Analogies play a well-noted role in innovative design. Analogical reasoning is central to the practices of design-by-analogy and bio-inspired design. In both, analogies are used to derive abstracted principles from prior examples to generate new design solutions. While numerous laboratory and classroom studies of analogy usage have been published, relatively few studies have systematically examined real-world design-by-analogy to describe its characteristics and impacts. To better teach design-by-analogy and develop support tools for engineers, specific insights are needed regarding, for example, what types of product advantages are gained through design-by-analogy and how different design process characteristics influence its outcomes. This research comprises two empirical product studies which investigate analogical inspiration in real-world design to inform the development of new analogy methods and tools. The first, an exploratory pilot study of 57 analogy-inspired products, introduces the product study method and applies several categorical variables to classify product examples. These variables measure aspects such as the composition of the design team, the driving approach to analogical reasoning, and the achieved benefits of using the analogy-inspired concept. The full scale study of 70 analogy-inspired products uses formal collection and screening methods and a refined set of classification variables to analyze examples. It adopts a cross-sectional approach, using statistical tests of association to detect relationships among variables. Combined, these surveys of real-world analogy-inspired innovation inform the development of analogy tools and provide a general account of distant analogy usage across engineering disciplines. The cross-sectional product study method demonstrated in this work introduces a valuable tool for investigating factors and impacts of real-world analogy usage in design.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/51891 |
| Date | 22 May 2014 |
| Creators | Ngo, Peter |
| Contributors | Linsey, Julie |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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