Page 10 - 3D Metal Printing Magazine Winter 2022

3D TECH UPDATE Fundamental Research
into the Microstructure of AM Components Using X-ray CT
In October 2020, the University
of Nebraska-Lincoln (UNL) invested
in a Nikon Metrology computed- tomography (CT) system (pictured
at right) to make X-ray CT of 3D-
printed metal parts available to academia and industry throughout the Great Plains. The Model XT H 225 ST system, housed at the university's Nano- Engineering Research Core Facility (NERCF), helps perform fundamental research into the effects of component geometry on overheating during metal powder-bed additive manufacturing (AM). In a technical paper (www.sci- encedirect.com/science/article/pii/S0264 127521002379), researchers propose modeling based on a novel graph-theory approach to predict the thermal history of an AM part during the build process, and correlating the results with the actu- al formation of porosity, inclusions and other flaws.
Thermal-history prediction using graph theory was shown to be impres- sively precise, with results being obtained in 5 min. to within 20 C throughout the build volume. And, ana- lyzing porosity on an Inconel 718 sam- ple, the CT system’s resolution of 15 μm/voxel was even able to determine from the circularity of a pore whether it was formed by escape gas trapped in the melt pool or by incomplete fusion of the powder.
"The equipment not only can inspect the interior of a sample without damage, but measure its dimensions as well,” says Prahalada Rao, associate professor from the UNL Mechanical and Materials Engineering department. “It allows man- ufacturers greater control over the quali- ty of AM or machined parts by allowing them to see flaws that previously were expensive and difficult to find. In some fields, being able to examine the inside
of components could be the dif- ference between safety and tragedy."
Within the first four months of using the X-ray CT system, the NERCF had embarked on numerous external industry projects, including thermal modeling for a manufacturer of AM melt-pool sensors and 3D printing of oscillators for the U.S. Navy. And, discussions are ongoing with- in the automotive-manufacturing sector regarding testing components made using wire-arc AM.
Nikon Metrology: www.nikonmetrology.com
Machine-Learning Software Eases Material-Allowables Development
Through a contract awarded by America Makes and funded by the U.S. Air Force, Senvol has applied its machine-learning (ML) software, Senvol ML, to enable a path to rapid develop- ment of material property allowables for AM. The approach was shown to be more flexible, more cost-effective, more time-effective and just as accurate as a conventional approach to allowables development, according to Senvol offi- cials. An ML approach is extremely flexi- ble and able to handle any change to the AM process, which makes this
approach ideal for sustain- ment in the long-term, the
officials continue.
The America Makes-Air
Force program focused on demonstrating the approach using a Nylon 11 flame- retardant material processed via a polymer powder-bed fusion AM
machine—it has applications for metal and nonmetal AM. As AM has started to enable lightweight and rapidly pro-
duced designs that are revolu- tionary to various U.S. Air Force
and commercial capabilities and applications, these benefits reportedly cannot yet be fully realized due to the time and high cost of allowables devel- opment.
The high cost stems in large part from the fact that material allowable develop- ment requires an enormous amount of empirical data to be generated, at a fixed processing point, meaning that all of the empirical data must typically be regenerated from scratch for each major change in the process. This results in an AM process that is not only costly and time-consuming to implement the first time, claim Senvol officials, but costly and time-consuming to maintain in the long run when changes to the AM process inevitably occur.
Senvol ML software supports the qualification of AM processes and was used in the program to develop statisti- cally substantiated material properties analogous to material allowables. Fur- thermore, it did so while simultaneously optimizing data generation require- ments. The flexible software reportedly can be applied to any AM process, any AM machine, and any AM material.
“AM is a modern and digital manu- facturing method with rapidly tailorable processing,” says Dr. Brandon Ribic, America Makes technology director. “To continue using traditional material allow- ables development approaches is a bot-
8 | 3D METAL PRINTING • WINTER 2022
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