Browse > Article

Optimization of an Electron Microwave Oven Window Injection Mold Using Kriging Based Approximation Model  

Ryu M. R. (동아대학교 대학원)
Lee K. H. (도앙대학교 기계공학과)
Kim Y. H. (동아대학교 신소재공학과)
Park H. S. (동아대학교 기계공학과)
Publication Information
Abstract
Recently, the engineering designer of injection mould has become more and more dependent on the CAE. In the design factors of injection mould, the shrinkage rate should be considered as one of the important performances to produce the reliable products. therefore the shrinkage rate can be mostly calculated by the MoldFlow and Pro-engineering. in the design process. However it is not easy to predict the shrinkage rate of a plastic injection mold in its design process because the analysis can take minutes to hours, the high computational costs of performing the analysis limit their use in design optimization. In this study, the surrogate models, DACE model, based on the Kriging in order to optimize the shrinkage rate of electric microwave oven window is used in lieu of the original models, facilitating design optimization.
Keywords
Optimization; Injection mold; Kriging; DACE(Design and analysis of computer experiments); Electron microwave oven window; MoldFlow;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Choi, D.S. and Im, Y.T., 'Prediction of shrinkage and warpage in consideration of residual stress in integrated simulation of infection molding,' Composite Structures, Vol. 47, pp. 655-665, 1999   DOI   ScienceOn
2 Deceneiere, A. 'Applicaions of Kriging to Image Sequence Cooling,' Signal Processing; Image Communication, Vol. 13, pp.227-249, 1998   DOI   ScienceOn
3 Chung, H. S. and Alons,. J. J., 'Comparison of Approximation Models with Merit Functions for Design Optimization,' American Institute of Aeronautics and Astronautics, 8th AIAA/SUAF/NASA/ISSMO Symposium on Multidisciplinary Optimization, Hampton, March 13-16, VA, SIAM, pp.315-329, 1995
4 Bacchi, B. and Kottegoda, N. T., 'Identification and Calibration of Spatial Correlation Patterns of Rain Fall,' Journal of Hydrology, Vol.165, pp. 311-348, 1995   DOI
5 Mardia, K. L. 'Kriging and Splines with Derivative Information,' Boimetrica, Vol. 83, pp. 207-221, 1996   DOI   ScienceOn
6 Park, T. W., Jea, D. G., Jung, Y. D., 'Injection mold of Through Plate Type for Recycling,' KSPE, Vol.20, pp.123-129, 2003   과학기술학회마을
7 Georg, Menges Walter, Michaeli and Paul, Mohren, 'How to Make Injection Molds,' Hanser Gardner Publications, Inc. 2001
8 Ryu, M. R., Seo, Y. B., Mun, B. J., Park, H. S., 'Shoemoulds Runner Shape Optimization using MoldFlow,' KSPE Spring Conference, 2003
9 Dubrule, O., 'Two Methods with Different Objections, Splines and Kriging,' Mathematical Geology, Vol. 15, pp.245-257, 1983   DOI
10 Cressie, N., 'Kriging Nonstationary Data,' Journal of the American Statistical Association, Vol.8, pp.625-634, 1986   DOI
11 Sacks, J., Welch, W. J., Mitchell, T. J. and Wynn, H. P., ' Design and Analysis of Computer Experiments,' Statistical Science, Vol. 4, No.4, pp. 409-435. 1989   DOI
12 Simpson, T. 'Comparison fo Response Surface and Kriging Models for Multidisciplinary Design Optimization,' American Institute of Aeronautics and Astronautics, ALLAA-98-47755, pp. 381-391, 1998