Reference number : GC-2017-Q4-01424, amendment number : , agreement type : G, recipient legal name : Paulovich, Fernando (Dalhousie University), recipient country : CA, recipient province : nan, recipient city : Nova Scotia|Nouvelle-Écosse, recipient postal code : nan, program name english : Engage Grants for universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : Stelia North America is a company specialized in the design and fabrication of composites structures for the_x000D_
aeronautic, defense and space market. In their manufacturing process, several parameters affect the quality of a_x000D_
final product, from the material properties to environmental factors (temperature, humidity, etc.). To control_x000D_
the product quality and support inspections, throughout the production process different types of data are_x000D_
collected and stored. Stelia has identified that if they can develop more robust manufacturing processes, they_x000D_
will reduce material losses and improve the quality of their products, helping them to pursue a leadership_x000D_
position in the composite structures industry. Stelia is hindered in this goal by not being able to identify where_x000D_
in their manufacturing process issues are injected. Stelia believes that it can acquire this knowledge through_x000D_
detailed analysis of the various data streams they collect. However, the very heterogeneous nature of such data_x000D_
is a challenge, hampering them to take full advantage of all collected information for analytical purposes. The_x000D_
proposed project will investigate the application of state-of-the-art data mining and visualization techniques on_x000D_
the analysis of the manufacturing parameters that affect the quality of a composites part. We will work on_x000D_
integrating different sources of data to allow the execution of analytical tasks. Our goal is to understand the_x000D_
influence of the manufacturing parameters on the quality of a composite material, ultimately helping on_x000D_
developing more robust processes., program purpose french : Stelia North America is a company specialized in the design and fabrication of composites structures for the_x000D_
aeronautic, defense and space market. In their manufacturing process, several parameters affect the quality of a_x000D_
final product, from the material properties to environmental factors (temperature, humidity, etc.). To control_x000D_
the product quality and support inspections, throughout the production process different types of data are_x000D_
collected and stored. Stelia has identified that if they can develop more robust manufacturing processes, they_x000D_
will reduce material losses and improve the quality of their products, helping them to pursue a leadership_x000D_
position in the composite structures industry. Stelia is hindered in this goal by not being able to identify where_x000D_
in their manufacturing process issues are injected. Stelia believes that it can acquire this knowledge through_x000D_
detailed analysis of the various data streams they collect. However, the very heterogeneous nature of such data_x000D_
is a challenge, hampering them to take full advantage of all collected information for analytical purposes. The_x000D_
proposed project will investigate the application of state-of-the-art data mining and visualization techniques on_x000D_
the analysis of the manufacturing parameters that affect the quality of a composites part. We will work on_x000D_
integrating different sources of data to allow the execution of analytical tasks. Our goal is to understand the_x000D_
influence of the manufacturing parameters on the quality of a composite material, ultimately helping on_x000D_
developing more robust processes., agreement title english : Visual Data Analysis for Advanced Composite Materials Quality Control, agreement title french : Visual Data Analysis for Advanced Composite Materials Quality Control, agreement number : EGP, agreement value : 25000.0, agreement start date : 2018-03-07, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada