Skip to main content

Machinability Data Base Systems for Automated Manufacturing

  • Chapter
Book cover Computer-Based Automation

Abstract

A machinability data base system, which forms a part of the common manufacturing data base and is also capable of adapting and optimizing the machining data, is an important component of automated manufacturing systems. In this paper, the current status of machinability data base systems is analyzed. Several drawbacks of the present systems and the need for new developments are discussed. A generative type machinability data base system is proposed for automating the adaptation and optimization of the machining data. Various elements of these types of systems such as the machinability data base design, model builder, optimization algorithm, and adaptation algorithm are discussed. A typical machining problem is formulated and analyzed to illustrate the proposed adaptive optimization methodology.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. V. A. Tipnis, “Development of mathematical models of adaptive control systems,” Proc. 13th NC Society Conference, pp. 149–156, 1976.

    Google Scholar 

  2. V. A. Tipnis, S. C. Buescher, and R. C. Garrison, “Mathematically modeled machining data for adaptive control of end milling operations,” Proc. NAMRC-IV, pp. 279–286, 1976.

    Google Scholar 

  3. R. A. Mathias and R. B. Ludwig, “A machinability routine that optimizes CL file feeds and speeds prior to postprocessing,” SME Technical Paper, MS79–403.

    Google Scholar 

  4. D. S. Appleton, “Measure twice; cut once,” Datamation, Vol. 28, No. 2, pp. 126–136, February 1982.

    Google Scholar 

  5. M. F. DeVries, P. Balakrishnan, and J. Agapiou, “A study of two tasks applicable to an automated manufacturing research facility-Volume I: Task A; A study of machinability data banks,” Report for the National Bureau of Standards, University of Wisconsin-Madison, 1982.

    Google Scholar 

  6. P. Balakrishnan and M. F. DeVries, “A review of computerized machinability data base systems,” Proc. NAMRC-X, pp. 348–356, 1982.

    Google Scholar 

  7. H. Yoshikawa, “Study on the structure of software for fully automated factory,” Proc. CIRP Intl. Sem. on Manufacturing Systems, Vol. 7, No. 2, pp. 101–109, 1978.

    Google Scholar 

  8. M. Y. Friedman, M. Field, and K. J. Kahles, “Machinability data bank design,” Ann. CIRP, Vol. 23, No. 1, pp. 171–172, 1974.

    Google Scholar 

  9. W. J. Zdeblick, “Real time manufacturing data selection system,” Proc. CIRP Intl. Sem. on Manufacturing Systems,“ Vol. 9, No. 4, pp. 243–263, 1980.

    Google Scholar 

  10. J. Stanic and V. Solaja, “On an adaptive optimization model of manufacturing processes,” Ann. CIRP, Vol. 27, No. 1, pp. 419–423, 1978.

    Google Scholar 

  11. W. J. Zdeblick, “An adaptive planning methodology for machining operations,” SME Technical Paper, MR 82–243, 1982.

    Google Scholar 

  12. R. A. Ross, “Logical data base design,” Data Base Journal, Vol. 11, No. 4, pp. 2–8, 1981.

    Google Scholar 

  13. S. Arun, “Logical data base design: A management oriented approach,” Information & Management, Vol. 5, No. 2, pp. 77–85, June 1982.

    Article  Google Scholar 

  14. D. C. Tsichritzis and F. H. Lochovsky, Data Models, Prentice-Hall, Inc., 1982.

    Google Scholar 

  15. R. J. Miner, M. E. Grant, and R. J. Mayer, “Decision support for manufacturing,” Proc. IEEE Winter Simulation Conf., pp. 543–549, 1981.

    Google Scholar 

  16. P. Balakrishnan and M. F. DeVries, “Analysis of mathematical model building techniques adaptable to machinability data base systems,” Proc. NAMRC-XI, pp. 466–475, 1983.

    Google Scholar 

  17. R. H. Philipson and A. Ravindran, “Application of mathematical programming to metal cutting,” Mathematical Program Study, Vol. 11, Enginering Optimization, M. Avriel (Ed.), North Holland Publishing Co., pp. 116–134, 1979.

    Google Scholar 

  18. D. L. Kimbler, R. A. Wysk, and R. P. Davis, “Alternative approaches to the machining parameter optimization problem,” Compt. & Indus. Eng., Vol. 2, No. 4, pp. 195–202, 1978.

    Article  Google Scholar 

  19. A. D. Waren and L. S. Ladson, “The status of nonlinear programming software,” Operations Research, Vol. 27, No. 3, pp. 431–456, May-June 1979.

    Article  MathSciNet  MATH  Google Scholar 

  20. G. N. Saridis, Self-Organizing Control of Stochastic Systems, Marcel Dekker, Inc., 1977.

    Google Scholar 

  21. T. Sata and K. Matsushima, “A proposal of the multilayered control of machine tools for fully automated machining operations,” Proc. IFAC Symposium on Information Control Problems in Manufacturing Technology, Y. Oshima (Ed.), Pergamon Press, pp. 173–181, 1978.

    Google Scholar 

  22. S. Yonetsu and I. Inasaki, “Optimization of turning operation,” Proc. NAMRC-VI, pp. 17–23, 1978.

    Google Scholar 

  23. S. K. Birla, “Sensors for adaptive control and machine diagnostics,” Technology of Machine Tools-Machine Tool Task Force, Vol. 4, Chapter 7–12, October 1980.

    Google Scholar 

  24. P. Link, “Shop floor control,” Commline, Vol. XI, No. 6, pp. 16–18, November 1982.

    Google Scholar 

  25. P. Balakrishnan and M. F. DeVries, “Sequential estimation of machinability parameters for adaptive optimization of machinability data base systems,” paper submitted for presentation at the ASME Winter Annual Meeting, November 1983.

    Google Scholar 

  26. J. V. Beck and K. J. Arnold, Parameter Estimation in Engineering and Science, John Wiley & Sons, 1977.

    Google Scholar 

  27. D. S. Ermer and R. K. Pradhan, “Economic selection of cutting conditions for constrained single or multipass operation,” Proc. NAMRC-VII, pp. 355–361, 1979.

    Google Scholar 

  28. IMSL Library Reference Manual, IMSL, Inc., 1982.

    Google Scholar 

  29. GPM/GPMNLC: Extended Gradient Projection Method Nonlinear Programming Subroutine for ASCII Fortran, User Manual for the UNIVAC 1100, MACC, University of Wisconsin-Madison, 1983.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1985 Plenum Press, New York

About this chapter

Cite this chapter

Balakrishnan, P., DeVries, M.F. (1985). Machinability Data Base Systems for Automated Manufacturing. In: Tou, J.T. (eds) Computer-Based Automation. Springer, Boston, MA. https://doi.org/10.1007/978-1-4684-7559-3_24

Download citation

  • DOI: https://doi.org/10.1007/978-1-4684-7559-3_24

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4684-7561-6

  • Online ISBN: 978-1-4684-7559-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics