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Exploring Multiple Solutions and Multiple Analogies to Support Innovative Design

  • Apeksha Gadwal
  • Julie Linsey

Abstract

Idea generation and design-by-analogy is a core part of design. Designers need tools to assist them in developing creative and innovative ideas. Multiple solutions can be developed based on single analog and designers derive principles of design from the analogs (products) they experience. There is little research that discusses creating multiple solutions from a single analog or how multiple analogs can assist designers in mapping high level principles of design. This study explores two phases of design-by-analogy in which designers have difficulty, generating multiple inferences from a single source analog and the identification of high level principles given multiple example analogs in the presence of noise. Two hypotheses are proposed to explore the importance of analogies in design. 1. Multiple solutions can be generated from a single analog. 2. The mapping of high level principles increases with the increase in the number of example analogs and decreases with the amount of noise. The paper presents two laboratory experiments, “Multiple Solutions” and “Multiple Analogies” conducted to answer the proposed research questions and to understand how designers can become better analogical reasoners. The experiments are explained in detail with the methods for collecting data, metrics and the analysis. The results from the pilot experiments show that engineers, when directed to, can create multiple solutions from a single analog. This can allow designers to find better solutions and to evaluate their inferences. Results from the second experiment also indicate the mapping of high level principles increases with an increase in the number of analogs and decreases with distracters. A significant interaction is also observed between these two factors. The results indicate more future work with a greater sample size.

Keywords

Design Problem Multiple Solution Structural Alignment Analogical Reasoning Source Analog 
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.

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Copyright information

© Springer Netherlands 2011

Authors and Affiliations

  • Apeksha Gadwal
    • 1
  • Julie Linsey
    • 1
  1. 1.Texas A & M UniversityUSA

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