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Research Papers: Design Theory and Methodology

Characterizing the Effects of Multiple Analogs and Extraneous Information for Novice Designers in Design-by-Analogy

[+] Author and Article Information
Hyeon Ik Song

School of Mechanical Engineering,
Georgia Institute of Technology,
Atlanta, GA 30332-0405
e-mail: hyeoniksong@gatech.edu

Ricardo Lopez

Department of Mechanical Engineering,
Texas A&M University,
College Station, TX 77843-3123
e-mail: r.lopez87@gmail.com

Katherine Fu

School of Mechanical Engineering,
Georgia Institute of Technology,
Atlanta, GA 30332-0405
e-mail: katherine.fu@me.gatech.edu

Julie Linsey

School of Mechanical Engineering,
Georgia Institute of Technology,
Atlanta, GA 30332-0405
e-mail: julie.linsey@me.gatech.edu

1Corresponding author.

Contributed by the Design Theory and Methodology Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received May 16, 2017; final manuscript received November 15, 2017; published online December 21, 2017. Assoc. Editor: Katja Holtta-Otto.

J. Mech. Des 140(3), 031101 (Dec 21, 2017) (13 pages) Paper No: MD-17-1340; doi: 10.1115/1.4038565 History: Received May 16, 2017; Revised November 15, 2017

This study examines how the quantity of ideas and analog transfer in design-by-analogy (DbA) are affected by multiple analogs and extraneous information, or noise, using a between-subjects, factorial experiment. To evaluate the effects of multiple analogs and noise on ideation, the study uses two metrics in conjunction with one another; namely, number of ideas (most typical in engineering design) and recognition of high-level principle (more common in psychology). The quantity analysis included three components: number of ideas generated, number of ideas that use example products (analogs and noise stimuli), and number of ideas that use analogs. The results indicate two important findings: (1) providing multiple analogs during ideation had a positive impact on ideation quantity and analog transfer. Specifically, the number of analog-based ideas increased with increasing number of analogs but eventually reached a “saturation point”; (2) introducing extraneous information (noise) diminished the successful mapping of analogs to design solutions. The presence of extraneous information did not significantly affect student designers' ability to identify high-level principles in analogs. The study demonstrated that some extraneous information was perceived as surface similar analogs. Any design analog retrieval method or automated tool will produce extraneous information, and more work is needed to understand and minimize its impact.

Copyright © 2018 by ASME
Topics: Noise (Sound) , Design
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Figures

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Fig. 1

Schematic of the analogical reasoning process. Adapted from Ref. [16].

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Fig. 2

Design problem statement

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Fig. 3

Drawing of locking mechanism

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Fig. 4

Analogs used as stimuli in study

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Fig. 5

Pure noise used as stimuli in study

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Fig. 6

Noise with elasticity as surface feature used as stimuli in study

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Fig. 7

Sample ideation sketches

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Fig. 8

Number of ideas generated, error bars show ± one standard error

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Fig. 9

Number of ideas that use example products, error bars show ± one standard error

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Fig. 10

Number of ideas that analogs, error bars show ± one standard error

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Fig. 11

Percentage of high-level principle recognition rate in stage I

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Fig. 12

The mean similarity ratings between ideas and example product, error bars show ± one standard error

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Fig. 13

Number of ideas that use analogs, pure noise, and noise w/surface feature over time, error bars show ± one standard error

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Fig. 14

Rating of example product's usefulness, error bars show ± one standard error

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Fig. 15

Rating of use of given example products, error bars show ± one standard error

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Fig. 16

Rating of difficulty of similarity task, error bars show ± one standard error

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Fig. 17

Number of analogs used in idea generation, error bars show ± one standard error

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