Engineers aim to create digital twins of LPBF parts to predict defects.
Metal 3D printing has been gaining ground as a production technology, but one of the issues holding it back is uncertainty about the durability of metal parts made via additive manufacturing (AM).
In order to understand how long 3D printed metal parts are likely to last in the field, the Defense Advanced Research Projects Agency (DARPA) is providing up to $10.3M to a team of engineers from the University Michigan, Texas A&M, the ASTM Additive Manufacturing Center of Excellence and in-situ AM process monitoring start-up, Addiguru.
More specifically, the team is examining the extent to which variations in the laser powder bed fusion (LPBF) process affect part durability.
“Depending on which model of LPBF printer you use, you might get different microstructures and different properties. The laser spot size and laser power levels might be different. The scanning strategies might be different. These things change the quality of the part,” said Veera Sundararaghavan in a press release. Sundararaghavan is a professor of aerospace engineering at the University of Michigan and principal investigator of the project.
The idea is to record the LPBF process for a variety of parts with optical and infrared cameras and use this information to create a digital twin of each one. By computationally modelling repeated stresses on the part, they hope to identify where and how quickly cracks will form. These fatigue models will also incorporate actual service data to enhance the accuracy of their predictions.
“To understand the lifespan of LPBF parts, we must push the current boundaries of the field and detect even the most critical defects that impact component performance,” said Mohsen Taheri Andani, assistant professor of mechanical engineering at Texas A&M University in the same release. “Through the PRIME [Predictive Real-Time Intelligence for Metal Endurance] project, we are doing exactly that—leveraging state-of-the-art monitoring and AI techniques to redefine what’s possible.”
Addiguru’s contribution to the project is a method for multisensory integration that includes acoustic monitoring to detect signs of porosity. According to the researchers, this combination of sensors will enable them to identify defects as small as 0.025mm.
“Multisensor data, combined with advanced analytics, will provide critical insights to part manufacturers,” said Shuchi “SK” Khurana, founder and CEO of Addiguru, also co-leading the print monitoring effort. “This project will enable a comprehensive, real-time assessment of part quality, helping manufacturers make informed go/no-go decisions with confidence.”
If successful, this project could provide vital information for manufacturers working with metal LPBF across a host of industries, from aerospace, to automotive, to medical devices.
