한국정밀공학회지 (Journal of the Korean Society for Precision Engineering)

  • 제22권7호
  • /
  • Pages.177-184
  • /
  • 2005
  • /
  • 1225-9071(pISSN)
  • /
  • 2287-8769(eISSN)
한국정밀공학회 (Korean Society for Precision Engineering)
권호 표지

크리깅을 이용한 전자 오븐 윈도우 부품용 사출금형의 최적설계

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

  • 발행 : 2005.07.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

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.

키워드

참고문헌

  1. Ryu, M. R., Seo, Y. B., Mun, B. J., Park, H. S., 'Shoemoulds Runner Shape Optimization using MoldFlow,' KSPE Spring Conference, 2003
  2. Park, T. W., Jea, D. G., Jung, Y. D., 'Injection mold of Through Plate Type for Recycling,' KSPE, Vol.20, pp.123-129, 2003
  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 https://doi.org/10.1016/0022-1694(94)02590-8
  5. Mardia, K. L. 'Kriging and Splines with Derivative Information,' Boimetrica, Vol. 83, pp. 207-221, 1996 https://doi.org/10.1093/biomet/83.1.207
  6. Deceneiere, A. 'Applicaions of Kriging to Image Sequence Cooling,' Signal Processing; Image Communication, Vol. 13, pp.227-249, 1998 https://doi.org/10.1016/S0923-5965(98)00007-1
  7. 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
  8. 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 https://doi.org/10.1016/S0263-8223(00)00045-3
  9. Georg, Menges Walter, Michaeli and Paul, Mohren, 'How to Make Injection Molds,' Hanser Gardner Publications, Inc. 2001
  10. 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 https://doi.org/10.1214/ss/1177012413
  11. Dubrule, O., 'Two Methods with Different Objections, Splines and Kriging,' Mathematical Geology, Vol. 15, pp.245-257, 1983 https://doi.org/10.1007/BF01036069
  12. Cressie, N., 'Kriging Nonstationary Data,' Journal of the American Statistical Association, Vol.8, pp.625-634, 1986 https://doi.org/10.2307/2288990