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Table 6 ANOVA results for the first-order regression model
significantly estimates the shrinkage. The P value indicates
the significance of process parameters on the shrinkage. If the P values are less than 0.05 (i.e., a = 0.05 or 95% confi- dence), the process parameters in the regression model are significant. As can be clearly seen in Table 5, Tmelt, Itime, and Ctime are statistically the most significant process parameters for the shrinkage. The other process parameters (Tmold and Pinj) are not significant because their P value is bigger than
0.05. Table 6 reveals the results of the ANOVA analysis
showing that the process parameters on the shrinkage are sta- tistically significant. The F value of 98.72 in Table 6 implies that the first-order regression model is significant. The bold value in Table 5 and 7 shows whether the process parameters are important or not.
The second-order regression model, in terms of coded values of process parameters, can be found as below:
Source DF SSE MSE F P
Regression 5 5.3364 1.0673 98.72 0.000
Residual error 21 0.2270 0.0108
Total 26 5.5634
Table 7 The results of the second-order regression model
Predictor Coefficient SE coefficient T P
I2 0.02506 0.04224 0.59 0.559
Table 5 The results of the first-order regression model
Predictor Coefficient SE coefficient T P
S = 0.1035 R-Sq(pred) = 93.90%
PRESS = 0.339428 R-Sq = 95.9%
R-Sq(adj) = 94.9%
Constant 1.0120 0.6120 1.65 0.113
Tmold 0.001267 0.001225 1.03 0.313 Table 8 ANOVA results for the second-order regression
Tmelt 0.037461 0.002451 15.29 0.000 model
Pinj —0.00030 0.001225 —0.24 0.809
Itime —0.38861