OBRABOTKAMETALLOV Vol. 26 No. 3 2024 technology Ta b l e 5 ANOVA for F-values and % contribution of different parameters Elements Surface roughness (Ra) Microhardness (HV) Roundness error (Re) F-Values % contribution F-Values % contri-bution F-Values % contribution Cutting speed (V) (m/ min) 0.3382 0.07 15.8251 16.91 40.2758 25.89 Feed (f) (mm/rev) 6.3512 1.23 0.6335 0.68 0.6619 0.43 Number of passes (N) 63.1738 12.25 1.5631 1.67 24.0589 15.47 Interaction V×f 12.7024 2.46 7.4668 7.98 1.4796 0.95 Interaction V×N 81.8517 15.88 5.8132 6.21 28.7154 18.46 Interaction f×N 21.7218 4.21 7.4668 7.98 5.7595 3.70 V 2 103.2749 20.03 29.0338 31.02 0.9816 0.63 f 2 158.5728 30.76 11.8708 12.68 50.5574 32.50 N 2 67.5406 13.10 13.9156 14.87 3.0571 1.97 Total F-value 515.5274 100 93.5887 100 155.5472 100 * Significant elements are shown as underlined and contributions in bold-case. As for microhardness, cutting speed and elements in an interaction effects, the higher order effects and elements can be considered significant depending on the feed rate and the number of passes. It can be seen that the microhardness is mostly affected by the higher cutting speed (almost 31.02 %), followed by the cutting speed (almost 16.91 %) and the higher number of passes and feed rate (almost 14.87 % and 12.68 %, respectively), while the feed rate and the number of passes have almost no effect (Table 5). The roundness error is significantly affected by the higher order of feed rate (almost 32.5 %), followed by the cutting speed (almost 25.89 %), and the combined effect of the cutting speed and the number of passes (almost 18.46 %) and the number of passes (almost 15.47 %). It can be seen that the number of passes significantly affects the surface roughness, and the cutting speed significantly affects the microhardness and roundness error. It can be seen from Fig. 2 and Table 5 that the tolerances are inherently in conflict with the process parameters. And to obtain positive results, multiobjective optimization of these conflicting parameters is required. In the present work, the roller burnishing process parameters are optimized using the desirability function approach to obtain the minimum surface roughness, maximum microhardness, and minimum roundness error. In this approach, each response variable is transformed into a desirability function, and the optimization of several response variables is transformed into the optimization of a single desirability function [20–22]. The process variables and the range of response functions are given in Table 6. The minimum and maximum limits of surface roughness, microhardness and roundness error are referred to from experimental observations as depicted in Table 6. Each response is transformed into its respective desirability function by using a one-way transformation [16]. In the present study, the multiobjective optimization of roller burnishing was performed using optimization module of the DesignExpert® software. For the optimization study, around 100 data points having different combinations of process parameters were considered within the range shown in Table 6. For each level of independent parameters, the desirability for surface roughness, desirability for microhardness, and desirability for roundness error were calculated. Then, a single desirability function, desirability for minimum surface roughness, maximum microhardness, and minimum roundness error was calculated. Table 7 shows the optimized process parameters for minimum surface roughness, maximum microhardness, and minimum
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