2012 Volume 53 Issue 9 Pages 1685-1688
Correcting and quickly predicting the shrink mold shape in the sport shoe industry for direct injection-expanded foam molding manufacturing procedures are critical. Traditional methods rely on the engineer to guess the initial shrink mold shape when manufacturing the actual shrink mold and shoe sole product. The artificial experience is then used to compare the original large 3D model with the shoe sole product to modify the shrink mold, requiring numerous iterations to complete. In this study, we designed a series of rectangular specimens varying with z-thickness, and measured the density in the middle location of these specimens and transferred them into an expansion ratio. Furthermore, we performed a heat transfer simulation to determine the temperature–time curve in these locations and correlated the expansion ratio with the curve. We then used the heat expansion finite element method to simulate the expansion behavior. Finally, we used the actual shoe sole to verify our algorithm; with the precision meeting the shoe sole requirement. Therefore, this algorithm can reduce the number of iterations.