Multiobjective Optimization Method for Polymer Injection Molding Based on a Genetic Algorithm

Table 10

Fitting results of the warpage using the four regression models.

	R-sq	R-sq (adjustment)	R-sq (prediction)	regression; model
Quadratic	98.18%	91.87%	51.38%	Warpage1
Linear + parabolic	96.40%	94.69%	88.19%	Warpage2
Linear + interaction	94.80%	89.92%	52.50%	Warpage3
Linear	93.02%	91.67%	88.81%	Warpage4

Annotation: the four regression models were followed:
Warpage1 = 1.68272 - 0.03713 A - 0.00171 B - 0.04379 C - 0.01929 D - 0.04304 E + 0.00266A×A - 0.00747B×B - 0.00522 C×C - 0.00609D×D + 0.00553 E×E - 0.00419A×B + 0.00069 A×C + 0.00706A×D - 0.00094 A×E+ 0.00069 B×C + 0.00031B×D + 0.00081B×E + 0.00569 C×D + 0.00594 C×E+ 0.00456 D×E.
Warpage2 = 1.68272 - 0.03713 A - 0.00171 B - 0.04379 C - 0.01929 D - 0.04304 E + 0.00266 A×A - 0.00747 B×B - 0.00522 C×C - 0.00609 D×D + 0.00553 E×E.
Warpage3 = 1.67478 - 0.03713 A - 0.00171 B - 0.04379 C - 0.01929 D - 0.04304 E - 0.00419A×B + 0.00069A×C + 0.00706 A×D - 0.00094 A×E + 0.00069 B×C + 0.00031B×D + 0.00081B×E + 0.00569C×D + 0.00594 C×E + 0.00456 D×E.
Warpage4 = 1.67478 - 0.03713 A - 0.00171 B - 0.04379 C - 0.01929 D - 0.04304 E.