Sentient Corporation proposes to integrate its DigitalClone Component (DCC) physics-based modeling technology and Johns Hopkins University Applied Physics Laboratorys in-situ thermal sensors to develop a comprehensive sensor-based tool to monitor, identify and locate defects in metallic additive manufacturing, and create a DCC model-enabled feedback loop to correct the process-induced defects to improve part quality. In Phase I, Sentient will demonstrate that an in-process sensor measured thermograph can be successfully linked to different types of defects on the build surface, and Sentients DCC model can be used to optimize the process parameters and correct known defects. The corrected part will be experimentally tested to show improved material properties and reduced residual stress in Phase I option. In Phase II, Sentient will partner with Sikorsky to further develop this flaw detection-correction technology into a closed-loop application in an AM process, and select suitable components in Army helicopter gearbox to demonstrate the developed application. It is expected that at the end of Phase II, the developed technique will meet the goal of this solicitation with an in-process method that can improve the repeatability of the material properties, geometry and quality of AM manufactured aluminum parts.
