Advertisement

Research in Engineering Design

, Volume 3, Issue 2, pp 105–122 | Cite as

A formal method for subjective design evaluation with multiple attributes

  • Deborah L. Thurston
Article

Abstract

This paper contributes toward a more formal theory and methodology for design by mathematically modeling the functional relationships between design decisions and the ultimate overall worth of a design. The conventional approach to design evaluation is limited in two respects. First, the direct measurement of attribute performance levels does not reflect the subsequentworth to the designer. Second, ad hoc methods for determining the relative importance or priority of attributes do not accurately quantify beneficial attribute tradeoffs. This information is critical to the iterative redesign process. A formal Methodology for the Evaluation of Design Alternatives (MEDA) is presented which resolves these problems and can be used to evaluate design alternatives in the iterative design/redesign process. Multiattribute utility analysis is employed to compare the overall utility or value of alternative designs as a function of the levels of several performance characteristics of a manufactured system. The evaluation function reflects the designer's preferences for sets of multiple attributes. Sensitivity analysis provides a quantitative basis for modifying a design to increase its utility to the decision-maker. Improvements in one or more areas of performance and tradeoffs between attributes which would increase desirability of a design most are identified. A case study of materials selection and design in the automotive industry is presented which illustrates the steps followed in application of the method.

Keywords

Manufacture System Design Evaluation Automotive Industry Multiple Attribute Attribute Performance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Altshuler, A., Anderson, M., Jones, D., Roos, D., and Womack, J., “The Future of the Automobile,” MIT Press, 1984Google Scholar
  2. 2.
    Bard, J., “A Two-Phase Methodology for Technology Selection and System Design,”IEEE Transactions on Engineering Management, Vol. EM-36, No. 1, February 1989Google Scholar
  3. 3.
    Bohren, J.S., and Nevill, G.E., “A Methodology for Incorporating Multiple Goals in Automated Abstract Design,”Design Theory and Methodology—DTM '89 Vol. 17, 1 1989Google Scholar
  4. 4.
    Bodily, S.E., “The Utilization of Frozen Red Cell in Blood Banking Systems: A Decision Theoretic Approach,” Technical Report No. 94, Operations Research Center MIT, May, 1974Google Scholar
  5. 5.
    Boothroyd, G., “Making it Simple: Design for Assembly,”Mechanical Engineering, February 1988, 28–31Google Scholar
  6. 6.
    Boothroyd, G., and Dewhurst, P., “Design for Assembly—A Designer's Handbook,” Technical Report, Department of Mechanical Engineering, University of Massachusetts, 1983Google Scholar
  7. 7.
    Buede, D.M., and R.W. Choisser, “An Aid for Evaluators of System Design Alternatives,”Defense Management Journal, 2nd Qtr (1984), 32–38Google Scholar
  8. 8.
    Byer, P.H., and deNeufville, R., “Choosing the Dimensions and Uncertainties of an Evaluation,” from D.W. Bunn and H. Thomas, eds.,Formal Methods in Policy Formulation. Birkhauser Verlag, Basel, 1978Google Scholar
  9. 9.
    Byrne, D.M., and S. Taguchi, “The Taguchi Approach to Parameter Design,” ASQC Quality Congress Transaction, Anaheim, May 1986. pp. 168–177Google Scholar
  10. 10.
    Chandrasekran, B., “A Framework for Design Problem-Solving,”Research in Engineering Design, Vol. 1, No. 2, 1989Google Scholar
  11. 11.
    Chang, D.C., and Justusson, J.W., “Structural Requirements in Material Substitution for Car-Weight Reduction,” Society of Automotive Engineers, Technical Paper No. 760023, Warrendale, PA, 1976Google Scholar
  12. 12.
    Chang, D.C., Wu, K.M., and Vella, J.R., “The Regional Stiffness Requirement of Body Panels for Material Substitution Design,” Society of Automotive Engineers, Technical Paper No. 841202, Warrendale, PA, 1984Google Scholar
  13. 13.
    Conti, T., “Process Management and Quality Function Deployment,”Quality Process, December 1989, 45–48Google Scholar
  14. 14.
    Delquie, P., “Statistical Exploration of ‘Certainty Effects’ on Utility Assessments,” Masters thesis, Department of Civil Engineering, MIT, June 1986Google Scholar
  15. 15.
    De Neufville, R.,Applied Systems Analysis McGraw-Hill, New York, 1990Google Scholar
  16. 16.
    Dixon, J., Howe, A., Cohen, P., and Simmons, M.K., “Dominic I: Progress Towards Domain Independence by Iterative Redesign,”Proc. ASME 1987 International Computers in Engineering Conference, American Society of Mechanical Engineers, Chicago, IL, July 24–26, 1987Google Scholar
  17. 17.
    Dixon, J.R., et al, “Computer-Based Models of Design Processes: The Evaluation of Designs for Redesign,”NSF Engineering Design Research Conference, University of Massachusetts, Amherst, June 11–14, 1989Google Scholar
  18. 18.
    Dyer, J.S., and Miles, R.F., Jr., “An Actual Application of Collective Choice Theory to the Selection of Trajectories for the Mariner Jupiter/Saturn,”Operations Research Vol. 24, No. 2 (1976), 220–244Google Scholar
  19. 19.
    Finger, S., and Dixon, J.R., “A Review of Research in Mechanical Engineering Design, Part I: Descriptive, Prescriptive, and Computer-Based Models of Design Processes,”Research in Engineering Design, Vol. 1, No. 1, 1989Google Scholar
  20. 20.
    Fishburn, P.C.,Utility Theory for Decision Making Wiley, New York, 1970Google Scholar
  21. 21.
    Golabi, K., “Selecting a Group of Dissimilar Projects for Funding,”IEEE Transactions on Engineering Management, Vol. EM-34, No. 3, August 1987Google Scholar
  22. 22.
    Hauser, J.R., and Clausing, D., “The House of Quality,”Harvard Business Review 66:3, 1988, 63–73Google Scholar
  23. 23.
    Howe, A., Cohen, P., and Dixon, J., “Dominic: A Domain-Independent Program for Mechanical Engineering Design,”Artificial Intelligence, Vol. 1, No. 1, 1986Google Scholar
  24. 24.
    Ishii, K., “Life-Cycle Engineering Using Design Compatibility Analysis,” Proceeding of the 1991 NSF Design and Manufacturing Systems Conference, University of Texas at Austin, January 9–11, 1991Google Scholar
  25. 25.
    Kackar, R.N., “Off-Line Quality Control, Parameter Design, and the Taguchi Method,”Journal of Quality Technology 17:4, 1985, 176–188Google Scholar
  26. 26.
    Knight, W.A., and Poli, C., “A Systematic Approach to Forging Design,”Machine Design, January 24, 1985Google Scholar
  27. 27.
    Keeney, R.L., and Raiffa, H.,Decisions with Multiple Objectives: Preferences and Value Tradeoffs Wiley, New York, 1976Google Scholar
  28. 28.
    Kirkwood, C.W., “A Case History of Nuclear Power Plant Site Selection,”J. of Operational Research Society, Vol. 33, 1982Google Scholar
  29. 29.
    Luce, R.D., and H. Raiffa,Games and Decisions Wiley, New York, 1957Google Scholar
  30. 30.
    Madey, G.R., and Dean, B.V., “Strategic Planning for Investment in R&D Using Decision Analysis and Mathematical Programming,”IEEE Transactions on Engineering Managements, Vol. EM-32, No. 2, May 1985Google Scholar
  31. 31.
    Nevill, G.E., “Guiding Iterative Processes for Preliminary Design,” Proceedings of NSF Conference on Design and Manufacturing Systems Research, Arizona State University, January 8–12, 1990, SMEGoogle Scholar
  32. 32.
    Pignatiello, Jr., J.J., “An Overview of the Strategy and Tactics of Taguchi,”IEEE Transactions 20:3, 1988, 247–254Google Scholar
  33. 33.
    Poli, C., and Knight, W.A., “Design for Forging Handbook,” Technical Report, Department of Mechanical Engineering, University of Massachusetts, 1984Google Scholar
  34. 34.
    Poli, C., Escudero, J., and Fernandez, R., “How Part Design Affects Injection Molding Tool Costs,”Machine Design, November 24, 1988Google Scholar
  35. 35.
    Savage, L.J.,The Foundations of Statistics Wiley, New York, 1954Google Scholar
  36. 36.
    Shah, J.J., Hsiao, D., and Robinson, R., “A Framework for Manufacturability Evaluation in a Feature Based CAD System,” Proceedings of NSF Conference on Design and Manufacturing Systems Research, Arizona State University, January 8–12, 1990, SMEGoogle Scholar
  37. 37.
    Sullivan, L.P., “Policy Management Through Quality Function Deployment,”Quality Progress, 1988, 18–20Google Scholar
  38. 38.
    Sullivan, L.P., “Quality Function Deployment,”Quality Progress, 1986, 39–50Google Scholar
  39. 39.
    Taguchi, G., Elsayed, E.A., and Hsiang, T.,Quality Engineering in Production Systems McGraw Hill, New York, 1989Google Scholar
  40. 40.
    Talaysum, A.T., Zia Hassan, M., and Goldhar, J.D., “Uncertainty Reduction Through Flexible Manufacturing,”IEEE Transactions on Engineering Management Vol. EM-34, No. 2, pp. 85–91, May 1987Google Scholar
  41. 41.
    Ting, H.M., “Aggregation of Attributes for Multiattributed Utility Assessment,” Technical Report No. 66, Operations Research Center MIT, August, 1971Google Scholar
  42. 42.
    Thurston, D.L., “A Materials Selection Tool for Automotive Structural and Body Skin Systems,” SAE Materials Transactions 1988, no. 881303, also inDesign and Manufacturing of Off-Highway Equipment: Computer Applications, Society of Automotive Engineers No. SP-755, 1988Google Scholar
  43. 43.
    von Neumann, J., and Morgenstern, O.,Theory of Games and Economic Behavior 2nd ed., Princeton University Press, Princeton, NJ, 1947Google Scholar
  44. 44.
    Ward, A., and Seering, W.P., “Four Hypotheses on Mechanical Design Automation,” NSF Engineering Design Research Conference, University of Massachusetts at Amherst, June 1989, pp. 183–203Google Scholar
  45. 45.
    Watson, S.R., and Buede, D.M.,Decision Synthesis: The Principles and Practice of Decision Analysis Cambridge University Press, Cambridge, Great Britain, 1987Google Scholar
  46. 46.
    Webster's New Collegiate Dictionary, G.&C. Merriam Co., Springfield, MA, 1974Google Scholar
  47. 47.
    Welch, R.V., and Dixon, J.R., “Extending the Iterative Redesign Model to Configuration Design: Sheet Metal Brackets as an Example,”Design Theory and Methodology—DTM '89, Vol. 17, 1989Google Scholar
  48. 48.
    Wood, K.L., Antonsson, E.K., and Beck, J.L., “Representing Imprecision in Engineering Design—Comparing Fuzzy and Probability Calculus,”Research in Engineering Design, Vol. 1, Nos. 3/4, 1990Google Scholar

Copyright information

© Springer-Verlag New York Inc. 1991

Authors and Affiliations

  • Deborah L. Thurston
    • 1
  1. 1.Decision Systems Laboratory, Department of General EngineeringUniversity of Illinois at Urbana-ChampaignUrbanaUSA

Personalised recommendations