## 3 Results and Discussion
### Statistical Analysis
The residual error accounts for 4.05% of the variation, reflecting the reliability of the model. The R-squared value (R\({}^{2}\) = 95.95%) and adjusted R-squared value (R\({}^{2}\)(adj) = 83.81%) further confirm the model's accuracy in capturing the relationship between the factors and compressive strength. In both cases, the F-values indicate the significance of the factors. Compaction pressure had the highest F-values (25.48 for microhardness and 16.90 for compressive strength), confirming its dominant influence. However, the \(p\)-values suggest statistical significance only for compaction pressure in microhardness (\(p\) = 0.038), while the contributions of sintering temperature and time were not statistically significant (\(p\) > 0.05). Similarly, for compressive strength, none of the factors are statistically significant at the 5% level (\(p\) > 0.05), though compaction pressure approaches significance (\(p\) = 0.056). These results emphasize the critical role of compaction pressure while highlighting opportunities to further refine sintering conditions for enhanced material performance. The graphical interpretation of the results from Table 6 was illustrated in Figures 6 and 7, which presents the main effect plots for the signal-to-noise (SN) ratios of microhardness and compressive strength. The graphs depict the influence of each control factor, i.e., compaction pressure (A), sintering temperature (B), and sintering time (C) on the response variables. In the plots, if the line corresponding to a controlling factor was nearly horizontal, it indicates that the factor had a negligible effect on the response variable. Conversely, a steeply sloping line signifies a significant influence, as the response variable changes considerably with variations in that control factor. Therefore, the steepness of the slopesin the plots enables the identification of the most influential factors. From the analysis, the optimal combination of control factor levels was determined to be A3:B3:C2, corresponding to the highest compaction pressure (350 MPa), the highest sintering temperature (600 \({}^{\circ}\)C), and a medium sintering time (60 min). This combination yields the maximum values for both microhardness and compressive strength. The high compaction pressure ensures superior particle bonding and densification, the elevated sintering temperature promotes efficient grain growth and porosity reduction, and the medium sintering time allows sufficient diffusion without causing excessive grain coarsening. Further analysis of the factors reveals the following: Factor A (compaction pressure) shows that higher levels of this factor contribute to more stable and improved values for both microhardness and compressive strength. This factor plays a significant role in reducing variation and noise in the process, leading to more stable and precise results in both parameters. Factor B (sintering temperature) had a nonlinear impact: the middle  
Figure 6: Main effects plot for the signal-to-noise ratio for microhardness of composite at various process parameters of powder metallurgy. The annotation for A, B, and C is depicted in Table 4.  
Figure 7: Main effects plot for the signal-to-noise ratio for compressive strength of composite at various process parameters of powder metallurgy. The annotation for A, B, and C is depicted in Table 4.  
level causes variations in both parameters, leading to fluctuations in S/N ratios. However, higher levels of factor B improve the stability of the process, making it more controlled and resulting in better values for both microhardness and compressive strength. This explains the trend observed in the plots--the middle level introduces instability, while higher levels stabilize the results. Factor C (sintering time) shows that the second level was optimal for achieving stable and precise values of both microhardness and compressive strength. At this level, the process was optimized for minimal variation and noise.