Award Data

The Department of Defense (DoD) has a demand for out-of-production parts to maintain mission readiness of various weapons platforms. Additive manufacturing (AM) is an exciting and promising manufacturing technique that can make out-of-production parts and holds the potential to solve supply chain issues, such as high costs (i.e. for low-volume parts) and sole sourcing risks. The ability of AM to s ...

Universal Technology Corporation (UTC) has teamed with the University of Dayton Research Institute (UDRI), Stratonics, and Macy Consulting to demonstrate not only the transitionability into commercial systems, but also to develop the data analytics and monitoring and control requirements to extract the full value fromseveral sensors, including the Stratonics ThermaViz, acoustic and profilometry se ...

Additive manufacturing (AM) has rapidly evolved into a valuable technique for making parts which, at times, cannot be fabricated through conventional machining methods.One challenge in the area of AM is the lack of real-time feedback on the fabrication process and the quality of the part being made.This is especially critical given the relatively long periods of time that complex parts can require ...

Additive Manufacturing (AM) is a modern and increasingly popular manufacturing process for metallic components, but suffers from well known problems of inconsistent quality of the finished product. Process monitoring and feedback control are therefore crucial research areas with a goal of solving this problem. To address this concern, X-wave Innovations, Inc. (XII) and the University of Dayton Res ...

On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

This Phase II project aims to assemble the key set of sensor modalities that are needed to reliably view the key process anomalies and properties of laser powder bed fusion. The research team will down-select from the Phase I sensors investigated and integrate the sensors into a sensor fusion software package that facilitates data collection and synchronization, and eventually feedback control of ...

Additive manufacturing (AM) has rapidly evolved into a valuable technique for making parts which, at times, cannot be fabricated through conventional machining methods, or for fabrication of small quantities of complex parts. One challenge in the area of AM is the lack of real-time feedback on the fabrication process and the quality of the part being made. This is especially critical given the rel ...