Visual Data Analysis for Advanced Composite Materials Quality Control

Stelia North America is a company specialized in the design and fabrication of composites structures for theaeronautic, defense and space market. In their manufacturing process, several parameters affect the quality of afinal product, from the material properties to environmental factors (temperature, humidity, etc.). To controlthe product quality and support inspections, throughout the production process different types of data arecollected and stored. Stelia has identified that if they can develop more robust manufacturing processes, theywill reduce material losses and improve the quality of their products, helping them to pursue a leadershipposition in the composite structures industry. Stelia is hindered in this goal by not being able to identify wherein their manufacturing process issues are injected. Stelia believes that it can acquire this knowledge throughdetailed analysis of the various data streams they collect. However, the very heterogeneous nature of such datais a challenge, hampering them to take full advantage of all collected information for analytical purposes. Theproposed project will investigate the application of state-of-the-art data mining and visualization techniques onthe analysis of the manufacturing parameters that affect the quality of a composites part. We will work onintegrating different sources of data to allow the execution of analytical tasks. Our goal is to understand theinfluence of the manufacturing parameters on the quality of a composite material, ultimately helping ondeveloping more robust processes.