Ann Arbor Times

The Defense Advanced Research Projects Agency (DARPA) is set to fund a University of Michigan-led research team with up to $10.3 million. The objective is to investigate the durability of 3D-printed metal parts made through a process known as laser powder bed fusion (LPBF). This method, while costly, offers a solution to the lengthy delays encountered when military equipment parts are ordered and shipped to remote areas.

The need for reliable and robust 3D-printed parts has prompted this study due to the variability inherent in LPBF manufacturing. Unlike traditional cold-forged parts, LPBF components exhibit more frequent and random material defects, posing challenges for ensuring consistent longevity.

"Depending on which model of LPBF printer you use, you might get different microstructures and different properties," stated Veera Sundararaghavan, a professor of aerospace engineering at the University of Michigan and principal investigator of the project. "Our aim is to guarantee the quality of the part as you print."

Sundararaghavan and his team aim to address this by tracking the printing process meticulously and crafting a "digital twin" of each part. This digital model will help in predicting fatigue life by identifying where and when cracks might occur due to repeated stress. The project is named Predictive Real Time Intelligence for Metal Endurance, or PRIME.

“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,” explained Mohsen Taheri Andani, assistant professor of mechanical engineering at Texas A&M University, who is co-leading the monitoring efforts of LPBF printing.

In partnership with Addiguru, Texas A&M University, and the ASTM Additive Manufacturing Center of Excellence, the research will focus on developing data collection standards during LPBF manufacturing. The team will integrate multiple sensors, including an optical camera and two infrared cameras, as well as a multisensor acoustic device. This setup will help detect defects as minute as 0.025 millimeters.

"Multisensor data, combined with advanced analytics, will provide critical insights to part manufacturers," expressed Shuchi “SK” Khurana, founder and CEO of Addiguru.

Moreover, the University of Michigan team will collaborate with AlphaSTAR to combine physics-based modeling with simulations of the part’s microstructure. This approach will assist in identifying residual stresses and predict fatigue life. The involvement also extends to researchers at the University of California, San Diego, who will run uncertainty quantification models, while Auburn University will conduct fatigue tests.

“If PRIME takes off, it’s like giving 3D printing a crystal ball—predicting the lifetime of LPBF parts across platforms and turning critical part production into a low-cost, distributed dream,” Sundararaghavan added.

This initiative is supported under DARPA's Structures Uniquely Resolved to Guarantee Endurance program.