IDETC2005 -85431 RECOGNITION OF INTERACTING TURNING FEATURES FOR MILL/TURN PARTS

ABSTRACT This paper focuses on efficient automatic recognition algorithms for turning features. As with other domains, recognition of interacting features is a difficult issue, because feature interaction removes faces and alters the topology of the existing turned features. This paper presents a method for efficiently recognizing both isolated (without interaction with other features) and interacting rotational features from geometrical CAD model of mill/turn parts. Additionally, the method recognizes Transient Turned Features (TTFs) that are defined as maximal axisymmetric material volumes from a nonturning feature that can be removed by turning. A TTS may not share any faces with the finished part. First, the rotational faces on a solid model are explored to extract isolated rotational features and some of the interacting ones. Then portions of the 3D model where no rotational faces can be used to recognize turning features are cut out and processed by a novel algorithm for finding their transient turning features

Applied Tests of Design Skills — Part 1: Divergent Thinking

A number of cognitive skills relevant to conceptual design were identified previously. They include divergent thinking (DT), visual thinking (VT), spatial reasoning (SR), qualitative reasoning (QR), and problem formulation (PF). A battery of standardized tests is being developed for these design skills. This paper focuses only on the divergent thinking test. This particular test has been given to over 500 engineering students and a smaller number of practicing engineers. It is designed to evaluate four direct measures (fluency, flexibility, originality, and quality) and four indirect measures (abstractability, afixability, detailability, and decomplexability). The eight questions on the test overlap in some measures and the responses can be used to evaluate several measures independently (e.g., fluency and originality can be evaluated separately from the same idea set). The data on the twenty-three measured variables were factor analyzed using both exploratory and confirmatory procedures. A four-factor solution with correlated (oblique) factors was deemed the best available solution after examining solutions with more factors. The indirect measures did not appear to correlate strongly either among themselves or with the other direct measures. The four-factor structure was then taken into a confirmatory factor analytic procedure that adjusted for the missing data. It was found to provide a reasonable fit. Estimated correlations among the four factors (F) ranged from a high of 0.32 for F1 and F2 to a low of 0.06 for F3 and F4. All factor loadings were statistically significant

Spinneret: Aiding Creative Ideation through Non-Obvious Concept Associations

Mind mapping is a popular way to explore a design space in creative thinking exercises, allowing users to form associations between concepts. Yet, most existing digital tools for mind mapping focus on authoring and organization, with little support for addressing the challenges of mind mapping such as stagnation and design fixation. We present Spinneret, a functional approach to aid mind mapping by providing suggestions based on a knowledge graph. Spinneret uses biased random walks to explore the knowledge graph in the neighborhood of an existing concept node in the mind map, and provides "suggestions" for the user to add to the mind map. A comparative study with a baseline mind-mapping tool reveals that participants created more diverse and distinct concepts with Spinneret, and reported that the suggestions inspired them to think of ideas they would otherwise not have explored.Comment: ACM CHI 202