Investigation of hardness behavior in aluminum matrix composites reinforced with coconut shell ash and red mud using Taguchi analysis

OBRABOTKAMETALLOV MATERIAL SCIENCE Vol. 26 No. 3 2024 Ta b l e 4 ANOVA for Brinell hardness Source Degree of variance DF Adjusted value of within-group variability (error variance) Adj SS Adjusted variance value Adj MS F-Value P-Value Contribution % Red mud (%) 2 205.446 102.723 65.54 0.000 48.80 CSA (%) 2 43.744 21.872 13.96 0.002 10.41 Load (kN) 2 96.652 48.326 30.83 0.000 23.01 Red Mud (%)* CSA (%) 4 16.548 4.137 2.64 0.113 3.94 Red Mud (%)* Load (kN) 4 40.826 10.206 6.51 0.012 9.73 CSA (%)* Load (kN) 4 4.641 1.160 0.74 0.590 1.15 Error 8 12.539 1.567 2.29 Total 26 420.396 *Standard deviation S = 1.2519; R2 = 97.02 %; adjusted R2 = 90.31 %. 5.0 2.5 0.0 -2.5 -5.0 99 95 90 80 70 60 50 40 30 20 1 0 5 1 Residual Percent Normal Probability Plot (response is HB) Fig. 3. Normal probability plot for residual on hardness of Hybrid Al composites 95 % probability level. Equation 1 shows the regression of hardness and in Table 1 shows the predicted value based on Equation 1 and it is found that the error of the predicted value compared with the experimental value is only 4 %, so this regression equation can be used for further analysis [22–23]. Brinell Hardness = 21.78 + 0.883 Red Mud + 0.397 CSA + 0.4562 Load (1) The normal probability plot is drawn for 95 % confidence level and the straight line shows the regression equation line (Figure 3). Using this residual value, it is shown that all hardness deviations are very close to the regression line, out of 27 data, about 4 falls outside the optimal residual value. Therefore, this hybrid compositional combination can be considered suitable for further hardness design analysis.

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