In the design and fabrication process of composites structures, several parameters affect the quality of a composites part, starting with the raw material up to the final inspection. Throughout the entire process, many data are collected and stored on various formats that depend on the type of equipment used, including material properties, inspection records, environmental data, and others. In the end, a significant amount of data is accumulated for each part produced. Since all the data are generated and stored in different formats, we cannot readily process or analyze these. Therefore, there is an acute need to define a strategy to integrate all data into a centralized database and to apply mining and visualization techniques aiming at identifying key process parameters affecting the quality and performance of the composite part. Such a tool would be tremendously useful in problem-solving, process optimization, and further down, in developing more robust processes.
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