Additive Manufacturing Data Analytics, Process to Performance Analysis
Additive manufacturing (AM) is a digital process that provides critical information across the entire process lifecycle from product definition, manufacturing, test/inspection and final acceptance. This information is comprised of large spatial and temporal data sets that provide insights to the quality of the final manufactured part. These data sets currently reside on disparate systems which can limit correlation and advancement of AM process understanding and insights. There is a desire to integrate these data sets into a "super set" of data that is registered and fused together using data consolidation and visualization techniques. With the data integrated, there is the opportunity to apply new data analysis techniques to infer relationships between in process, post process and performance data. The student team worked to enhance data analytics applied to existing UW data sets through the development of new software packages that enable large AM data sets to be integrated.
Luna Yue Huang,
Materials Science & Engineering
Developing a synthetic railbelt power system model
A team of electrical and chemical engineering graduate students on a capstone project focused on developing a synthetic power system model of Alaska’s Railbelt transmission system.
Third annual Boeing capstone
Students earned their wings during a spring quarter capstone project undertaken in partnership with Boeing. Fittingly, they worked on a novel design for a wingtip end cap that was produced using 3D printing.
Students design a rover to help fish
As part of an industry capstone project, engineering students created a rover to inspect sewer pipes and culverts for damage that may prevent fish migration.