Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-27T20:24:11.777Z Has data issue: false hasContentIssue false
  • English
  • Français

Automating the conceptual design process: “From black box to component selection”

Published online by Cambridge University Press:  29 January 2010

Tolga Kurtoglu ,
Albert Swantner  and
Matthew I. Campbell
Tolga Kurtoglu
Affiliation:
Mission Critical Technologies, NASA Ames Research Center, Intelligent Systems Division, Moffett Field, California, USA
Albert Swantner
Affiliation:
Automated Design Laboratory, Department of Mechanical Engineering, University of Texas at Austin, Austin, Texas, USA
Matthew I. Campbell
Affiliation:
Automated Design Laboratory, Department of Mechanical Engineering, University of Texas at Austin, Austin, Texas, USA
Get access Rights & Permissions [Opens in a new window]

Abstract

Conceptual design is a vital part of the design process during which designers first envision new ideas and then synthesize them into physical configurations that meet certain design specifications. In this research, a suite of computational tools is developed that assists the designers in performing this nontrivial task of navigating the design space for creating conceptual design solutions. The methodology is based on automating the function-based synthesis paradigm by combining various computational methods. Accordingly, three nested search algorithms are developed and integrated to capture different design decisions at various stages of conceptual design. The implemented system provides a method for automatically generating novel alternative solutions to real design problems. The application of the approach to the design of an electromechanical device shows the method's range of capabilities and how it serves as a comparison to human conceptual design generation and as a tool suite to complement the skills of a designer.

Keywords

Automated DesignConcept GenerationFunctional DesignGraph Grammars
Type
Special Issue Articles
Information
AI EDAM , Volume 24 , Issue 1: Design Computing and Cognition , February 2010 , pp. 49 - 62
Copyright
Copyright © Cambridge University Press 2010

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

Agarwal, M., & Cagan, J. (1998). A blend of different tastes: the language of coffee makers. Environment and Planning B: Planning and Design 25(2), 205–226.CrossRefGoogle Scholar
Bhatta, S., Goel, A., & Prabhakar, S. (1994). Innovation in analogical design: a model-based approach. Proc. AI in Design. Dordrecht: Kluwer Academic, pp. 57–74.Google Scholar
Bracewell, R.H., & Sharpe, J.E.E. (1996). Functional description used in computer support for qualitative scheme generation—Schemebuilder. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10(4), 333–345.CrossRefGoogle Scholar
Brown, K.N., & Cagan, J. (1997). Optimized process planning by generative simulated annealing. Artificial Intelligence in Engineering Design, Analysis and Manufacturing 11, 219–235.CrossRefGoogle Scholar
Bryant, C., Stone, R., McAdams, D., Kurtoglu, T., & Campbell, M. (2005). A computational technique for concept generation. ASME 2005 Int. Design Engineering Technical Conf., Long Beach, CA.CrossRefGoogle Scholar
Campbell, M., Cagan, J., & Kotovsky, K. (2000). Agent-based synthesis of electro-mechanical design configurations. Journal of Mechanical Design 122(1), 61–69.CrossRefGoogle Scholar
Campbell, M.I. (2007). The official GraphSynth Site, University of Texas at Austin. Accessed at http://www.graphsynth.comGoogle Scholar
Carlson, S.E. (1996). Genetic algorithm attributes for component selection. Research in Engineering Design 8(1), 33–51.CrossRefGoogle Scholar
Carlson-Skalak, S., White, M.D., & Teng, Y. (1998). Using an evolutionary algorithm for catalog design. Research in Engineering Design 10(2), 63–83.CrossRefGoogle Scholar
Chakrabarti, A., & Bligh, T. (1996). An approach to functional synthesis of mechanical design concepts: theory, applications and emerging research issues. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10, 313–331.CrossRefGoogle Scholar
Dallaali, M.A., & Premaratne, M. (2004). Double-constrained optimization of optical component selection problem using genetic elitism and double string coding. Int. Conf. Numerical Simulation of Ootoelectronic Devices '04.CrossRefGoogle Scholar
Hirtz, J., Stone, R., McAdams, D., Szykman, S., & Wood, K. (2002). A functional basis for engineering design: reconciling and evolving previous efforts. Research in Engineering Design 13(2), 65–82.CrossRefGoogle Scholar
Hundal, M. (1990). A systematic method for developing function structures, solutions and concept variants. Mechanism and Machine Theory 25(3), 243–256.CrossRefGoogle Scholar
Kirschman, C., & Fadel, G. (1998). Classifying functions for mechanical design. Journal of Mechanical Design, Transactions of the ASME 120(3), 475–482.CrossRefGoogle Scholar
Kitamura, Y., & Mizoguchi, R. (1999). Metafunctions of artifacts. Proc. 13th Int. Workshop on Qualitative Reasoning (QR-99), Loch Awe, Scotland, pp. 136–145.Google Scholar
Kota, S., & Chiou, S.-J. (1992). Conceptual design of mechanisms based on computational synthesis and simulation of kinematic building blocks. Research in Engineering Design, 4, 75–87.CrossRefGoogle Scholar
Kurtoglu, T. (2007). An computational approach to innovative conceptual design. PhD dissertation. Austin, TX: University of Texas at Austin Press.Google Scholar
Kurtoglu, T., & Campbell, M. (2009). An evaluation scheme for assessing the worth of automatically generated design alternatives. Journal of Research in Engineering Design 20, 59–76.CrossRefGoogle Scholar
Kurtoglu, T., Campbell, M., Gonzales, J., Bryant, C., Stone, R., & McAdams, D. (2005). Capturing empirically derived design knowledge for creating conceptual design configurations. ASME 2005 Int. Design Engineering Technical Conf., Long Beach, CA.CrossRefGoogle Scholar
Mittal, S., Dym, C., & Morjara, M. (1985). “PRIDE: an expert system for the design of paper handling systems. IEEE Computer 19(7), 102–114.CrossRefGoogle Scholar
Navinchandra, D., Sycara, K.P., & Narasimhan, S. (1991). A transformational approach to case-based synthesis. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 5(1), 31–45.CrossRefGoogle Scholar
Otto, K., & Wood, K. (1997). Conceptual and configuration design of products and assemblies. ASM Handbook, Materials Selection and Design (Vol. 20). Materials Park, OH: ASM International.Google Scholar
Otto, K., & Wood, K. (2001). Product Design: Techniques in Reverse Engineering and New Product Development. Englewood Cliffs, NJ: Prentice–Hall.Google Scholar
Pahl, G., & Beitz, W. (1996). Engineering Design: A Systematic Approach. Berlin: Springer–Verlag.CrossRefGoogle Scholar
Qian, L., & Gero, J.S. (1996). Function–behavior–structure paths and their role in analogy-based design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10, 289–312.CrossRefGoogle Scholar
Schmidt, L., & Cagan, J. (1995). Recursive annealing: a computational model for machine design. Research in Engineering Design 7(2), 102–125.CrossRefGoogle Scholar
Shea, K., Cagan, J., & Fenves, S.J. (1997). A shape annealing approach to optimal truss design with dynamic grouping of members. ASME Journal of Mechanical Design 119(3), 388–394.CrossRefGoogle Scholar
Sridharan, P., & Campbell, M.I. (2004). A grammar for function structures. Proc. ASME DETC, Salt Lake, UT.Google Scholar
Starling, A.C., & Shea, K. (2003). A grammatical approach to computational generation of mechanical clock designs. Proc. ICED '03 Int. Conf. Engineering Design, Stockholm, Sweden.Google Scholar
Starling, A.C., & Shea, K. (2005). Virtual synthesizers for mechanical gear systems. Proc. ICED’05 Int. Conf. Engineering Design, Melbourne, Australia.Google Scholar
Stone, R., & Wood, K. (1999). Development of a functional basis for design. Proc. Design Engineering Technical Conf., Paper No. DETC99/DTM-8765, Las Vegas, NV.CrossRefGoogle Scholar
Subramanian, D., & Wang, C.-S. (1995). Kinematic synthesis with configuration spaces. Research in Engineering Design 7(3), 193–213.CrossRefGoogle Scholar
Suh, N. (1990). The Principles of Design. New York: Oxford University Press.Google Scholar
Szykman, S., Racz, J., & Sriram, R. (1999). The representation of function in computer-based design. Proc. Design Engineering Technical Conf., DETC99/DTM-8742, Las Vegas, NV.CrossRefGoogle Scholar
Tamhankar, M.S., & Campbell, M.I. (2007). An intelligent and efficient tree search algorithm for computer-aided component selection. ASME Design Engineering Technical Conf. Computers in Engineering, Las Vegas, NV.Google Scholar
Ullman, D. (1995). The Mechanical Design Process. New York: McGraw–Hill.Google Scholar
Ulrich, K., & Eppinger, S. (1995). Product Design and Development. New York: McGraw–Hill.Google Scholar
Umeda, Y., & Tomiyama, T. (1997). Functional reasoning in design. IEEE Expert March–April, 42–48.CrossRefGoogle Scholar
Wang, K., & Yan, J. (2002). An analytical approach to functional design. Proc. ASME Design Engineering Technical Conf., Montreal, CA.CrossRefGoogle Scholar
Ward, A.C., & Seering, W.P. (1989). The performance of a mechanical design compiler. ASME, Design Engineering 17, 89–97.Google Scholar
Wielinga, B.J., & Schreiber, G. (1997). Configuration design problem solving. Technical Report, University of Amsterdam, Department of Social Science Informatics.CrossRefGoogle Scholar
Williams, B.C. (1990). Interaction-based invention: designing novel devices from first principles. AAAI-90 Proc., 8th National Conf. Artificial Intelligence, Vol. 1, pp. 349–356.CrossRefGoogle Scholar