Skip to main content Accessibility help
×
Home
Hostname: page-component-56f9d74cfd-dpvgk Total loading time: 0.38 Render date: 2022-06-27T04:03:14.878Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "useRatesEcommerce": false, "useNewApi": true }

Article contents

An empirical understanding of use of internal analogies in conceptual design

Published online by Cambridge University Press:  27 April 2015

V. Srinivasan*
Affiliation:
Institute of Product Development, Technische Universität München, Munich, Germany
Amaresh Chakrabarti
Affiliation:
Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore, India
Udo Lindemann
Affiliation:
Institute of Product Development, Technische Universität München, Munich, Germany
*
Reprint requests to: V. Srinivasan, Institute of Product Development, Technische Universität München, Boltzmannstrasse 15, 85748 Garching, Germany. E-mail: srinivasan.venkataraman@pe.mw.tum.de

Abstract

Internal analogies are created if the knowledge of source domain is obtained only from the cognition of designers. In this paper, an understanding of the use of internal analogies in conceptual design is developed by studying: the types of internal analogies; the roles of internal analogies; the influence of design problems on the creation of internal analogies; the role of experience of designers on the use of internal analogies; the levels of abstraction at which internal analogies are searched in target domain, identified in source domain, and realized in the target domain; and the effect of internal analogies from the natural and artificial domains on the solution space created using these analogies. To facilitate this understanding, empirical studies of design sessions from earlier research, each involving a designer solving a design problem by identifying requirements and developing conceptual solutions, without using any support, are used. The following are the important findings: designers use analogies from the natural and artificial domains; analogies are used for generating requirements and solutions; the nature of the design problem influences the use of analogies; the role of experience of designers on the use of analogies is not clearly ascertained; analogical transfer is observed only at few levels of abstraction while many levels remain unexplored; and analogies from the natural domain seem to have more positive influence than the artificial domain on the number of ideas and variety of idea space.

Type
Special Issue Articles
Copyright
Copyright © Cambridge University Press 2015 

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

Ahmed, S., & Christensen, B. (2008). Use of analogies by novice and experienced design engineers. Proc. ASME 2008 Int. Design Engineering Technology Conf. and Computers and Information in Engineering Conf., IDETC/CIE 2008. New York: ASME.Google Scholar
Chakrabarti, A., Sarkar, P., Leelavathamma, B., & Nataraju, B.S. (2005). A functional representation for aiding biomimetic and artificial inspiration of new ideas. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 19(2), 113132.CrossRefGoogle Scholar
Christensen, B.T., & Schunn, C.D. (2007). The relationship of analogical distance to analogical function and preinventive structure: the case of engineering design. Memory & Cognition 35(1), 2938.CrossRefGoogle ScholarPubMed
French, M. (1988). Conceptual Design for Engineers, 3rd ed.London: Springer–Verlag.Google Scholar
Gentner, D. (1989). The mechanisms of analogical learning. In Similarity and Analogical Reasoning (Vosniadou, S., & Ortony, A., Eds.), pp. 199241. New York: Cambridge University Press.CrossRefGoogle Scholar
Goel, A.K. (1997). Design, analogy and creativity. IEEE Expert 12(3), 6270.CrossRefGoogle Scholar
Helms, M., & Goel, A. (2012). Analogical problem evolution in biologically inspired design. Proc. Design Computing and Cognition 2012, DCC12, pp. 317. Dordrecht: Springer.Google Scholar
Helms, M., & Goel, A. (2013). Grounded knowledge representations for biologically inspired design. Proc. Int. Conf. Engineering Design 2013, ICED13, pp. 351–360. Seoul: Design Society.Google Scholar
Howard, T.J., Dekoninck, E.A., & Culley, S.J. (2010). The use of creative stimuli at early stages of industrial product innovation. Research in Engineering Design 21(4), 263274.CrossRefGoogle Scholar
Jansson, D., & Smith, S. (1991). Design fixation. Design Studies 12(1), 311.CrossRefGoogle Scholar
Kletke, M.G., Mackay, J.M., Barr, S.H., & Jones, B. (2001). Creativity in the organization: the role of individual creative problem solving and computer support. International Journal of Human–Computer Studies 55(3), 217237.CrossRefGoogle Scholar
Lopez, R., Linsey, J., & Smith, S. (2011). Characterizing the effect of domain distance in design-by-analogy. Proc. Int. Design Engineering Technology Conf. and Computers and Information in Engineering Conf. 2011, IDETC/CIE 2011, pp. 141–151. Washington, DC: ASME.Google Scholar
Nelson, B.A., Yen, J., Wilson, J.O., & Rosen, D. (2009). Refined metrics for measuring ideation effectiveness. Design Studies 30(6), 737743.CrossRefGoogle Scholar
Pahl, G., Beitz, W., Feldhusen, J., & Grote, K.H. (2007). Engineering Design: A Systematic Approach, 3rd ed.London: Springer–Verlag.CrossRefGoogle Scholar
Qian, L., & Gero, J. (1996). Function–behavior–structure paths and their role in analogy-based design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10(4), 289312.CrossRefGoogle Scholar
Sarkar, P., & Chakrabarti, A. (2007). Understanding search in design. Proc. Int. Conf. Engineering Design 2007, ICED07. Paris: Design Society.Google Scholar
Sarkar, P., & Chakrabarti, A. (2008). The effect of representation of triggers on design outcomes. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 22(2), 101116.CrossRefGoogle Scholar
Sarkar, P., & Chakrabarti, A. (2011). Assessing design creativity. Design Studies 32(4), 348383.CrossRefGoogle Scholar
Sartori, J., Pal, U., & Chakrabarti, A. (2010). A methodology for supporting transfer in biomimetic design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 24(4), 483505.CrossRefGoogle Scholar
Shah, J., Vargas-Hernandez, N., & Smith, S.M. (2003). Metrics for measuring ideation effectiveness. Design Studies 24(2), 111134.CrossRefGoogle Scholar
Srinivasan, V., & Chakrabarti, A. (2009). SAPPhIRE—an approach to analysis and synthesis. Proc. Int. Conf. Engineering Design, ICED09, pp. 417–428. Los Angeles: Design Society.Google Scholar
Srinivasan, V., & Chakrabarti, A. (2010 a). An integrated model of designing. Journal of Computing and Information Science in Engineering 10(3), 115124.CrossRefGoogle Scholar
Srinivasan, V., & Chakrabarti, A. (2010 b). Investigating novelty–outcome relationships in engineering design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 24(2), 161178.CrossRefGoogle Scholar
Tseng, I., Moss, J., Cagan, J., & Kotovsky, K. (2008). Overcoming blocks in conceptual design: the effects of open goals and analogical similarity on idea generation. Proc. Int. Design Engineering Technology Conf. Computers and Information in Engineering Conf., IDETC/CIE 2008, pp. 3–9. New York: ASME.CrossRefGoogle Scholar
VanGundy, A.B. (1981). Techniques of Structured Problem Solving. New York: Van Nostrand Reinhold.Google Scholar
Vattam, S., & Goel, A. (2013). Seeking bioinspiration online: a descriptive account. Proc. Int. Conf. Engineering Design 2013, ICED13, pp. 347–356. Seoul: Design Society.Google Scholar
Vattam, S., Helms, M., & Goel, A. (2010). A content account of creative analogies in biologically inspired design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 24(4), 467481.CrossRefGoogle Scholar
Vattam, S., Wiltgen, B., Helms, M., Goel, A., & Yen, J. (2011). DANE: fostering creativity in and through biologically inspired design. In Design Creativity 2010 (Taura, T., & Nagai, Y., Eds.), pp. 115122. London: Springer–Verlag.CrossRefGoogle Scholar
Verhaegen, P.-A., Vandevenne, D., Peeters, J., & Duflou, J.R. (2013). Refinements to the variety metric for idea evaluation. Design Studies 34(2), 243263.CrossRefGoogle Scholar
Wilson, J.O., Rosen, D., Nelson, B., & Yen, J. (2010). The effects of biological examples in idea generation. Design Studies 31(2), 169186.CrossRefGoogle Scholar
Young, L. (1987). The metaphor machine: a database method for creativity support. Decision Support Systems 3(4), 309317.CrossRefGoogle Scholar
4
Cited by

Save article to Kindle

To save this article to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

An empirical understanding of use of internal analogies in conceptual design
Available formats
×

Save article to Dropbox

To save this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about saving content to Dropbox.

An empirical understanding of use of internal analogies in conceptual design
Available formats
×

Save article to Google Drive

To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about saving content to Google Drive.

An empirical understanding of use of internal analogies in conceptual design
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *