Setup and Operation Sequence Generation from Manufacturability Evaluation for Prismatic Parts

제조성 평가를 기반으로 한 비회전형상 부품의 작업준비 및 작업순서 생성

  • Choi, Hoo Gon (Department of Systems Management Engineering, Sungkyunkwan University) ;
  • Han, Jung Hyun (Department of Computer Science and Engineering, Korea University) ;
  • Kang, Mujin (School of Mechanical Engineering, Sungkyunkwan University)
  • 최후곤 (성균관대학교 시스템경영공학과) ;
  • 한정현 (고려대학교 컴퓨터학과) ;
  • 강무진 (성균관대학교 기계공학부)
  • Published : 2005.12.30

Abstract

Although some successful recognition algorithms have been developed, most of them did emphasize on extracting accurate interpretations without considerations of manufacturability. Evaluating the manufacturability for multiple features leads to produce the machining sequences. In this paper, the A* algorithm guarantees the optimal setup sequences with minimizing the machining cost. Also, tolerances including surface roughness are converted to STEP formats to be utilized for more reliable process plans. Finally, decision tables are used to create the detailed operational sequences based on geometric tolerances and surface roughness. Machining parameters such as feed, depth of cut, and cutting speed for each operation are added to the routing sheet. Windows are presented to show how the entire system works for a sample part.

Keywords

Acknowledgement

Supported by : Korea Research Foundation

References

  1. ASM International Handbook Committee (1989), Metals Handbook, Vol. 16, Machining, ASM International
  2. Chang, T.C. and Wysk, R.A. (1985), An Introduction to Automated Process Planning Systems, Prentice Hall, chapter 3
  3. Gao, J.X and Huang, X.X. (1996), Production and Manufacturing Capability Modeling in an Integrated CAD/Process Planning Environment, Int. J. of Advanced Manufacturing Technology, 11, 43-51 https://doi.org/10.1007/BF01177183
  4. Gu, P. and Zhang, Y. (1993), Operation sequencing in an automated process planning system, Journal of Intelligent Manufacturing, 4, 219-232 https://doi.org/10.1007/BF00123966
  5. Halevi, G.. and Weill, R.D. (1995), Principles of Process Planning, Chapman & Hall, chapter 5
  6. Han, J. and Han, I. (1999), Manufacturing Feature Recognition and its Integration with Process Planning, The 5th ACM SIGGRAPH Symposium on Solid Modeling and Applications, 108-118
  7. Han, J. and Requicha, A. (1997), Integration of Feature Based Design and Feature Recognition, Computer Aided Design, 29, 393-403 https://doi.org/10.1016/S0010-4485(96)00079-6
  8. Han, J., Kang, M., and Choi, H. (2001), STEP-based Feature Recognition for Manufacturing Cost Optimization, Computer Aided Design, 33(9), 671-686 https://doi.org/10.1016/S0010-4485(01)00071-9
  9. Han, J. and Requicha, A. (1998), Feature Recognition from CAD Models, IEEE Computer Graphics and Applications, 18, 80-94 https://doi.org/10.1109/38.656791
  10. Hart, P.E., Nilsson, N.J. and Raphael, B. (1968), A formal basis for the heuristic determination of minimum cost paths, IEEE Transactions on SSC 4, 100-107
  11. Jung, J., Kim, K.S., and Choi, H.G.. (2003), An Algorithm for Automatic Generation of Dimension and Tolerance Charts, Journal of the Korean Institute of Industrial Engineers, 29(1), 21-31
  12. Machinability Data Centre (1980), Machining Data Handbook, 3rd Ed., Vols. 1 and 2, Machinability Data Centre
  13. Owen, J. (1993), STEP: An Introduction, Information Geometers
  14. $ST-DEVELOPER^{TM}$(1996), ROSE Library Reference Manual, $STEP TOOLS^{TM}$(2nd ed.)
  15. Wang, H P and Li, J.K. (1991), Computer Aided Process Planning, Elsevier, chapters 4, 7 and 8
  16. Wong, T.N. and Siu, S.L. (1992), An Automated Process Planning System for Prismatic Parts, Int. J. of Computer Integrated Manufacturing, 5, 319-333 https://doi.org/10.1080/09511929208944540