Robust Design and Statistical Tolerance Analysis

  • Fouad Bennis
Conference paper

Abstract

Product variation is a key piece of information that flows from the design function to manufacturing function in an enterprise. Every, engineering design is subject to variation that can arise from a variety of sources, including manufacturing operations, variation in material properties, and at the operating environment. Engineers must deal with variations in the products they design and manufacture. They have to produce robust designs by assessing the expected size of variation and determining the risk of failure. The best time to reduce the impact of variation is in the early stages of design process. Variation analysis in mechanical design becomes an essential practice.

This paper presents a review of statistical tolerance analysis and the robust design approaches. The main objective of tolerance analysis and robust design domains is to control the geometrical and operational variation of product. Tolerance analysis and robust design methods are based on several precise hypotheses and conditions.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Srinivasan V., “ISO Deliberates Statistical Tolerancing”. Proc. of the 5th CIRP International Seminar on Computer Aided Tolerancing, Toronto, Canada. 1997, pp: 25–35.Google Scholar
  2. [2]
    Srinivasan V., “Role of Statistics in Achieving Global Consistency of tolerances”, Proc. of the 6th CIRP International Seminar on Computer Aided Tolerancing, The Netherlands, 22–24 March 1999, pp 395–404.CrossRefGoogle Scholar
  3. [3]
    Bjorke O. “Computer Aided tolerancing”, ASME Press, second edition 1989.Google Scholar
  4. [4]
    Chase K. W. et Parkinson A. R., “A Survey of Research in the Application of Tolerance Analysis to the Design of Mechanical Assemblies”. Research In Engineering Design, 3: pp:23–37, 1991.CrossRefGoogle Scholar
  5. [5]
    Nigam S. D. et Turner J. U., “Review of statistical approaches to tolerance analysis”. Computer Aided Design, 27(1): 6–15, 1995.MATHCrossRefGoogle Scholar
  6. [6]
    Srinivasan V., O’Connor M. A. et Scholz F.W., “Techniques for composing a Class of Statistical Tolerances Zones”. IBM Research Division. Report n°20254, 1996.Google Scholar
  7. [7]
    Zhang W., “Sensitive factor for position tolerance”. Int. Jour. Of Research In Engineering Design, (9), pp: 228–234, 1997.Google Scholar
  8. [8]
    Greenwood W.H and Chase K.W, “Root sum squares tolerance analisysis with nonlinear problems”, Transaction of the ASME Journal of Engineering for Industry, Vol 112, Nov. 1990, pp: 382–384.CrossRefGoogle Scholar
  9. [9]
    Whitney D. E. et Gilbert O.L., and M. Jastrzebski, “Representation of geometric variations using matrix transforms for statistical tolerance analysis in assemblies”. Inter. Jour. Of Research In Engineering Design, (6), pp: 191–210, 1994.Google Scholar
  10. [10]
    Skowronski V.J and Turner J.U., “Estimating gradients for statistical tolerance synthesis”, Computer Aided Design, Vol 28, n° 12, 1996,pp 933–941.CrossRefGoogle Scholar
  11. [11]
    Skowronski V.J and Turner J.O. , “Using Monte-Carlo variance reduction in statistical tolerance synthesis”, Computer Aided Design, Vol 29, n° 1, 1997, pp 63–69.CrossRefGoogle Scholar
  12. [12]
    Taylor W.A, “Process tolerancing: A solution to the dilemma of worst-case versus statistical tolerancing”, Fall technical conference, 1995.Google Scholar
  13. [13]
    Kane V. E, “Process Capability indices”, Jour. Qual. Technol., 18(1), 1986r, pp: 41–52.Google Scholar
  14. [14]
    Harry M.J and Stewart R, “Six sirma mechanical design tolerancing” , Tech. Report 6sigma 2–10/88 Motorola Corporation (1988).Google Scholar
  15. [15]
    Glancy C.G and Chase K. “A second-order method for assembly tolerance analysis”, Proc. of ASME Design Engineering Tech. conf. Las vagas Nevada, Sept. 12–15, 1999. DETC99/DAC-8707.Google Scholar
  16. [16]
    Sundaresan S., Ishii K. and Houser D.R, “A robust optimization procedure with variations on design variables and constraints”, DE-Vol 65–1 Advances in design Automation, Vol 1, ASME 1993, pp 379–387.Google Scholar
  17. [17]
    Kaisi M., Hacker K., and Lewis K., “A comprehensive Robust Design Approach for decision Tradeoffs in comlex systems design”. Proc. of ASME Design Engineering Tech. conf. Las vagas Nevada, Sept. 12–15, 1999. DETC99/DAC-8589.Google Scholar
  18. [18]
    Srinivasan V. “On interpreting key characteristics”, Proc. of ASME Design Engineering Tech. conf. Las vagas Nevada, Sept. 12–15, 1999. DETC99/DAC-8701.Google Scholar
  19. [19]
    Parkinson A., Sorensen C. and Pourhassan N. “A general Aproach for robust optimal design”, Transaction of ASME Journal of Mechanical Design, Vol. 115, June 1993, pp: 74–80.CrossRefGoogle Scholar
  20. [20]
    Parkinson A. “Robust Mechanical Design using engeneering models”, Transaction of ASME Journal of Mechanical Design, Vol. 117, June 1995, pp 48–54.CrossRefGoogle Scholar
  21. [21]
    Gadallah M. H. and Elmaraghy H.A. “Desing for robust performance: a concurent engineering approch”, Adances in Manufacturing systems 1994 R.S. Sodhi (editor), 1994, pp 269–277.Google Scholar
  22. [22]
    Parkinson A, Chase K. Rogers M. “Robust design via tolerance analysis in the conceptual design stage”, Proc. of ASME Design Engineering Tech. conf. Las vagas Nevada, Sept. 12–15, 1999. DETC99/DAC-8577.Google Scholar
  23. [23]
    Chen Li, “A coordination based approach to robust product design”, Proc. of ASME Design Engineering Tech. conf. Las vagas Nevada, Sept. 12–15, 1999. DETC99/DAC-8558.Google Scholar
  24. [24]
    Yu J.O and Ishii K. “Design for robustness based on manufacturing variation patterns”, Transaction of The ASME Journal of Mechanical Design, Vol 120, June 1998, pp 196–202CrossRefGoogle Scholar
  25. [25]
    Du X and Chen W, “Towards a better understanding of modeling feasibility robustness in engineering design”. Proc. of ASME Design Engineering Tech. conf. Las vagas Nevada, Sept. 12–15, 1999. DETC99/DAC-8565.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2002

Authors and Affiliations

  • Fouad Bennis
    • 1
  1. 1.IRCCyN, UMR. CNRS 6597Ecole Centrale de NantesNantes cedexFrance

Personalised recommendations