Transactions of the Korean Society of Automotive Engineers (한국자동차공학회논문집)

The Korean Society of Automotive Engineers (한국자동차공학회)
권호 표지

Web-based Design Support System for Automotive Steel Pulley

웹 기반 자동차용 스틸 풀리 설계 지원 시스템

  • Kim, Hyung-Jung (School of Mechanical and Aerospace Engineering & Institute of Advanced Machinery and Design, Seoul National University) ;
  • Lee, Kyung-Tae (School of Mechanical and Aerospace Engineering & Institute of Advanced Machinery and Design, Seoul National University) ;
  • Chun, Doo-Man (School of Mechanical and Aerospace Engineering & Institute of Advanced Machinery and Design, Seoul National University) ;
  • Ahn, Sung-Hoon (School of Mechanical and Aerospace Engineering & Institute of Advanced Machinery and Design, Seoul National University) ;
  • Jang, Jae-Duk (R&D Center, Korea Powertrain Co., Ltd.)
  • 김형중 (서울대학교 기계항공공학부, 정밀기계설계공동연구소) ;
  • 이경태 (서울대학교 기계항공공학부, 정밀기계설계공동연구소) ;
  • 천두만 (서울대학교 기계항공공학부, 정밀기계설계공동연구소) ;
  • 안성훈 (서울대학교 기계항공공학부, 정밀기계설계공동연구소) ;
  • 장재덕 (한국파워트레인(주))
  • Published : 2008.11.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this research, a web-based design support system is constructed for the design process of automotive steel pulley to gather engineering knowledge from pulley design data. In the design search module, a clustering tool for design data is proposed using K-means clustering algorithm. To obtain correlational patterns between design and FEA (Finite Element Analysis) data, a Multi-layer Back Propagation Network (MBPN) is applied. With the analyzed patterns from a number of simulation data, an estimation of minimum von mises can be provided for given design parameters of pulleys. The case study revealed fast estimation of minimum stress in the pulley within 12% error.

Keywords

References

  1. A. Persidis and A. Duffy, Learning in Engineering Design. Intelligent III (H. Yoshikawa et al., Eds.), Elsevier Science Publishers, North- Holland, pp.251-272, 1991
  2. S. K. Sim and A. Duffy, "A Foundation for Machine Learning in Design," Artificial Intelligence Engineering Design, Analysis and Manufacturing, Vol.12, pp.193-209, 1998
  3. N. Ivezic and J. H. Garrett, "A Neural Network- based Machine Learning Approach for Supporting Synthesis," Artificial Intelligence Engineering Design, Analysis and Manufacturing, Vol.8, pp.143-161, 1994 https://doi.org/10.1017/S0890060400000731
  4. Y. Reich, "The Development of BRIDGER, A Methodological Study of Research in the Use of Machine Learning in Design," Artificial Intelligence Engineering, Vol.8, pp.165-181, 1993 https://doi.org/10.1016/0954-1810(93)90003-X
  5. A. H. B. Duffy, A. Persidis and K. J. Mac- Callum, "NODES: A Numerical and Object Based Modeling System for Conceptual Engineering Design," Knowledge-Based Systems, Vol.9, pp.183-206, 1996 https://doi.org/10.1016/0950-7051(95)01027-0
  6. S. M. Duffy and A. H. B. Duffy, "Shearing the Learning Activity Using Intelligent CAD," Artificial Intelligence Engineering Design, Analysis and Manufacturing, Vol.10, pp.83-100, 1996 https://doi.org/10.1017/S0890060400001335
  7. G. C. Onwubolu, "Manufacturing Features Recognition Using Backpropagation Neural Networks," Journal of Intelligent Manufacturing, Vol.10, pp.289-299, 1999 https://doi.org/10.1023/A:1008904109029
  8. B. H. M. Sadeghi, "A BP-neural Network Predictor Model for Plastic Injection Molding Process," Journal of Materials Processing Technology, Vol.103, pp.411-416, 2000 https://doi.org/10.1016/S0924-0136(00)00498-2
  9. J. Lee, "Automated Structural Design System Using Fuzzy Theory and Neural Network," International Journal of Precision Engineering and Manufacturing, Vol.3, No.1, pp.43-48, 2002
  10. D. Kim and B. Kim, "Determination of the Initial Billet Geometry for a Forged Product Using Neural Networks," Journal of Materials Processing Technology, Vol.72, pp.86-93, 1997 https://doi.org/10.1016/S0924-0136(97)00134-9
  11. M. Lee, M. Yoon, M. Sunwoo, S. Park and K. Lee, "Development of a New Misfire Detection System Using Neural Network," Int. J. Automotive Technology, Vol.7, No.5, pp.637-644, 2006
  12. S. H. Ahn, V. Sundararajan, C. E. Smith, B. Kannan, R. D'Souza, G. Sun, J. Kim, S. McMains, J. Smith, A. Mohole, C. H. Sequin and P. K. Wright, "CyberCut: An Internet Based CAD/CAM System," ASME Journal of Computing and Information Science in Engineering, Vol.1, No.1, pp.52-59, 2001 https://doi.org/10.1115/1.1351811
  13. S. H. Ahn, B. Bharadwaj, H. Khalid, S. Y. Liou and P. K. Wright, "Web-based Design and Manufacturing System for Automobile Components: Architectures and Usability Studies," International Journal of Computer Integrated Manufacturing, Vol.15, pp.555-563, 2002 https://doi.org/10.1080/09511920210151012
  14. S. H. Ahn, D. S. Kim, W. S. Chu and C. S. Jun, "MIMS: Web-based Micro Machining Service," International Journal of Computer Integrated Manufacturing, Vol.18, pp.251-259, 2005 https://doi.org/10.1080/09511920400030187
  15. D. M. Chun, S. H. Ahn and J. D. Jang, "Construction of Web-based Material Database and Case Study of Material Selection for Automotive Engine Pulley," Transactions of KSAE, Vol.14, No.4, pp.107-114, 2006
  16. D. M. Chun, H. J. Kim, S. H. Ahn, J. D. Jang and G. B. Lee, "SmartPulley: Web-based Design Support System for Automotive Steel Pulley," SAE 2006 World Congress, Detroit, Michigan, 2006
  17. J. Hartigan and M. Wang, "A K-means Clustering Algorithm," Applied Statistics, Vol.28, pp.100-108, 1979 https://doi.org/10.2307/2346830
  18. Z. Gu, M.X. Tang and J. H. Frazer, "Capturing Aesthetic Intention during Interactive Evolution," Computer-Aided Design, Vol.38, pp.224-237, 2006 https://doi.org/10.1016/j.cad.2005.10.008
  19. O. Richard, E. Peter and G. David, Pattern Classification, 2nd Edn, Wiley Interscience, New York, pp.323-402, 2000