Exploring the Application of Network Analytics in Characterizing a Conceptual Design Space
| Autor: | Kosa Goucher-Lambert, Jonathan Cagan, Joshua T. Gyory, Kenneth Kotovsky |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Engineering support Computer science 0211 other engineering and technologies 02 engineering and technology General Medicine Network theory Space (commercial competition) Data science Variety (cybernetics) 020901 industrial engineering & automation Conceptual design Semantic similarity Design methods Representation (mathematics) 021106 design practice & management |
| Zdroj: | Proceedings of the Design Society: International Conference on Engineering Design. 1:1953-1962 |
| ISSN: | 2220-4342 |
| DOI: | 10.1017/dsi.2019.201 |
| Popis: | The ability to effectively analyse design concepts is essential for making early stage design decisions. Human evaluations, the most common assessment method, describe individual design concepts on a variety of ideation metrics. However, this approach falls short in creating a holistic representation of the design space as a whole that informs the underlying relations between concepts. Motivated by this shortcoming, this work leverages network theory to visualize and characterize features of a conceptual design space. To illustrate the utility of network theory for these purposes, a network composed of a corpus of solutions to a design problem and their semantic similarity is derived, and its design properties (e.g., uniqueness and innovation potential) are studied. This network-based approach not only characterizes features of individual designs themselves, but also uncovers more nuanced properties of the design space through studying emerging clusters of concepts. Overall, this work expands on developing research in design, demonstrating the value in applying network analytics to a conceptual design space as an engineering support tool to aid design decision-making. |
| Databáze: | OpenAIRE |
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