Researchers from Johns Hopkins Applied Physics Laboratory (APL) and the Whiting School of Engineering are taking titanium manufacturing to the next level with artificial intelligence. Their novel approach enhances both speed and strength, paving the way for advancements in aerospace, defense, and medical applications.
“The nation faces an urgent need to accelerate manufacturing to meet the demands of current and future conflicts,” said Morgan Trexler, APL’s program manager. “At APL, we are advancing research in laser-based additive manufacturing to rapidly develop mission-ready materials.”
The research, published in Additive Manufacturing, focuses on Ti-6Al-4V, a widely used titanium alloy. By using AI-driven models, the team mapped processing conditions in laser powder bed fusion – a key 3D printing method for metals – unexplored before. The findings challenge long-help assumptions, showing that titanium can be printed faster, more robust, and with customizable properties.
“For years, we assumed certain parameters were ‘off-limits’ because they led to poor-quality parts,” said Brendan Croom, senior materials scientist at APL. “AI helped us discover new processing regions that allow faster printing while improving material strength and ductility.”
This discovery builds on years of APL research in additive manufacturing. Steve Storck, lead scientist at APL, stated that previous limitations stemmed from slow trial-and-error testing. Now, with the help of Bayesian optimization, AI predicts the optimal processing conditions, reducing years of experiments to just weeks.
“This isn’t just about speed,” confirmed Croom. “It’s about striking the right balance between strength, flexibility, and efficiency.”
The researchers’ approach is currently explored for more metals and advanced alloys. In the future, real-time AI monitoring will hopefully ensure next-gen manufacturing, as on-demand, high-performance metal printing gets closer to reality.
