A Computer-Aided Inspection Planning System for On-Machine Measurement - Part I : Global Inspection Planning -

  • Lee, Hong-Hee (Division of Mechanical Engineering, lnha University) ;
  • Cho, Myeong-Woo (Division of Mechanical Engineering, lnha University) ;
  • Yoon, Gil-Sang (Division of Mechanical Engineering, lnha University) ;
  • Choi, Jin-Hwa (Division of Mechanical Engineering, lnha University)
  • Published : 2004.08.01

Abstract

Computer-Aided Inspection Planning (CAIP) is the integration bridge between CAD/CAM and Computer Aided Inspection (CAI). A CAIP system for On-Machine Measurement (OMM) is proposed to inspect the complicated mechanical parts efficiently during machining or after machining. The inspection planning consists of Global Inspection Planning (GIP) and Local Inspection Planning (LIP). In the GIP, the system creates the optimal inspection sequence of the features in a part by analyzing the various feature information such as the relationship of the features, Probe Approach Directions (PAD), etc. Feature groups are formed for effective planning, and special feature groups are determined for sequencing. The integrated process and inspection plan is generated based on the sequences of the feature groups and the features in a feature group. A series of heuristic rules are developed to accomplish it. In the LIP of Part II, the system generates inspection parameters. The integrated inspection planning is able to determine optimum manufacturing sequence for inspection and machining processes. Finally, the results are simulated and analyzed to verify the effectiveness of the proposed CAIP.

Keywords

References

  1. Cho, M. W. and Kim, K., 1995, 'New Inspection Planning Strategy for Sculptured Surfaces Using Coordinate Measuring Machine,' International Journal of Production Research, Vol. 33, No. 2, pp. 427-444 https://doi.org/10.1080/00207549508930158
  2. Cho, M. W. and Seo, T. I., 2002, 'Inspection Planning Strategy for the On-Machine Measurement Process Based on CAD/CAM/CAI Integration Concept,' The International Journal of Advanced Manufacturing Technology, Vol. 19, pp. 607-617 https://doi.org/10.1007/s001700200066
  3. Cho, M. W., Seo, T. I. and Kwon, H. D., 2003, 'Integrated error compensation method using OMM system for profile milling operation,' Journal of Materials Processing Technology, Vol. 136, pp. 88-99 https://doi.org/10.1016/S0924-0136(02)00943-3
  4. Chang, T. C. and Wysk, R. A., 1985, An Introduction to Process Planning Systems, Prentice-Hall, Englewood cliffs, New Jersey, USA
  5. Descotte, Y. and Latombe, J. C., 1984, GARI : An Expert System for Process Planning, Solid Modeling by Computers, Plenum Press, NY, pp. 329-345
  6. Lee, H., 1991, 'A Generic Learning System for Computer-Aided Process Planning, Ph. D. Dissertation,' The Pennsylvania state University, University Park, PA.
  7. Lee, J. W., Kim, M. K. and Kim, K., 1994, 'Optimal Probe Path Generation and New Guide Point Selection Methods,' Engineering Application of Artificial Intelligence, Vol. 7, No. 4, pp. 439-445 https://doi.org/10.1016/0952-1976(94)90009-4
  8. Lee, K. I., Lee, H., Noh, S. D., Shim, Y. B. and Cho, H. S., 1995, 'A Process Planning System Using Group Technology and Rule-base,' IE Interfaces. Korean Institute of Industrial Engineers, Vol. 8, No. 3, pp. 221-230
  9. Rogers, M., 1994, 'Case Study of Feature Representation in STEP,' Part 48, Technical Report, Design Automation Laboratory, Department of Mechanical Engineering, Arizona State University, USA
  10. Shah, J. J., Mantyla, M. and Nau, D. D., 1994, Advances in Feature-Based Manufacturing, Elsevier Science B. V., Amsterdam, Netherlands
  11. Stout, K. J., 2000, 'Engineered Surfaces Part I. -A Philosophy of Manufacture,' KSME International Journal, Vol. 14, No. 1, pp. 72-83 https://doi.org/10.1007/BF03184773