## 3 Results and Discussion
### Statistical Analysis  
The results for microhardness and compressive strength, along with their corresponding signal-to-noise (SN) ratios, are presented in Table 6. Regardless of the type of quality loss function applied, the transformation of experimental results into SN ratios allows for a consistent interpretation signifying that a higher SN ratio provides better performance. These experimental outcomes were further analyzed using an analysis of variance (ANOVA) to determine the effects of the control factors, i.e., compaction pressure, sintering temperature, and sintering time on the microhardness and compressive strength of the material. Additionally, ANOVA assessed the interactions between these processing parameters. The analysis was conducted at a significant level of 5%, equivalent to a 95% confidence level. The results of the ANOVA are summarized in Tables 7 and 8. Table 7, specifically, presents the response table for SN ratios, which ranks the control factors based on their influence on microhardness and compressive strength. The ranking was determined using the delta value, which reflects the range of SN ratio variations caused by each factor. The outcomes revealed that the compaction pressure exerts the greatest influence on microhardness, followed by sintering temperature. However, sintering time had the least influence on microhardness. A similar trend was observed for compressive strength, where compaction pressure was the dominant factor, followed by sintering temperature and sintering time. Figure 5: (**a**) Compressive strength and (**b**) microhardness of composite at different levels with variable process parameters of powder metallurgy approach. The percentage contribution analysis highlights the influence of individual control factors on both microhardness and compressive strength. For microhardness, compaction pressure was identified as the most significant factor, contributing 72.99% to the observed variations. This indicates that compaction pressure plays a dominant role in determining the microhardness of the material as it directly affects the densification and bonding of powder particles. Sintering temperature was the second most influential factor, contributing 22.01%, as it governs grain growth and diffusion, which were critical for enhancing material hardness. Sintering time, however, had a relatively minor influence on microhardness, \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Sample**} & \multirow{2}{*}{**Microhardness**} & **Compressive** & **S/N for** & **S/N for** & **Prediction for** & **Prediction for** \\  & & **(Hv)** & **Strength** & **Microhard-** & **Compressive** & **Microhard-** & **Compressive** \\  & & **(MPa)** & **ness (dB)** & **Strength (dB)** & **ness (dB)** & **Strength (dB)** \\ \hline S1 & 75.5 & 390 & 37.5589 & 51.8213 & 37.7800 & 51.9243 \\ S2 & 80.5 & 405 & 38.1159 & 52.1491 & 37.9656 & 52.0835 \\ S3 & 87.1 & 419 & 38.8004 & 52.4443 & 38.7296 & 52.4069 \\ S4 & 88.9 & 425.2 & 38.9780 & 52.5719 & 38.9073 & 52.5344 \\ S5 & 82.3 & 414.3 & 38.3080 & 52.3463 & 38.5290 & 52.4493 \\ S6 & 95.4 & 435.7 & 39.5910 & 52.7838 & 39.4407 & 52.7181 \\ S7 & 99.8 & 438.9 & 39.9826 & 52.8473 & 39.8323 & 52.7817 \\ S8 & 96.3 & 430.5 & 39.6725 & 52.6795 & 39.6018 & 52.6420 \\ S9 & 108.5 & 452.2 & 40.7086 & 53.1066 & 40.9296 & 53.2097 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Experimental results using L9 orthogonal array.