RII Track-2 FEC: Rapid Qualification for Additively Manufactured Safety-Critical Components

Additive Manufacturing (AM) such as metal powder based 3D printing part qualification has been identified by the America Makes & American National Standard Institute (ANSI) Additive Manufacturing Standardization Collaborative (AMSC) as a standardization gap with high priority in our nation. To make 3D printed metal parts more commercially viable, a rapid parts qualification process is a must.

This Research Infrastructure Improvement Track-2 Focused EPSCoR Collaboration (RII Track-2 FEC) award will permit researchers from two EPSCoR jurisdictions (LA and AL) institutions, Southern University (SU), Louisiana State University (LSU), in Louisiana and the National Center for Additive Manufacturing Excellence (NCAME) at Auburn University (AU) in Alabama to establish a Consortium for Additive Manufacturing Qualification (CAM-Q). CAM-Q will exploit research opportunities at the intersection of materials science and data analytics, with a technological focus on Laser Beam Powder Bed Fusion (LB-PBF) additive manufacturing (AM), to radically transform the AM parts qualification process.

The major outcomes of this project will be an overall framework for AM process design and rapid fatigue performance qualification, together with significant contributions to the education, training, and development of a highly-skilled, multidisciplinary, and diverse workforce to support the industry in the United States. The planned research represents a significant change from the current AM qualification practices.

Successful execution of this project will enable the fabrication of metal/alloy parts with a significantly accelerated qualification cycle, make the AM process commercially viable, and propel the US industry to a global leadership position.

To make LB-PBF AM more commercially viable, a rapid parts qualification process is a must. By coupling multiscale simulations and characterization with data analytics and by structuring a meso-scale mechanical testing framework, CAM-Q will establish processing strategy-structure-performance (PSP) relationships for meso-scale building strategies and subsequently demonstrate a new qualification approach on the structural integrity for LB-PBF parts.

CAM-Q’s goal is to establish a science-driven, non-destructive evaluation (NDE) based framework for the rapid qualification of AM parts for safety-critical applications. A new PSP database for a crucial collection of Discrete Building Strategy Sets (DBSS) will be generated to support the qualification process by combining experimentation, data analysis, and physics-based modeling.

For each Discrete Building Strategy set, this database will include: 1) location-specific process control parameters; 2) detailed microstructure maps, including volumetric distributions of pores/cracks collected via X-ray computed tomography (XCT) scans, three-dimensional (3D) "slice and view" data cubes in combination with data analysis and reconstruction, and physics-based simulations linking defects to fatigue performance; and 3) micro-to-meso scale mechanical testing to pinpoint location-specific mechanical performance, with emphasis on fatigue performance. Data analytics will be utilized to evaluate the performance of components and provide guidance on processing strategies for making parts with improved performance, thus achieving rapid quantification.

The research outcomes will be incorporated in the education and workforce training program, consisting of year-long projects for undergraduates and dissertations for graduate students with direct industry participation. Tight integration and coordination between research, education, and workforce development and training programs will be supported by well-coordinated project management, evaluation, and assessment plans.

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.