Journal of Failure Analysis and Prevention

, Volume 8, Issue 5, pp 469–481 | Cite as

Failure Prevention in Design Through Effective Catalogue Utilization of Historical Failure Events

  • K. A. Grantham Lough
  • R. B. Stone
  • I. Y. Tumer
Technical Article---Peer-Reviewed


The science of failure prevention relies heavily on the experience of personnel on a project. As the nation is about to face a tremendous decline in the experienced workforce due to the baby boomer generation’s retirement, it is critical to begin focusing on capturing their knowledge. Cataloging and communicating the knowledge of potential failures is critical to prevent engineering disasters. Many companies have adopted failure-reporting systems that allow them to record their engineering failures to promote failure prevention. While recording this information is vital to learning from past mistakes, often the information is not stored so that engineers and designers can easily recall this valuable linguistic information and use it to improve designs. Therefore, more effective systems for cataloging and utilizing corporate memory of recorded failure events are needed. This article presents the design of a computational linguistic database to support the failure prevention tool, the risk in early design (RED) method. RED promotes failure prevention by identifying failure risks as early as the conceptual phase of product design, where impacts of failure prevention are greatest. It uses a database populated by historical failure event information to present specific areas that are at risk of failure in a product.


Design Failure analysis Failure prevention Risk assessment 


  1. 1.
    Beiter, K.A., Cheldelin, B., Ishii, K.: Assembly quality method: a tool in aid of product strategy, design, and process improvement. In: Proceedings of the Design Engineering Technical Conferences, ASME, Baltimore, MD (2000) Google Scholar
  2. 2.
    Hawkins, P.G., Woolons, D.J.: Failure modes and effects analysis of complex engineering systems using functional models. Artif. Intell. Eng. 12, 375–395 (1998)CrossRefGoogle Scholar
  3. 3.
    Wirth, R., et al.: Knowledge-based support anlysis for the analysis of failure modes and effects. Eng. Appl. Artif. Intell. 9(3), 219–229 (1996)Google Scholar
  4. 4.
    Kurfman, M., Rajan, J., Stone, R., Wood, K., Stock, M.: Experimental studies assessing the repeatability of a functional modeling derivation method. J. Mech. Des. 125(4), 682–693 (2003)CrossRefGoogle Scholar
  5. 5.
    Otto, K., Wood, K.: Product Design: Techniques in Reverse Engineering, Systematic Design, and New Product Development. Prentice-Hall, New York (2001)Google Scholar
  6. 6.
    Hirtz, J., Stone, R., McAdams, D., Szykman, S., Wood, K.: A functional basis for engineering design: reconciling and evolving previous efforts. Res. Eng. Des. 13(2), 65–82 (2002)Google Scholar
  7. 7.
    Miles, L.: Techniques of Value Analysis Engineering. McGraw-Hill (1972)Google Scholar
  8. 8.
    Pahl, G., Beitz, W.: Engineering Design: A Systematic Approach. Design Council, London (1984)Google Scholar
  9. 9.
    Greer, J., Stock, M., Stone, R., Wood, K.: Enumerating the component space: first steps toward a design naming convention for mechanical parts. In: Proceedings of the ASME Design Engineering Technical Conference, Chicago, IL (2003)Google Scholar
  10. 10.
    Tumer, I., Stone, R., Bell, D.: Requirements for a failure mode taxonomy for use in conceptual design. In: Proceedings of the International Conference on Engineering Design, Stockholm (2003)Google Scholar
  11. 11.
    Collins, J.A., Hagan, B.T., Bratt, H.M.: The failure experience matrix: a useful design tool. ASME J. Eng. Ind. August, 1074–1079 (1976)Google Scholar
  12. 12.
    Barbour, G.L.: Failure model and effects analysis by matrix method. In: Proceedings of the Annual Reliability and Maintainability Symposium (1977)Google Scholar
  13. 13.
    Collins, J.A.: Mechanical Reliability and Design. Wiley (1993)Google Scholar
  14. 14.
    Goddard, P.L., Dussalt, H.B.: The automated matrix FMEA-A logistics engineering tool. In: Proceedings of the Society of Logistics Engineers’ 19th Annual Symposium (1984)Google Scholar
  15. 15.
    Henning, S., Paasch, R.: Diagnostic analysis of mechanical systems. In: Proceedings of the Design Engineering Technical Conferences, ASME, Baltimore, MD (2000)Google Scholar
  16. 16.
    Grantham Lough, K., Stone, R., Tumer, I.: Function based risk assessment: mapping function to likelihood. In: Proceedings of 2005 ASME International Design Engineering Technical Conference, September 24–28, Long Beach, CAGoogle Scholar
  17. 17.
    Grantham Lough, K., Stone, R., Tumer, I.: The risk in early design (RED) method. J. Eng. Des. on-line November 21, 2007, edition, hardcopy pendingGoogle Scholar
  18. 18.
    Grantham Lough, K., Stone, R., Tumer, I.: Prescribing and implementing the risk in early design (RED) method. J. Ind. Syst. Eng., publication pendingGoogle Scholar
  19. 19.
    Stone, R., Tumer, I., Van Wie, M.: The function failure design method. J. Mech. Des. 127(3), 397–407 (2005)CrossRefGoogle Scholar
  20. 20.
    Office of the Under Secretary of Defense. DSMC Risk Management Guide for DoD Acquisition, 2nd edn. Defense Systems Management College Press, Fort Belvoir, VA (1999)Google Scholar
  21. 21.
    Van Wie, M., Grantham Lough, K., Stone, R., Barrientos, F., Tumer, I.: An analysis of risk and function information in early stage design. Submitted to Proceedings of Design Engineering Technical Conference DETC, Long Beach, CA (2005)Google Scholar
  22. 22.
    ASM International. Handbook of Case Histories in Failure Analysis, vol. 1, pp. 3–8. USA (1992)Google Scholar
  23. 23.
    Wang, J., Roush, M.: What Every Engineer Should Know About Risk Engineering and Management. Marcel Dekker, Inc., New York (2002)Google Scholar
  24. 24.
    Uder, S., Stone, R., Tumer, I.: Function based risk assessment and failure prediction for unmanned space missions. ASME International Mechanical Engineering Congress IMECE 2004-60846Google Scholar
  25. 25.
    Brown, A.F.: Development of a method for flight anomaly characterization. JPL Technical Report, JPL D-11382. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA (1994)Google Scholar
  26. 26.
    Quinn, J.D.: Flight P/FRs and the design review process. JPL Technical Report, JPL D-11381. Jet Propulsion Laboratory, California Institute of Technology, Pasedena, CA (1994)Google Scholar
  27. 27.
    National Transportation Safety Board. (2001)
  28. 28.
    Wikipedia, “Galileo spacecraft.” (2006)
  29. 29.
  30. 30.

Copyright information

© ASM International 2008

Authors and Affiliations

  • K. A. Grantham Lough
    • 1
  • R. B. Stone
    • 1
  • I. Y. Tumer
    • 2
  1. 1.Department of Interdisciplinary EngineeringMissouri University of Science and TechnologyRollaUSA
  2. 2.Department of Mechanical EngineeringOregon State UniversityCorvallisUSA

Personalised recommendations