desirability approach. The desirability function values, aimed at maximizing surface hardness and corrosion resistance of the steel samples, were 80.2% and 89.3%, respectively.

Keywords

References

[1] Kobayashi, M., Matsui, T., & Murakami, Y. (1998). Mechanism of creation of compressive residual stress by shot peening. International Journal of Fatigue, 20(5), 351-357. https://doi.org/10.1016/S0142-1123(98)00002-4
[2] Farrahi, G. H., Lebrijn, J. L., & Couratin, D. (1995). Effect of shot peening on residual stress and fatigue life of a spring steel. Fatigue & Fracture of Engineering Materials & Structures, 18(2), 211-220. https://doi.org/10.1111/j.1460-2695.1995.tb00156.x
[3] Wang, C., Guo, Z., Zhou, B., Li, B., Fei, S., Deng, H., & Shen, G. (2024). Experimental investigation and numerical study on evolution of surface roughness caused by ultrasonic shot peening of 2024 aluminum alloy sheet. Journal of Materials Research and Technology, 30, 9061-9083. https://doi.org/10.1016/j.jmrt.2024.05.254
[4] Tao, N. R., Sui, M. L., Lu, J., & Lua, K. (1999). Surface nanocrystallization of iron induced by ultrasonic shot peening. Nanostructured Materials, 11(4), 433-440. https://doi.org/10.1016/S0965-9773(99)00324-4
[5] Pandey, V., Chattopadhyay, K., Srinivas, N. S., & Singh, V. (2017). Role of ultrasonic shot peening on low cycle fatigue behavior of 7075 aluminium alloy. International Journal of Fatigue, 103, 426-435. https://doi.org/10.1016/j.ijfatigue.2017.06.033
[6] Mahobia, G. S., Kumar, C. S., & Chattopadhyay, K. (2019). Nanocrystallisation of nickel free high nitrogen austenitic stainless steel through ultrasonic shot peening. Key Engineering Materials, 813, 43-48. https://doi.org/10.4028/www.scientific.net/KEM.813.43
[7] Dong, Z., Wang, F., Qian, D., Yin, F., Wang, H., Wang, X., Hu, S., & Chi, J. (2022). Enhanced wear resistance of the ultrastrong ultrasonic shot-peened M50 bearing steel with gradient nanograins. Metals, 12(3), 424. https://doi.org/10.3390/met12030424
[8] Kumar, C. S., Mahobia, G. S., Podder, A., Kumar, S., Agrawal, R. K., Chattopadhyay, K., & Singh, V. (2019). Role of ultrasonic shot peening on microstructure, hardness and corrosion resistance of nitrogen stabilised stainless steel without nickel. Materials Research Express, 6(9), 096578. https://doi.org/10.1088/2053-1591/ab2dbe
[9] Agrawal, R. K., Pandey, V., Barhanpurkar-Naik, A., Wani, M. R., Chattopadhyay, K., & Singh, V. (2020). Effect of ultrasonic shot peening duration on microstructure, corrosion behavior and cell response of cp-Ti. Ultrasonics, 104, 106110. https://doi.org/10.1016/j.ultras.2020.106110
[10] Zhang, Q., Duan, B., Zhang, Z., Wang, J., & Si, C. (2021). Effect of ultrasonic shot peening on microstructure evolution and corrosion resistance of selective laser melted Ti–6Al–4V alloy. Journal of Materials Research and Technology, 11, 1090-1099. https://doi.org/10.1016/j.jmrt.2021.01.091
[11] Han, M., Du, J., Chen, Y., Sun, Q., & Hu, K. (2024). Influence of ultrasonic shot peening on the microstructure and corrosion behavior of AZ80M magnesium alloy. Journal of Alloys and Compounds, 980, 173633. https://doi.org/10.1016/j.jallcom.2024.173633
[12] Song, R. B., Xiang, J. Y., & Hou, D. P. (2011). Characteristics of mechanical properties and microstructure for 316L austenitic stainless steel. Journal of Iron and Steel Research International, 18(11), 53-59. https://doi.org/10.1016/S1006-706X(11)60117-9
[13] MatWeb. (2025, March 7). MatWeb: Online Materials Information Resource. https://www.matweb.com
[14] Alavi, F., & Jahan, M. P. (2017). Optimization of process parameters in micro-EDM of Ti-6Al-4V based on full factorial design. The International Journal of Advanced Manufacturing Technology, 92, 167-187. https://doi.org/10.1007/s00170-017-0103-x
[15] ASM Handbook Committee. (1990). Properties and selection: irons, steels, and high-performance alloys, ASM International. ISBN: 978-0-87170-377-4
[16] Ivium Technologies. (2025). Ivium Technologies software [Software]. https://www.ivium.com
[17] Stat-Ease, Inc. (2025). Design Expert [Software]. https://www.statease.com
[18] Jarahi, F., Vahdati, M., & Abedini, R. (2024). Modeling and optimization of shear strength of the welded joint produced by ultrasonic welding of copper wire to aluminum sheet. Transactions of the Indian Institute of Metals, 77(9), 2499-2508. https://doi.org/10.1007/s12666-024-03336-6
[19] Isapour Rudy, M., Vahdati, M., & Mirnia, M. J. (2023). Statistical analysis and optimization of variables affecting the end diameter of AISI 304 steel tube produced by flaring process. Amirkabir Journal of Mechanical Engineering, 54(12), 2861-2876. https://doi.org/10.22060/mej.2022.21622.7479
[20] Vahdati, M. (2020). Statistical analysis and optimization of parameters affecting the hardness of butt joint cross-section of Al7075 produced by FSW and SFSW using RSM and desirability approach. Journal of Solid and Fluid Mechanics, 10(4), 165-180. https://doi.org/10.22044/jsfm.2020.9476.3136 
[21] Mohmmadi Jazi, H., Vahdati, M., & Mahdavi, A. (2024). Modeling and optimization of variables affecting tensile properties of printed PP/Cu composite samples using LDM process. Iranian Journal of Manufacturing Engineering, 11(8), 10-19. https://doi.org/10.22034/ijme.2024.470528.1989
Iranian Journal of Materials Forming
Volume 12, Issue 1
January 2025
Pages 28-36

Files

Share

How to cite

Statistics