Design Computing and Cognition ’10 2011
DOI: 10.1007/978-94-007-0510-4_25
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Organizing a Design Space of Disparate Component Topologies

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Cited by 3 publications
(4 citation statements)
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“…Dependencies are modeled by two linked approaches: matrix based or graph based. Matrix-based approaches, also known as design structured matrix (DSM), can be viewed as methods focusing on adjacency matrices of graphs (Browning, 2016; Kreimeyer and Lindemann, 2011; Kumar and Campbell, 2011; Sunnersjo, 2016). The choice of using one representation or the other depends on the computational practicability and the needs of representation (readability and compactness).…”
Section: Related Workmentioning
confidence: 99%
“…Dependencies are modeled by two linked approaches: matrix based or graph based. Matrix-based approaches, also known as design structured matrix (DSM), can be viewed as methods focusing on adjacency matrices of graphs (Browning, 2016; Kreimeyer and Lindemann, 2011; Kumar and Campbell, 2011; Sunnersjo, 2016). The choice of using one representation or the other depends on the computational practicability and the needs of representation (readability and compactness).…”
Section: Related Workmentioning
confidence: 99%
“…A graph grammar representation however encodes much more complex forms of functioncomponent mapping by using grammar rules. Previous work on computational design synthesis for product assemblies using graph grammar representation [15] describes a two layer approach as a simplification of the Function Behavior Structure approach [16]. This uses function structure and a Component Flow Graph to represent electromechanical products such as compressors, blowers, hair dryer etc.…”
Section: Related Workmentioning
confidence: 99%
“…Rather than present a long list of alternatives, the set of concepts are also passed to a clustering routine in the interest of identifying similarities amongst the generated alternatives. [38,39]. These activities result in a wealth of data that may be useful to a designer, without an intuitive means of exploring the space of design alternatives.…”
Section: Underlying Architecturementioning
confidence: 99%
“…In the second, the number of dimensions used to describe the concepts is reduced by identifying the principal components before clustering. The first option, discussed in detail in [38] uses a variant K-means clustering or Lloyd's algorithm as an iterative clustering algorithm. [21,48] A second clustering option, discussed in detail in [39] uses Principal Component Analysis (PCA) to reduce the dimensionality of the problem prior to applying the clustering algorithm [49] .…”
Section: Goalsmentioning
confidence: 99%