Manufacturing Process Informatics for Composite Curing Analysis Toolkit (M-PICC-AT)

In nearly all composite manufacturing processes, composite cure data output from autoclaves and ovens is used as the primary source of composite quality data. Following a cure cycle, data is manually analyzed to ensure process specification conformance, parts are sent on for non-destructive inspection, and the data is stored for trace-ability sake. Following storage, this data is rarely looked back upon for process improvement or quality identifiers. Ultimately, this leaves all of the major aerospace composites manufacturers with a mountain of sensor data ready for exploitation to drastically improve process time and quality. In industry, there are a few critical methods in which this data can be leveraged through advanced data analytic methods. The M-PICC Analysis Toolkit (M-PICC-AT) is a complete framework for allowing data scientists, analysts, and machine learning engineers streamline their algorithms.  With this Direct to Phase 2 SBIR award, New Dawn Labs will focus defining the algorithms that identify non-conformance across and within cure cycles, and building an informatics platform that allows materials experts easily store their datasets for historical analysis, visualize the output of those algorithms, and integrate with other vendor systems.