Backed by a newly awarded National Science Foundation grant, researchers at the University of North Florida are developing an automated monitoring system that detects and corrects defects in metal 3D printing layer by layer, in real time.
Dr. Longfei Zhou, assistant professor of advanced manufacturing engineering, is leading the project alongside a team of undergraduate researchers, including advanced manufacturing engineering seniors Maria Fernanda Ocrospoma Figueroa, Tessa Baur, and Taylor Uhren.
Both Ocrospoma and Baur hold leadership roles in UNF’s SAMPE chapter and recently brought home top honours at the global Additive Manufacturing Competition at SAMPE 2026 Seattle, with Baur finishing first and Ocrospoma second.
A Layer-by-Layer Quality Control System
The core of the project is an automated monitoring system designed to observe each layer of a print in real time, identify irregularities as they emerge, and apply targeted corrections on the spot, rather than waiting until a build is complete to discover problems. By intervening early and precisely, the system aims to reduce failed parts without disrupting the broader printing workflow.
The team explained that catching problems before they compound translates directly into savings, fewer scrapped parts, lower operational costs, and a lighter environmental footprint. Beyond the lab, the team sees the work as a contribution to the long-term resilience of domestic manufacturing, where higher yields and greener production methods go hand in hand.
Beyond the technical outcomes, the project carries an educational and open-access mission. New course modules and lab activities will introduce students to the role of data and automation in modern manufacturing. The team also intends to release datasets, trained models, digital-twin software, and baseline decision policies publicly, so the benefits extend well beyond UNF.
An Industry-Wide Push to Close the Quality Gap
Laser powder bed fusion has become a cornerstone of advanced manufacturing, enabling the production of highly complex components for aerospace, healthcare, and energy sectors. Yet despite its capabilities, the process remains vulnerable to a subtle but costly flaw: streaking caused when the machine’s powder-spreading mechanism disturbs the metal bed mid-print. Left unaddressed, these streaks compromise structural integrity, forcing manufacturers to discard parts or restart entire builds, a drain on both materials and energy.
The challenge UNF is addressing sits at the centre of a growing industry effort. Past initiatives have focused on in-situ monitoring systems that track thermal behaviour and melt pool dynamics during printing, such as Sigma Labs’ PrintRite3D platform, deployed on DMG MORI LASERTEC metal 3D printers to analyse process data and flag defects in real time.
On the academic side, researchers at Aalen University’s LaserApplicationCentre have been refining process monitoring for powder bed-based laser melting using high-speed and high-resolution cameras, studying spatter, smoke, and solidification through global observation, while also conducting static analysis of powder bed layers to support defect detection, with plans to integrate AI for automated analysis of laser-material interactions.
The ambition is clear: quality control in metal AM should not end at detection, it should act.
3D Printing Industry is inviting speakers for its 2026 Additive Manufacturing Applications (AMA) series, covering Energy, Healthcare, Automotive and Mobility, Aerospace, Space and Defense, and Software. Each online event focuses on real production deployments, qualification, and supply chain integration. Practitioners interested in contributing can complete the call for speakers form here.
To stay up to date with the latest 3D printing news, don’t forget to subscribe to the 3D Printing Industry newsletter or follow us on LinkedIn.
Explore the full Future of 3D Printing and Executive Survey series from 3D Printing Industry, featuring perspectives from CEOs, engineers, and industry leaders on the industrialization of additive manufacturing, 3D printing industry trends 2026, qualification, supply chains, and additive manufacturing industry analysis.
Featured image shows Student researchers involved in the project. Photo via UNF.
