## 3 Results and Discussion
### Statistical Analysis
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**No.** & **Source** & **Mean of Squares** & \(p\)**-Value** \\ \hline
1 & Model & 1,463,290 & 0 \\
2 & **Linear parameters** & **4,473,581** & **0** \\
3 & Flow rate & 1,209,310 & 0.039 \\
4 & Melt temperature & 1,369,223 & 0.049 \\
5 & Holding pressure & 460,154 & 0.027 \\
6 & Runner diameter & 16,845,635 & 0 \\
7 & **Squares** & **533,923** & **0.008** \\
8 & Flow rate \(\times\) Flow rate & 6013 & 0.815 \\
9 & Melt temperature \(\times\) Melt temperature & 53,785 & 0.486 \\
10 & Holding pressure \(\times\) Holding pressure & 527 & 0.945 \\
11 & Runner diameter \(\times\) Runner diameter & 1,474,471 & 0.002 \\
**12** & **Interactions** & **76,008** & **0.641** \\
13 & Melt temperature \(\times\) Flow rate & 4789 & 0.834 \\
14 & Melt temperature \(\times\) Holding pressure & 9658 & 0.767 \\
15 & Melt temperature \(\times\) Runner diameter & 50,917 & 0.498 \\
16 & Flow rate \(\times\) Holding pressure & 126 & 0.973 \\
17 & Flow rate \(\times\) Runner diameter & 175,496 & 0.216 \\
18 & Holding pressure \(\times\) Runner diameter & 215,063 & 0.173 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Results of the second ANOVA (CCD). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**No.** & **Source** & **Mean of Squares** & \(p\)**-Value** \\ \hline
**1** & Model & 3,424,612 & 0.011 \\
**2** & Flow rate & 4,978,362 & 0.011 \\
**3** & Melt temperature & 19,348,900 & 0.001 \\
**4** & Mold temperature & 870,044 & 0.138 \\
**5** & Holding pressure & 6,600,269 & 0.007 \\
**6** & Runner diameter & 32,488,905 & 0.000 \\
**7** & Gate diameter & 458,198 & 0.250 \\
**8** & Gate angle & 1946 & 0.934 \\
**9** & Included angle & 96,108 & 0.571 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: ANOVA results of the screening step. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**No.** & **Flow Rate** & **Melt Temperature** & **Holding Pressure** & **Runner Diameter** \\
**(cm\({}^{3}\)/s)** & **(\({}^{\circ}\)C)** & **(MPa)** & **(mm)** \\ \hline
1 & 12 & 185.2 & 54.6 & 6.4 \\
2 & 14 & 187 & 59 & 7 \\
3 & 19 & 191 & 70 & 8.5 \\
4 & 24 & 196 & 81 & 10 \\
5 & 26 & 197.8 & 85.4 & 10.6 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The levels of CCD. Figure 8 illustrates the manner of the impact of each parameter on the results. According to the \(p\)-value obtained from the effects of ANOVA, the runner diameter has the most significant impact on the area of the blush defect. After that, the parameters of holding pressure, flow rate, and melt temperature have the highest impact on the defect area, respectively. Utilizing ANOVA, a regression equation to predict the area of the defect has been worked out using all input parameters presented in Equation (24). \[Area=-12367+(25.7\times A)-(25.4\times B)-(13.82\times C)+(3898\times D)-(193.2 \times D\times D) \tag{24}\]  
where \(A\) indicates the flow rate, \(B\) the melt temperature, \(C\) the holding pressure, and \(D\) represents the runner diameter. The standardized residual and histogram plot shown in Figure 9 reveal the accuracy of Equation (24). As can be seen from the Versus Order plot, the predicted data are in general equally scattered around the zero line. Additionally, the histogram plot in this figure shows that the amount of data with a standard residual equal to or near zero is much higher than the amount of data with higher residuals. Thus, it can be concluded that the defect area amounts predicted by the regression model are in good agreement with the FEA results. Figure 8: The effect of: (**a**) flow rate, (**b**) melt temperature, (**c**) holding pressure, and (**d**) runner diameter on the defect area. Figure 9: Standardized residual and histogram graph.