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

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.