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A methodology for creating a statistically derived shape grammar composed of non-obvious shape chunks

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Abstract

A shape grammar is a production system that can be used to create new product designs. Traditionally, a product shape grammar’s rules are created by a skilled person that understands the language of the design. In this paper the results of a principal component analysis of vehicles are used to create a vehicle shape grammar by basing the rules upon the determined shape relationships. The advantages are that: rules can be created according the results of a statistical analysis, and not according to a designer’s subjective observations; class specific vehicles can be created with fewer rule applications; and those rule applications encourage divergent designs. Using the principal component analysis based shape grammar, unique vehicles are created to demonstrate the potential of statistically based concept creation for the generation of product forms.

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Acknowledgments

Funding for this research was partially provided by the National Science Foundation under grant DMI-0245218 and by General Motors.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Carnegie Mellon University, Scaife Hall, 5000 Forbes Avenue, Pittsburgh, PA, 15213, USA

    Seth Orsborn & Jonathan Cagan

  2. Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA, USA

    Peter Boatwright

Authors
  1. Seth Orsborn
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  2. Jonathan Cagan
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  3. Peter Boatwright
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Corresponding author

Correspondence to Jonathan Cagan.

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Orsborn, S., Cagan, J. & Boatwright, P. A methodology for creating a statistically derived shape grammar composed of non-obvious shape chunks. Res Eng Design 18, 181–196 (2008). https://doi.org/10.1007/s00163-007-0035-9

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  • DOI: https://doi.org/10.1007/s00163-007-0035-9

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