An empirical understanding of use of internal analogies in conceptual design

V. Srinivasan, Amaresh Chakrabarti, Udo Lindemann

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

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.

Original languageEnglish
Pages (from-to)147-160
Number of pages14
JournalArtificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
Volume29
Issue number2
DOIs
StatePublished - 27 Apr 2015

Keywords

  • Experience
  • Ideas
  • Internal Analogy
  • Natural and Artificial Domains
  • Problem
  • Variety

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