Determination of the Optimal Locations for Injection Molding Gates with Higher Order Response Surface Approximations

Abstract:

This paper proposed a gate location optimization scheme to minimize the maximum injection pressure in plastic injection molding. The method utilized a series of higher order response surface approximations (RSA) to model the maximum injection pressure distribution with respect to gate locations, and the global minimum of these response surface models were subsequently sought by a global optimization method based on a multi-start sequential quadratic programming technique. The design points for RSA were evaluated by the finite element method. After a sequence of repetitions of RSA and optimization, the converged minimizer would represent the optimal gate location. A rectangular plate with two segments of different thicknesses was selected to demonstrate the effectiveness of the procedure. The variation of the thicknesses causes the optimal gate location to deviate from the center and induce multiple valleys in the maximum injection pressure distribution, which is ideal for the application of the higher order RSA and a global searching technique.

• Periodical: Applied Mechanics and Materials (Volumes 479-480)
• Pages: 126-130
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.479-480.126
• Online since: December 2013
• Authors: Kun Nan Chen, Wen Der Ueng
• Keywords: Gate Location, Global Optimization, Injection Molding, Response Surface Approximation

References

[1] M. Zhai, C. Shen, An optimization scheme based on flow resistance to locate optimum gate of complex part, Journal of Reinforced Plastics and Composites. 24 (2005) 1559-1566.

DOI: 10.1177/0731684405050389

[2] G.E.P. Box, K.B. Wilson, On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society. B 13 (1951) 1-45.

[3] R.H. Myers, D.C. Montgomery, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, John Wiley & Sons, Inc., New York, (1995).

[4] B. Liu, R.T. Haftka, M.A. Akgun, Two-level composite wing structural optimization using response surfaces, Struct Multidisc Optim. 20 (2000) 89-96.

DOI: 10.1007/s001580050140

[5] R.H. Myers, Response surface methodology – current status and future directions, Journal of Quality Technology. 31 (1999) 30-74.

[6] B. Ozcelik, T. Erzurumlu, Comparison of the warpage optimization in the plastic injection molding using ANOVA, neural network model and genetic algorithm, Journal of Materials Processing Technology. 171 (2006) 437-445.

DOI: 10.1016/j.jmatprotec.2005.04.120

[7] H. Kurtaran, T. Erzurumlu, Efficient warpage optimization of thin shell plastic parts using response surface methodology and genetic algorithm, Int. J. Adv. Manuf. Technol. 27 (2006) 468-472.

DOI: 10.1007/s00170-004-2321-2

[8] J.A. Snyman, L.P. Fatti, A multi-start global minimization algorithm with dynamic search trajectories, Journal of Optimization Theory and Applications. 54 (1987) 121-141.

DOI: 10.1007/bf00940408