Assessing the Variety of a Concept Space Using an Unbiased Estimate of Rao's Quadratic Index

TL;DR

This paper introduces a new unbiased metric for assessing the variety of a concept space in design, utilizing a distance-based approach and a knowledge representation framework to improve evaluation accuracy.

Contribution

It proposes a novel distance-based variety metric and a prescriptive framework using SAPPhIRE, implemented in the VariAnT software tool, addressing limitations of existing metrics.

Findings

The new metric provides a more accurate assessment of concept variety.

The framework effectively measures distances between design concepts.

The VariAnT tool demonstrates practical application in design evaluation.

Abstract

Past research relates design creativity to 'divergent thinking,' i.e., how well the concept space is explored during the early phase of design. Researchers have argued that generating several concepts would increase the chances of producing better design solutions. 'Variety' is one of the parameters by which one can quantify the breadth of a concept space explored by the designers. It is useful to assess variety at the conceptual design stage because, at this stage, designers have the freedom to explore different solution principles so as to satisfy a design problem with substantially novel concepts. This article elaborates on and critically examines the existing variety metrics from the engineering design literature, discussing their limitations. A new distance-based variety metric is proposed, along with a prescriptive framework to support the assessment process. This framework uses the SAPPhIRE model of causality as a knowledge representation scheme to measure the real-valued distance between two design concepts. The proposed framework is implemented in a software tool called 'VariAnT.' Furthermore, the tool's application is demonstrated through an illustrative example.