Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-04T18:37:09.824Z Has data issue: false hasContentIssue false
  • English
  • Français

Computational model for conceptual design based on extended function logic

Published online by Cambridge University Press:  27 February 2009

Robert H. Sturges ,
Kathleen O'Shaughnessy  and
Mohammed I. Kilani
Robert H. Sturges
Affiliation:
Engineering Design Research Center, Carnegie Mellon University, Pittsburgh, PA 15213, U.S.A.
Kathleen O'Shaughnessy
Affiliation:
Booz-Allen-Hamilton, Germantown, MD 20874, U.S.A.
Mohammed I. Kilani
Affiliation:
University of Jordan, Department of Mechanical Engineering, Amman, Jordan
Get access Rights & Permissions [Opens in a new window]

Abstract

Function logic methods have been successfully used in Value Analysis (VA) and Value Engineering (VE) for several decades. This functional approach attempts to provide a common language for specialists in multiple domains. This paper describes an extension of function logic that assists in systematic identification of design functions, allocations, and their interrelations. Our approach identifies a three-level function/allocation/component information structure to represent the state of the design. We illustrate new types of links that exist between functions and the effect of these on the representation of the interrelated functions. These linkages provide new pathways for design information and function evaluation through allocation arithmetic and supported functions. A computational model of the conceptual design process is proposed based on the extended function logic design representation. An outline of the inputs, outputs and operations on form and function variables is given as a step prior to the synthesis process. We illustrate, by example, the process of translating functional representations across specialist domains. Finally, a computer-based aid to developing functional models is described.

Keywords

ConceptualDesignFunctionValue
Type
Articles
Information
AI EDAM , Volume 10 , Issue 4: Special Issue: Representing functionality in design , September 1996 , pp. 255 - 274
Copyright
Copyright © Cambridge University Press 1996

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Beggs, R.M., Ciric, C., Etzl, J., Fischer, C., & McCoy, T. (1989). Automated design development support system (ADDSS). Boeing Vertol Company, Philadelphia, PA 19142.Google Scholar
Bytheway, C.W. (1971). The creative aspects of FAST diagramming, Proc. Soc. Am. Value Eng. Conf., 301–312.Google Scholar
Dao, H., & Sturges, R.H. (1994). A function logic modelling and allocation system based on n-Dim. Carnegie Mellon University Engineering Design Research Center, December, 1994.Google Scholar
Finger, S., & Dixon, J.R. (1989). A review of research in mechanical engineering design. Part I: Descriptive, prescriptive and computer-based models of design processes. Res. Eng. Design 1, 51–67.CrossRefGoogle Scholar
Fowlkes, J.K., Ruggles, W.F., Groothuis, J.D. (1972). Advanced fast diagramming. Proc. Save Conference, Newport Beach, CA, 45–52.Google Scholar
Furnas, G.W. (1986). Generalized fisheye views. Human factors in computing systems. ACM Proceedings CHI 1986.CrossRefGoogle Scholar
Garg, P.K., and Scacchi, W. (1989). Designing an intelligent software hypertext system. IEEE Expert Syst. 4(3), 52–63.CrossRefGoogle Scholar
Jakobsen, K., Sigurjónsson, J., & Jakobsen, Ø. (1991). Formalized specifications of functional requirements. Design Stud., 12(4), 221–224.CrossRefGoogle Scholar
Kantowitz, B.H., & Sorkin, R.D. (1987).Allocation of functions. In Handbook of Human Factors, (Salvendy, G.I., Ed.), pp. 355–369. John Wiley & Sons, New York.Google Scholar
Kaufman, J.J. (1982). Function analysis system technique (FAST) for management application and Function analysis system technique (FAST) for management application, (Part I, pp. 14–22; Part II, pp. 14–25). Value World July/September and October/December.Google Scholar
Meister, D. (1985). Behavior analysis and measurement methods. John Wiley & Sons, New York.Google Scholar
Miles, L.D. (1982). Techniques of value analysis, 2nd ed. Mc-Graw Hill Book Company, New York.Google Scholar
Paz-Soldan, J.P., & Rinderle, J.R. (1989). The alternate use of abstraction and refinement in conceptual mechanical design. ASME WAM, San Francisco, CA, Dec, 1989. EDRC 24–22–90, Carnegie Mellon University Engineering Design Research Center, September.Google Scholar
Prendergast, J.F., & Westinghouse Corporate Value Analysis Staff. (1982). Value analysis handbook. Westinghouse Productivity and Quality Center, Pittsburgh, PA.Google Scholar
Reed, R.G., & Sturges, R.H. (1994). A model for performance-intelligent design advisors. CERA, 2(1), 59–66.Google Scholar
Ruggles, W.F. (1971). A management planning tool. Proc. SAVE Conf., 312–316.Google Scholar
Sturges, R.H., O'Shaughnessy, K., & Kilani, M.I. (1990). Representation of aircraft design data for supportability, operability, and producibility evaluations. EDRC Report No. 14513, Carnegie Mellon University Engineering Design Research Center.Google Scholar
Sturges, R.H. (1993). The function of value engineering. ASME DAC, Albuquerque, NM, Sept 19–22, 1993.Google Scholar
Sturges, R.H., O'Shaughnessy, K., & Reed, R.G. (1993). A systematic approach to conceptual design. CERA 1(2), 93–106.Google Scholar
Subrahmanian, E., Podnar, G., & Westerberg, A. (1989). n-DIM: n-Dimensional information modeling— A shared computational environment for design. Carnegie Mellon University Engineering Design Research Center, September 1989.Google Scholar
Ullman, D.G., Dietterich, T.G., & Stauffer, L.A. (1988). A model of the mechanical design process based on empirical data. Al EDAM 2(1), 33–52.Google Scholar
Westerberg, A., Grossmann, I., Talukdar, S., Prinz, F., Fenves, S., & Maher, M.L. (1989). Applications of artificial intelligence in design research at Carnegie Mellon University's EDRC. Carnegie Mellon University Engineering Design Research Center.Google Scholar