Advertisement

Guidelines for Process Selection

  • Ian Gibson
  • David Rosen
  • Brent Stucker

Abstract

AM processes, like all materials processing, are constrained by material properties, speed, cost, and accuracy. The performance capabilities of materials and machines lag behind conventional manufacturing technology (e.g., injection molding machinery), although the lag is decreasing. Speed and cost, in terms of time to market, are where AM technology contributes, particularly for complex or customized geometries.

Keywords

Utility Theory Selective Laser Melting Ratio Scale Certainty Equivalent Geometric Complexity 
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.

References

  1. 1.
    Wohlers T (2013) State of the industry—2013 Worldwide progress report, Wohlers Associates, Fort CollinsGoogle Scholar
  2. 2.
    Keeney RL, Raiffa H (1976) Decisions with multiple objectives: preferences and value tradeoffs. Wiley, New YorkMATHGoogle Scholar
  3. 3.
    Hazelrigg G (1996) Systems engineering: an approach to information-based design. Prentice Hall, Upper Saddle RiverGoogle Scholar
  4. 4.
    Mistree F, Smith WF, Bras BA (1993) A decision-based approach to concurrent engineering. In: Paresai HR, Sullivan W (eds) Handbook of concurrent engineering. Chapman and Hall, New York, pp 127–158CrossRefGoogle Scholar
  5. 5.
    Marston M, Allen JK, Mistree F (2000) The decision support problem technique: integrating descriptive and normative approaches. Eng Valuation Cost Anal, Special Issue on Decisions-Based Design: Status and Promise 3:107–129Google Scholar
  6. 6.
    Mistree F, Smith WF, Bras BA, Allen JK, Muster D (1990) Decision-based design: a contemporary paradigm for ship design. Trans Soc Naval Arch Marine Eng 98:565–597Google Scholar
  7. 7.
    Bascaran E, Bannerot RB, Mistree F (1989) Hierarchical selection decision support problems in conceptual design. Eng Optim 14:207–238CrossRefGoogle Scholar
  8. 8.
    Deglin A, Bernard A (2000) A knowledge-based environment for modelling and computer-aided process planning of rapid manufacturing processes, CE’2000 conference, LyonGoogle Scholar
  9. 9.
    Fuh JYH, Loh HT, Wong YS, Shi DP, Mahesh M, Chong TS (2002) A web-based database system for RP machines, processes, and materials selection, Chap 2. In: Gibson I (ed) Software solutions for RP. Professional Engineering, LondonGoogle Scholar
  10. 10.
    Xu F, Wong YS, Loh HT (1999) A knowledge-based decision support system for RP&M process selection. In: Proceedings solid freeform fabrication symposium, Austin, Aug 9–11Google Scholar
  11. 11.
    Allen JK (1996) The decision to introduce new technology: the fuzzy preliminary selection decision support problem. Eng Optim 26(1):61–77CrossRefGoogle Scholar
  12. 12.
    Williams CB (2007) Design and development of a layer-based additive manufacturing process for the realization of metal parts of designed mesostructure, PhD dissertation, Georgia Institute of TechnologyGoogle Scholar
  13. 13.
    Herrmann A, Allen JK (1999) Selection of rapid tooling materials and processes in a distributed design environment. ASME design for manufacturing conference, paper #DETC99/DFM-8930, Las Vegas, Sept. 12–15Google Scholar
  14. 14.
    von Neumann J, Morgenstern O (1947) The theory of games and economic behavior. Princeton University, PrincetonMATHGoogle Scholar
  15. 15.
    Luce RD, Raiffa H (1957) Games and decisions. Wiley, New YorkMATHGoogle Scholar
  16. 16.
    Savage LJ (1954) The foundations of statistics. Wiley, New YorkMATHGoogle Scholar
  17. 17.
    Fernandez MG, Seepersad CC, Rosen DW, Allen JK, Mistree F (2001) Utility-based decision support for selection in engineering design. ASME design automation conference, paper #DETC2001/DAC-21106, Pittsburgh, Sept. 9–12Google Scholar
  18. 18.
    Thurston DL (1991) A formal method for subjective design evaluation with multiple attributes. Res Eng Des 3(2):105–122CrossRefGoogle Scholar
  19. 19.
    Wilson J, Rosen DW (2005) Selection for rapid manufacturing under epistemic uncertainty. Proceedings ASME design automation conference, paper DETC2005/DFMLC-85264, Long Beach, Sept. 24–28Google Scholar
  20. 20.
    Rosen DW, Gibson I (2002) Decision support and system selection for RP, Chapter 4. In: Gibson I (ed) Software solutions for RP. Professional Engineering, LondonGoogle Scholar
  21. 21.
    Rosen DW (2005) Direct digital manufacturing: issues and tools for making key decisions. Proceedings SME rapid prototyping and manufacturing conference, Dearborn, May 9–12Google Scholar
  22. 22.
    Dutta D, Prinz FB, Rosen D, Weiss L (2001) Layered manufacturing: current status and future trends. ASME J Comput Inf Sci Eng 1(1):60–71CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Ian Gibson
    • 1
  • David Rosen
    • 2
  • Brent Stucker
    • 3
  1. 1.School of EngineeringDeakin UniversityVictoriaAustralia
  2. 2.George W. Woodruff School of Mechanical EngineeringGeorgia Institute of TechnologyAtlantaUSA
  3. 3.Department of Industrial Engineering, J B SpeedUniversity of LouisvilleLouisvilleUSA

Personalised recommendations