This project is to enable groups of people to better brainstorm decisions in which people can have divergent opinions. Building on ValueCharts that lets people input their utility, we will build a tool that lets decision makers explore the space of the expressed opinion to see where there are differences and whether they matter to the decision being made.
This project involves the development and implementation of a visualization, analysis and exploration prototype for a parametric CAD tool. The prototype focuses on the design process; that is, the collection of actions taken by designers as they develop solutions. The visualization will allow designers to analyze, understand and make better decisions based on single actions and/or patterns across time. Designers using the prototype will be able to explore new design solutions derived from this knowledge using the visualization itself.
During assembly of an aircraft, technicians working in the interior need to be able to quickly identify parts and access part numbers. Part numbers can be retrieved through 3D geometric models of the aircraft. Navigating large 3D models is challenging and time consuming, and it is nearly impossible on small mobile devices with limited processing power and screen sizes. We will explore the use of techniques from computer vision and heuristic search with the goal of eliminating the need to manually traverse large 3D geometric models or search long parts catalogues.
The Centre for Operations Excellence (COE) at the Sauder School of Business at UBC will collaborate with Boeing Commercial Airplanes through its BC based subsidiary AeroInfo Systems to assess methodologies to allow for analysis of plausible scenarios of the future global business environment. The methodologies would provide a means for what‐if testing to describe the effects of scenarios on the demand for commercial aircraft, and Boeings order book in particular.
The average person manages uncertainty on a daily basis, from determining whether to invest in a particular stock to predicting the outcome of a baseball game. However, in some cases, such as that of Boeing safety analysis, the consequences can be much larger. When people’s lives are at stake, effective tools to manage and communicate uncertainty to decision makers are essential. Before being able to visually represent uncertainty effectively, there is a need for understanding where it fits in the analytic process and current methods of visualization.
The goal of this research is to define an information acquisition strategy for use in the definition and development of visual analytics (VA) tools relevant to the domain of interest. The strategy will account for task and job requirements gathering and incorporate a wealth of human factors issues known to be important in critical system design, e.g., workload, situation awareness, automation, etc. Another goal is to provide valid information for the design of laboratory and field studies using existing or new VA tools or components as the study apparatus.
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