Research Papers

Impacting Designer Creativity Through IT-Enabled Concept Generation

[+] Author and Article Information
Ken English, Aziz Naim, Kemper Lewis

 University at Buffalo, Buffalo, NY 14260

Susanne Schmidt, Vimal Viswanathan, Julie Linsey, Daniel A. McAdams

 Texas A&M University, College Station, TX 77843-3123

Bryan Bishop, Matthew I. Campbell

 University of Texas at Austin, Austin, TX 78712-0292

Kerry Poppa, Robert B. Stone

 Oregon State University, Corvallis, OR 97331

Seth Orsborn

 Bucknell University, Lewisburg, PA 17837

J. Comput. Inf. Sci. Eng 10(3), 031007 (Sep 03, 2010) (10 pages) doi:10.1115/1.3484089 History: Received July 28, 2009; Revised August 02, 2010; Published September 03, 2010; Online September 03, 2010

One of the innovation’s fundamental mechanisms, designer creativity, is both unsupported by rigorous information-technology-enabled tools and uncharacterized as a scientific phenomenon. In this paper, we present VISUALIZEIT —a project seeking to identify a scientific basis and develop the supporting cyberinfrastructure needed to facilitate, evaluate, and disseminate information-technology-enabled innovation methodologies that augment designer creativity. This particular research paper describes a method of synthesizing concept representations through the development and expansion of platforms focused on computational concept generation, clustering of design concepts, a repository of archived design knowledge, and an information integration and representation interface. We also present the initial results from implementing VISUALIZEIT using two populations of students.

Copyright © 2010 by American Society of Mechanical Engineers
Topics: Creativity , Design
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Figure 1

Overview of VISUALIZEIT approach

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Figure 2

The functional model (left) and CFG (right) for a hair dryer are shown. Two of the rules that are empirically extracted from the graphs are captured by the dashed arrows.

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Figure 3

Example segment of concept description message

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Figure 4

VISUALIZEIT web interface

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Figure 5

Functional model of a peanut sheller

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Figure 6

VISUALIZEIT interface showing a candidate solution (a CFG)

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Figure 11

Participant opinion on if the picture-based CFGs assisted with generating ideas

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Figure 7

Peanut sheller design problem

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Figure 8

The number of ideas as a function of condition. Error bars are ±1 one standard error.

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Figure 9

Mean number of ideas as a function of condition and location. Error bars are ±1 standard error.

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Figure 10

Some example results. The VISUALIZEIT software tended to focus participants on more abstract system representations (center).




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