Journal of Failure Analysis and Prevention

, Volume 11, Issue 4, pp 432–445 | Cite as

A Step Toward Risk Mitigation During Conceptual Product Design: Component Selection for Risk Reduction

Technical Article---Peer-Reviewed

Abstract

The objective of this article is to introduce a method that will mitigate product risks during the conceptual design phase by identifying design variables that affect product failures. By using this comprehensive, step-by-step process that combines existing techniques in a new way, designers can begin with a simple functional model and emerge from the conceptual design phase with specific components selected with many risks already mitigated. The risk in early design (RED) method plays a significant role in identifying failure modes by functions, and these modes are then analyzed through modeling equations or lifespan analyses, in such a manner that emphasizes variables under the designers’ control. With the valuable insight this method provides, informed decisions can be made early in the process, thereby eliminating costly changes later on.

Keywords

Concept selection Risk analysis Lifespan analysis 

Notes

Acknowledgments

The authors would like to acknowledge the assistance of Even Laboube and Noroharivelo Randrianampy for their help on this project.

References

  1. 1.
    2008 Performance and Accountability Report: Saving Lives and Keeping Families Safe. U.S. Consumer Product Safety Commission (ed.), November (2008)Google Scholar
  2. 2.
    Ullman, D.G.: The Mechanical Design Process, 3rd edn. McGraw Hill, Boston (2003)Google Scholar
  3. 3.
    Hyman, B.I.: Fundamentals of Engineering Design. Prentice Hall, Upper Saddle River, NJ (1998)Google Scholar
  4. 4.
    Otto, K.N., Wood, K.L.: Product Design. Prentice-Hall Inc., Upper Saddle River, NJ (2001)Google Scholar
  5. 5.
    Altshuller, G.: Creativity as an Exact Science. Gorden and Breach, Luxembourg (1984)Google Scholar
  6. 6.
    Bryant, C., Stone, R., McAdams, D., Kurtoglu, T., Campbell, M.: Concept Generation from the functional Basis of Design in International Conference on Engineering Design, ICED 05, Melbourne, Australia (2005)Google Scholar
  7. 7.
    Arnold, C.R., Stone, R.B., McAdams, D.A.: MEMIC: an interactive morphological matrix tool for automated concept generation. In: Proceedings of the 2008 Industrial Engineering Research Conference (2008)Google Scholar
  8. 8.
    Vesely, W.E., Goldberg, F.F., Roberts, N.H., Haasl, D.F.: Fault Tree Handbook, NUREG-0492, United States Nuclear Regulatory Commission (ed.), U.S. Government Printing Office (1981)Google Scholar
  9. 9.
    Bedford, T., Cooke, R.: Probabilistic Risk Analysis: Foundations and Methods. Cambridge University Press, Cambridge (2001)Google Scholar
  10. 10.
    Frank, M.V.: Reentry safety: probability of fuel release. In: ESREL ’99 (1999)Google Scholar
  11. 11.
    Reactor Safety Study: An Assessment of Accident Risks in U.S. Commercial Nuclear Power Plants, Appendix I: Accident Definition and Use of Event Trees. United States Nuclear Regulatory Commission (ed.) (1975)Google Scholar
  12. 12.
    Procedures for Performing Failure Mode, Effects, and Criticality Analysis, MIL-STD-1629A, Department of Defense (ed.) (1980)Google Scholar
  13. 13.
    Kurtoglu, T., Tumer, I.: A graph-based fault identification and propagation framework for functional design of complex systems. J. Mech. Des. 130, 051401 (2008)CrossRefGoogle Scholar
  14. 14.
    Grantham Lough, K., Krus, D.: Breaking the cycle-preventing failures by leveraging historical data conceptual design. In: Proceedings of the Flexible Automation and Intelligent Manufacturing ’07, Las Vegas, NV (2007)Google Scholar
  15. 15.
    Krus, D.A., Grantham Lough, K.: Function-based failure propagation for conceptual design. In: Artificial Intelligence for Engineering Design, Analysis and Manufacturing, vol. 23, pp. 409–426. Cambridge University Press (2009)Google Scholar
  16. 16.
    Coit, D.W., Smith, A.: Penalty guided genetic search for reliability design optimization. Comput. Ind. Eng. 30(4), 895–904 (1996)CrossRefGoogle Scholar
  17. 17.
    Coit, D.W.: System reliability prediction prioritization strategy. In: Proceedings of the Annual Reliability and Maintainability Symposium. IEEE (2000)Google Scholar
  18. 18.
    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
  19. 19.
    Collins, J.A., Hagan, B.T., Bratt, H.M.: The failure-experience matrix: a useful design tool. J. Eng. Ind. 98(3), 1074–1079 (1976)CrossRefGoogle Scholar
  20. 20.
    Collins, J.A.: Failure of Materials in Mechanical Design. Wiley, New York (1993)Google Scholar
  21. 21.
    Uder, S.J., Stone, R.B., Tumer, I.Y.: Failure analysis in subsystem design for space missions. In: Proceedings of ASME Design Engineering Technical Conference ’04, Salt Lake City (2004)Google Scholar
  22. 22.
    Tumer, I.Y., Stone, R.B., Bell, D.G.: Requirements for a failure mode taxonomy for use in conceptual design. In: International Conference on Engineering Design, Paper No. 1612, Stockholm, Sweden, August 2003Google Scholar
  23. 23.
    Grantham Lough, K.A.: Risk in early design. Dissertation, University of Missouri-Rolla, August 2005Google Scholar
  24. 24.
    Meeker, W.Q., Escobar, L.A.: Statistical Methods for Reliability Data. Wiley, New York (1998)Google Scholar
  25. 25.
    Metropolis, N., Ulam, S.: The Monte Carlo method. J. Am. Stat. Assoc. 44(247), 335–341 (1949)CrossRefGoogle Scholar
  26. 26.
    Kumamto, H., Henley, E.J.: In: Anderson, J.B. (ed.) Probabilistic Risk Assessment and Management for Engineers and Scientists, 2nd edn. IEEE Press, New York (1996)Google Scholar
  27. 27.
    Bannantine, J., Comer, J., Handrock, J.: Fundamentals of Metal Fatigue Analysis. Prentice Hall, New Jersey (1990)Google Scholar
  28. 28.
    Collins, J.A.: Failure of Materials in Mechanical Design: Analysis, Prediction & Prevention. Wiley, New York (1981)Google Scholar
  29. 29.
    Azizi, N., Couras, P.: Gate Oxide Breakdown, 2 December 2003Google Scholar
  30. 30.
    Agarwala, R.P.: Radiation Damage in Some Refractory Metals. Trans Tech Publication, Ltd, Switzerland (2005)Google Scholar
  31. 31.
    eFatigue.: eFatigue Material Property Finder. eFatigue LLC, 18 May 2010. https://efatigue.com/probabilistic/strainlife/materials/
  32. 32.
    Park, J., et al.: Development of accelerated life tests for lithium battery. In: Proceedings of International Workshop on Reliability and its Applications, pp. 247–253 (2003)Google Scholar
  33. 33.
    Weaver, R.D., McKubre, M.C.H., Symons, P.C., Tanzella, F.L.: Some reliability considerations of various networks of sodium/sulfur batteries. In: Proceedings of IECEC-89, Washington, DC, 6–11 August 1989Google Scholar
  34. 34.
    Simons, S.N., Willhoite, B.C., Van Ommering, G.: Energy storage and thermal control system design status. In: Proceedings of IECEC-89, Washington, DC, 6–11 August 1989Google Scholar
  35. 35.
    Beer, F., Johnston, R., Dewolf, J.: Mechanics of Materials, 3rd edn. McGraw Hill, Coston (2001)Google Scholar
  36. 36.
    ASM Handbook, 10th edn., vol. 13, 13a, 13b, 13c (1990)Google Scholar
  37. 37.
    Graig, B.D.: Material Failure Modes, Pt 2. Material EASE AMPTIAC 30Google Scholar
  38. 38.
    Shigley, J., Mischke, C., Budynas, R.: Mechanical Engineering Design, 7th edn. McGraw Hill, Boston (2004)Google Scholar
  39. 39.
    Anderson, T.L.: Fracture Mechanics, 3rd edn. Taylor & Francis, Boca Raton (2005)Google Scholar
  40. 40.
    Lewis, R.: A modeling technique for predicting compound impact wear. Wear 262(11–12), 1516–1521 (2007)CrossRefGoogle Scholar
  41. 41.
    Tipler, P.: Physics for Scientists and Engineers, 4th edn. W.H. Freeman and Company, New York (1999)Google Scholar
  42. 42.
    Quality and Reliability Handbook. Sanyo Semiconductor Co, LtdGoogle Scholar
  43. 43.
    Black, J.R.: Metallization Failures in Integrated Circuits. RADC Technical Report, vol. TR-68-243, October 1968Google Scholar
  44. 44.
    Zocholl, S.: On the Protection of Thermal Processes, April 2005Google Scholar

Copyright information

© ASM International 2011

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringMissouri University of Science and TechnologyRollaUSA
  2. 2.Engineering Management and Systems EngineeringMissouri University of Science and TechnologyRollaUSA

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