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Research Papers

A Component Taxonomy as a Framework for Computational Design Synthesis

[+] Author and Article Information
Tolga Kurtoglu

Mission Critical Technologies, NASA Ames Research Center, MS 269-3 Moffett Field, CA 94035tolga.kurtoglu@nasa.gov

Matthew I. Campbell

Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78712 mc1@mail.utexas.edu

Cari Bryant Arnold

Engineering Design Program, Penn State University, University Park, PA 16802cari.arnold@psu.edu

Robert B. Stone

Department of Interdisciplinary Engineering, Missouri University of Science and Technology, Rolla, MO 65409rstone@mst.edu

Daniel A. Mcadams

Department of Mechanical Engineering, Texas A&M University, College Station, TX 7784dmcadams@tamu.edu

J. Comput. Inf. Sci. Eng 9(1), 011007 (Mar 06, 2009) (10 pages) doi:10.1115/1.3086032 History: Received July 13, 2006; Revised March 03, 2008; Published March 06, 2009

In this paper, we present our findings on the development of a taxonomy for electromechanical components. In building this taxonomy, we have two main objectives: First, we strive to establish a framework for future computational tools that archive, search, or reuse component knowledge during the conceptual phase of design. Second, we aim to define a standard vocabulary that derives uniformity and consistency in the representation of electromechanical component space. Through both empirically dissecting existing products and defining categories based on functional analysis, we defined 135 generic component types. The use and necessity of the resulting taxonomy by a suite of computational design tools are illustrated in two applications of conceptual design.

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Copyright © 2009 by American Society of Mechanical Engineers
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Figures

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Figure 1

Port analysis for an electric motor

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Figure 2

An excerpt of component terms and definitions organized using the proposed hierarchical taxonomy

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Figure 3

The function structure, the exploded view, and the configuration flow graph of a camera

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Figure 4

Illustration of rule derivation from empirical analysis of consumer products

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Figure 5

Brief visual summary of the matrix-based concept generation approach

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