MRI: Track 1 Development of Metal 3D Printing Research Instrument with In-situ Characterization and Closed-loop Control Capability

About This Grant

This Major Research Instrumentation (MRI) award will support development of an advanced in-situ laser powder bed fusion additive manufacturing (AM, or 3D printing) platform at the University of Louisiana at Lafayette. While metal AM has transformative potential for the aerospace, energy, healthcare, and defense industries, current systems lack the ability to deliberately control in-situ alloying physics, defect presence, and material property formation in real time. The developed platform seeks to address these limitations by enabling in-situ control of melt pool dynamics, thermal behavior, and layer quality through sensor-driven feedback control loops and automated data analysis. Moreover, the system looks to support fundamental research into how materials solidify and form complex structures and properties under laser manufacturing conditions. The machine intends to monitor and regulate the printing process in real time and enable the fabrication of complex, high-performance components with improved reliability and precision. This platform will be a shared-use resource and support multidisciplinary research and hands-on training for students through the Institute for Materials Research and Innovation (IMRI). This award will also support student training at the graduate level. Overall, the activities supported by this project seek to promote innovation and workforce development to advance national efforts in science, innovation, and economic competitiveness. The development of an in-situ open-source metal 3D printing platform looks to support research and education in emerging technologies of advanced manufacturing, in-situ monitoring, intelligent systems, and advanced materials printing. When completed, the project intends to create new research and education avenues to: 1) resolve and closed-loop control of AM alloying melt pool physics and defects formation (e.g., pores, cracks, and delamination); 2) identify and mitigate adaptive physical adversarial control loops on AM system; 3) enable real-time detection of multilayer build defect and geometry distortion using in-situ sensors; 4) control in-situ AM alloying chemistry to design new materials with precise morphologies, microstructures and enhanced properties; and 5) arrange multilayer build’s interface and heterostructure precisely for fabrication of customized energy materials, such as battery electrodes, and lightweight structures. The system’s flexible architecture looks to support software and hardware customization, making it a valuable resource for industry and academic institutions. This project intends to strengthen scientific understanding, increase participation in engineering, and build a broad, skilled national workforce for the future of intelligent manufacturing. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.