Grants and Contributions:

Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019).

Stelia North America is a company specialized in the design and fabrication of composites structures for thex000D
aeronautic, defense and space market. In their manufacturing process, several parameters affect the quality of ax000D
final product, from the material properties to environmental factors (temperature, humidity, etc.). To controlx000D
the product quality and support inspections, throughout the production process different types of data arex000D
collected and stored. Stelia has identified that if they can develop more robust manufacturing processes, theyx000D
will reduce material losses and improve the quality of their products, helping them to pursue a leadershipx000D
position in the composite structures industry. Stelia is hindered in this goal by not being able to identify wherex000D
in their manufacturing process issues are injected. Stelia believes that it can acquire this knowledge throughx000D
detailed analysis of the various data streams they collect. However, the very heterogeneous nature of such datax000D
is a challenge, hampering them to take full advantage of all collected information for analytical purposes. Thex000D
proposed project will investigate the application of state-of-the-art data mining and visualization techniques onx000D
the analysis of the manufacturing parameters that affect the quality of a composites part. We will work onx000D
integrating different sources of data to allow the execution of analytical tasks. Our goal is to understand thex000D
influence of the manufacturing parameters on the quality of a composite material, ultimately helping onx000D
developing more robust processes.