Knowledge collection, extraction, and organization are critical activities in all aspects of the engineering design process. However, it remains challenging to surface and organize design knowledge, which often contains implicit or tacit dimensions that are difficult to capture in a scalable and accessible manner. Knowledge graphs have been explored to address this issue, but have been primarily semantic in nature in engineering design contexts, typically focusing on sharing explicit knowledge. Our work seeks to understand knowledge organization during an experiential activity and how it can be transformed into a scalable representation. To explore this, we examine 23 professional designers' knowledge organization practices as they virtually engage with data collected during a teardown of a consumer product. Using this data, we develop a searchable knowledge graph as a mechanism for representing the experiential knowledge and afford its use in complex queries. We demonstrate the knowledge graph with two extended examples to reveal insights and patterns from design knowledge. These findings provide insight into professional designers' knowledge organization practices, and represent a preliminary step toward design knowledge bases that more accurately reflect designer behavior, ultimately enabling more effective data-driven support tools for design.
Knowledge collection, extraction, and organization are critical activities in all aspects of the engineering design process. However, it remains challenging to surface and organize design knowledge in a scalable and accessible manner given it often contains implicit or tacit dimensions that are difficult to capture. Knowledge graphs have been explored to address this issue but have been primarily semantic in nature in engineering design contexts, typically focusing on sharing explicit knowledge. In this work, we explore how knowledge graphs could offer a mechanism to organize experiential design knowledge and afford its use in complex queries. We develop a searchable knowledge graph based on data from a previous virtual product teardown activity with 23 professional designers. Examples of the underlying data within this corpus include descriptions of product components and their purpose as well as participant-determined relationships between these components. To structure the knowledge graph, we develop a schema that uses its constituent nodes and edges to represent design knowledge, relational information, and properties such as the node author’s discipline and the node’s function-behavior-structure classification. We propose and demonstrate two user-driven graph search types — intentional and exploratory — and four data-driven graph search methods, and illustrate through two extended examples their potential to reveal insights and patterns from teardown knowledge. These findings suggest that knowledge graphs can be a valuable approach to organizing and availing experiential design knowledge emerging from complex design activities.
Life cycle assessment (LCA) has been established as a benchmark for design for sustainability practices. LCA provides detailed technical documents regarding a product's environmental impact, but its use is often limited to trained experts who share the knowledge with designers. Life cycle experts are highly specialized, and the typical designer faces technical barriers and time constraints in extracting information from LCA documents. This work uses knowledge transfer principles to replicate expert practices in LCA information retrieval to support designers. Life-cycle experts (n = 4) were interviewed to understand practices and challenges in information retrieval for LCA documents. Interview findings were used to create a set of guidelines for effectively navigating LCA documents and then tested in a follow-up task where designers (n = 16) annotated an electric toothbrush LCA using the identified guidelines. Results find designers can effectively extract information from LCA documents given provided guidelines, but need detailed support interpreting complex visual entities like charts and figures. This work is the first step toward enabling knowledge transfer from LCA documents and building a structured sustainability knowledge base.
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