UCF Associate Professor Dazhong Wu Receives DARPA Young Faculty Award

An associate professor at the University of Central Florida has been awarded a Young Faculty Award from the Defense Advanced Research Projects Agency (DARPA) to develop a machine learning model capable of predicting the performance and defects of 3D printed parts.

This approach aims to reduce costs and delays associated with testing, which have so far hindered the adoption of additive manufacturing (AM) in many industrial sectors.

Dazhong Wu, associate professor in mechanical and aerospace engineering at the University of Central Florida, has received over $500,000 to fund this two-year project titled “Affordable and Scalable Additive Manufacturing Part Qualification through Artificial Intelligence.” Additional funding of $500,000 for a third year may be granted by DARPA, pending research advancements.

Currently, metallic AM processes rely on expensive materials, including titanium alloys, to manufacture complex and high-performance parts layer by layer from digital models. The following trial and error testing cycles are often lengthy, lead to partial destruction of parts, and incur high costs. Wu’s project aims to address this by developing a model to reduce dependence on these destructive tests.

“Through AI, we can predict the mechanical performance of 3D printed parts from small amounts of data from destructive and non-destructive tests,” Wu stated. “This will ensure that each part is consistent, reliable, and less costly.”

“I hope that this AI-based AM qualification framework will be used across many industries, including aerospace and many others. Reducing costs is crucial for the AM industry. To achieve this, we must ensure that each part consistently meets performance requirements,” Wu added.