Research in Engineering Design

, Volume 15, Issue 4, pp 216–228 | Cite as

Life-cycle modeling for adaptive and variant design. Part 1: Methodology

Original Papers


Life-cycle modeling for design (LCMD) is a methodology for assessing the life-cycle impacts for a complex product with many individual components starting from initial design phases when few design specifications have been made. The methodology combines life-cycle assessment (LCA) with probabilistic design methods in a way that forecasts attributes of possible final designs yet reduces information needs. Specifically, LCMD is a methodology for generating arrays of design scenarios that communicate the range of designs being considered by a design team, and estimating missing data for those design scenarios. The main contribution to enhancing standard LCA is the incorporation of methods to estimate physical attributes of individual components for various design options and in four analyses for evaluating the arrays of design scenarios. An automotive case study presented in part 2 of this work demonstrates one application of LCMD.


Life-cycle assessment Adaptive design Variant design Probabilistic design 



The Ford Motor Company of Dearborn, Michigan provided financial support for this work. Special thanks are due to Drs. John Sullivan and Dennis Schutzle of the Ford Motor Company for their interest and support in shaping this research.


  1. Ashby M (1999) Materials selection in mechanical design. Butterworth-Heinemann, BostonGoogle Scholar
  2. Azapagic A, Clift R (1999) Life cycle assessment and multiobjective optimisation. J Cleaner Production 7:135–143CrossRefGoogle Scholar
  3. Barton JA, Love DM (2000) Design decision chains as a basis for design analysis. J Eng Des 11:283–297CrossRefGoogle Scholar
  4. Booker JD (2001) Designing capable and reliable products. Butterworth Heinemann, BostonGoogle Scholar
  5. Borg JC, Yan X, Juster NP (2000) Exploring decisions’ influence on life-cycle performance to aid “design for multi-X. Artif Intell Eng Des Anal Manufact 14:91–113Google Scholar
  6. Borland N, Wallace D, Kaufmann HP (1998) Integrating environmental impact assessment into product design. Proceedings of 1998 ASME design engineering technical conference, Atlanta, pp 13–16Google Scholar
  7. Bras, B (1997) Incorporating environmental issues in product design and realization. Ind Environ 20:7–13Google Scholar
  8. Brown RJ, Yanuck RR (1985) Introduction of life cycle costing.Prentice-Hall, Englewood CliffsGoogle Scholar
  9. Cacuci DG (2003) Sensitivity and uncertainty analysis. Chapman and Hall, Boca RatonGoogle Scholar
  10. Cooper JS (2003) Specifying functional units and reference flows for comparable alternatives. Int J Life Cycle Assess 8:337–349Google Scholar
  11. Curran MA (1996) Life cycle assessment. McGraw-Hill, New YorkGoogle Scholar
  12. Davis J (1991) The potential for vehicle weight reduction using magnesium. Society of Automotive Engineers, SAE#910551Google Scholar
  13. Eisenhard JL, Wallace DR, Sousa I, De Schepper MS, Rombouts JP (2000) Approximate life-cycle assessment in conceptual product design. Proceedings of ASME 2000 Design engineering technical conferences and computers and information in engineering conference, September 10–13, BaltimoreGoogle Scholar
  14. Fabryck WJ, Blanchard BS (1991) Life-cycle cost and economic analysis. Prentice-Hall, New JerseyGoogle Scholar
  15. Fitch PE (2004) Design forecasting: a method for performing dfx analyses in complex product design. Ph.D. Dissertation in Mechanical Engineering, University of WashingtonGoogle Scholar
  16. Fitch PE, Cooper JS (2004) Life cycle energy analysis as a method for material selection. J Mech Des (in press)Google Scholar
  17. Ford Motor Company (1988) Failure mode and effects analysis handbook. Dearborne, MichiganGoogle Scholar
  18. Graedel TE, Allenby BR (1996) Design for environment. Prentice Hall, New JerseyGoogle Scholar
  19. Hauser J, Clausing D (1988) “The house of quality,” Harvard Business Review, pp 63–73Google Scholar
  20. Hinckley CM (1994) A global conformance quality model: a new strategic tool for minimizing defects caused by variation, error, and complexity. Ph.D. Dissertation in Mechanical Engineering, Stanford UniversityGoogle Scholar
  21. ISO (International Standards Organization) (1997) ISO14040: life cycle assessment—principles and frameworkGoogle Scholar
  22. ISO (International Standards Organization) (1998) Environmental management— life cycle assessment—goal and scope definition and inventory analysis, ISO14041–1998 (E)Google Scholar
  23. Ishii K (1998) Design for manufacturability: product definition. Course notes for ME217A in Department of Mechanical Engineering, Stanford UniversityGoogle Scholar
  24. Jackson P, Wallace DR (1997) A modular method for representing product life-cycles. Proceedings of the 1997 ASME design engineering technical conferences, Sacramento, pp 14–17Google Scholar
  25. Kalyan-Seshu U, Bras B (1998) Integrating DFX tools with computer-aided design systems. Proceedings of the 1998 ASME design engineering technical conferences, Atlanta, pp 13–16Google Scholar
  26. Klöpffer W, Hutzinger O (1997) LCA documents: life cycle assessment: state-of-the-art and research priorities. Eco-Informa, BayreuthGoogle Scholar
  27. Nielsen PH, Wenzel H (2002) Integration of environmental aspects in product development: a stepwise procedure based on quantitative life cycle assessment. J Cleaner Production 10:247–257CrossRefGoogle Scholar
  28. Otto KN, Wood KL (2001) Product design: techniques in reverse engineering and new product development. Prentice Hall, New JerseyGoogle Scholar
  29. Pahl G, Beitz W (2001) Engineering design: a systematic approach. Springer, New YorkGoogle Scholar
  30. Pugh S (1991) Total design: integrated methods for successful product engineering. Addison-Wesley, ReadingGoogle Scholar
  31. Pugh S (1996) Creating innovative products using total design. Addison-Wesley, ReadingGoogle Scholar
  32. Regnier E, Hoffman III WF (1998) Uncertainty model for product environmental performance scoring. 1998 IEEE international symposium on electronics and the environment, Oak BrookGoogle Scholar
  33. Saaty TL (1980) The analytic hierarch process: planning, priority setting, resource allocation. McGraw-Hill, New YorkGoogle Scholar
  34. Saaty TL (1995) Decision Making for Leaders. Lifetime Learning, BelmontGoogle Scholar
  35. Saltelli A, Chan K, Scott EM (2000) Sensitivity analysis. Wiley, ChichesterGoogle Scholar
  36. Seiford LM, Thrall RM (1990) Recent developments in DEA the mathematical programming approach to frontier analysis. J Econom 26: 7–38CrossRefGoogle Scholar
  37. SETAC (Society of Environmental Toxicology and Chemistry) (1991) Guidelines for life cycle assessment: a code of practice. BrusselsGoogle Scholar
  38. SAWE (Society of Allied Weight Engineers) (1996) Introduction to aircraft weight engineering. Los AngelesGoogle Scholar
  39. Stamatis D (1995) Failure mode and effects analysis: FMEA from theory to execution. ASQC Quality, MilwaukeeGoogle Scholar
  40. Sullivan JL, Williams RL, Yester S, Cobas-Flores E, Chubbs ST, Hentges SG, Pomper SD (1998) Life cycle inventory of a generic US family sedan: overview of results USCAR AMP project, Society of Automotive Engineers, SAE#982160Google Scholar
  41. Ullman DG (1997) The mechanical design process. McGraw-Hill, New YorkGoogle Scholar
  42. Umeda Y, Nonomura A, Tomiyana T (2000) Study on life-cycle design for the post mass production paradigm. Artif Intell Eng Des Anal Manufact 14:149–161Google Scholar

Copyright information

© Springer-Verlag London Limited 2005

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringUniversity of WashingtonSeattleUSA

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