Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
권호 표지

A Study on Manufacturing of Precision Injection Mold Using Neural Network

신경회로망을 이용한 정밀 사출금형의 제작에 관한 연구

  • 이상찬 (목포대학교 기계시스템전공)
  • Published : 2005.05.01
Download PDF
⟨ Previous Next ⟩

Abstract

To predict the shrinkage of molded parts using numerical simulations, the mathematical model should be simplified to overcome the difficulties of formulation due to non-linearity of problems. So it is hard to predict the shrinkage exactly because of the simplification. In the present work, the neural network is used to predict the shrinkage which can implement nonlinear models very well. Comparison between the results of neural network and that of the commercial analysis software, ABAQUS, shows that the result of the neural network is in better agreement with that of the experiments.

Keywords

References

  1. Kamal, M. and Kenig, S., 'The Injection Molding of Thermoplastics Part I: Theoretical Model,' Polym. Eng. and Sci., Vol. 12, pp. 294, 1972 https://doi.org/10.1002/pen.760120408
  2. Richardson, S., 'Hele Shaw Flow with a Free Boundary produced by the Injection of Fluid into a Narrow Channel,' J. of Fluid Mech., Vol. 56, pp. 609, 1972 https://doi.org/10.1017/S0022112072002551
  3. White, J., 'Fluid Mechanical Analysis of Injection Mold Filling,' Polym. Eng. and Sci., Vol. 15, pp. 44, 1975 https://doi.org/10.1002/pen.760150108
  4. Ryan, M. and Chung, T., 'Conformal Mapping Analysis of Injection Molding Filling,' Polym. Eng. and Sci., Vol. 20, pp. 642, 1980 https://doi.org/10.1002/pen.760200910
  5. Stevenson, J., 'A Experimental study and Simulation of Disk Filling by Injection Molding,' SPE Technical Papers, Vol. 22, pp. 282, 1976
  6. White, J. and Dietz, W., 'Some Relationships Between Injection Molding Conditions and the Characteristics of Vitrified Molded Parts,' Polyrn. Eng. and Sci., Vol. 19, No. 15, pp. 1081, 1979 https://doi.org/10.1002/pen.760191504
  7. Krueger, W. and Tadmor, Z., 'Injection Molding into a Rectangular Cavity with inserts,' Polym. Eng. and Sci., Vol. 20, pp. 426, 1980 https://doi.org/10.1002/pen.760200608
  8. Osakada, K. and Yang, G., 'Application of Neural Networks to an Expert System for Cold Forging,' Int. J. Mach. Tool Manu., Vol. 41, pp. 577, 1991 https://doi.org/10.1016/0890-6955(91)90038-5
  9. Spencer, R. and Gilmore, G., 'Equation of State for High polymers', J. Appl. Phys., Vol. 21, pp. 523, 1950 https://doi.org/10.1063/1.1699699
  10. Lee, S. C., Park, C. E. and Yang, D. Y., 'Analysis for Filling Stage of Injection Molding Considering Compressibility and Phase Change,' J. of KSPE, Vol. 18, No. 12, pp. 60, 2001