The US National Institute of Standards and Technology (NIST) has awarded US$3.7 million in grants to help develop standards for metal additive manufacturing (AM).

This could help facilitate wider adoption of the technology, according to the institute.

“The US can take a leading role in developing the measurements and international standards that will help accelerate adoption of these important 3D printing technologies,” said Laurie E Locascio, NIST director. “Additive manufacturing offers advantages such as reduced material waste, lower energy intensity, reduced time-to-market, and just-in-time production that could bolster supply chains in the US. Accelerating the adoption of new measurement methods and standards will help to advance US competitiveness in this important industry.”

NIST is currently developing ways to support equivalence-based qualification and model-based qualification, the characterization of AM materials, and standards to support consistent data exchange/characterizing new advances in AM production systems, it said.

As well as this, the Research Foundation for the State University of New York has received US$957,706 to demonstrate an improved nondestructive evaluation (NDE) technique that can determine key material properties such as oxide thicknesses, splatter particle percentage, grain size and defect detection, while the Colorado School of Mines has been funded US$956,888 for a project aimed at examining optical metrologies to enable real-time process feedback and control. This could help achieve process-based qualification and certification of metallic parts made by AM.

The two other grant recipients are Auburn University, which has US$949,075 over two years to establish a “data-driven framework” for the nondestructive qualification of AM materials and parts for applications that cannot afford failures due to fatigue, and GE Additive and the University of Texas at El Paso which plans with the remainder to establish an Intelligent Stitch Integration for Testing and Evaluation (I-SITE) program to extend existing standardized methods and build correlations between sensor response, material behavior and mechanical properties.