With the ability to print metal structures with complex shapes and unique mechanical properties, metal additive manufacturing (AM) could be revolutionary. However, without a better understanding of how metal AM structures behave as they are 3D printed, the technology remains too unreliable for widespread adoption in manufacturing and part quality remains a challenge.
Researchers in Lawrence Livermore National Laboratory (LLNL)'s nondestructive evaluation (NDE) group are tackling this challenge by developing first-of-their-kind approaches to look at how materials and structures evolve inside a metal AM structure during printing. These NDE techniques can become enabling technologies for metal AM, giving manufacturers the data they need to develop better simulations, processing parameters and predictive controls to ensure part quality and consistency.
"If you want people to use metal AM components out in the world, you need NDE," said David Stobbe, group leader for NDE ultrasonics and sensors in the Materials Engineering Division (MED). "If we can prove that AM-produced parts behave as designed, it will allow them to proliferate, be used in safety-critical components in aerospace, energy and other sectors and hopefully open a new paradigm in manufacturing."
Measuring in the middle
NDE techniques involve sending signals like X-rays, ultrasound or electrical currents through objects and observing signal changes to infer information or reconstruct an image of what's inside. NDE is important for quality control in all manufactured parts, but for metal AM, it can also help catch printing problems before it's too late.
Most metal AM techniques use heat to bind material together, and since metals are extremely sensitive to heat, structures can change a lot during printing. Heat diffuses from the print surface into the already-printed structure, which can affect how well the material binds, create failure-inducing defects and lead to inconsistent products.
"Evolving processes in the subsurface need to be measured and characterized if you want to have a consistent print quality," said Saptarshi Mukherjee, a research scientist in the Lab's Atmospheric, Earth and Energy Division (AEED). "This is very challenging because most of the current NDE technologies cannot see through heat, and even infrared cameras and antennas only detect heat at the surfaces."
Mukherjee is part of a project to monitor internal temperature during laser powder-bed fusion (LPBF) metal AM using eddy currents, swirling loops of electrical current induced by applying magnetic fields. Eddy currents are sensitive to electrical conductivity, and since conductivity is a function of temperature, eddy current sensors provide real-time localized temperature information from inside structures. Simulations from collaborators at Michigan State University suggested the approach was viable, and the group validated it with a simple experiment, resulting in a recent paper published in Scientific Reports.
"To our knowledge, this is the first time that eddy current sensors have been used to look at these very rapid non-equilibrium thermal processes, which are suggestive of the sort of thermal processes you would see in a metal AM process," said MED postdoc Ethan Rosenberg.
Rosenberg is now leading the experimental testing for a follow-up study using closer to real-world conditions such as non-uniform heating and faster timescales.
Trailblazers
NDE group leader Joe Tringe launched the first Laboratory-Directed Research and Development (LDRD) project in the area in 2018 and ever since, the group has been treading new ground to keep pace with metal AM.
In their first project, the group showed that millimeter wave signatures could efficiently characterize the shape of individual droplets of liquid metal used to create structures in liquid metal jetting. They eventually collected enough data to train a machine learning algorithm to predict droplet shape.
"If we can combine that feedback with system modeling, we may be able to learn whether the print parameters are working or if they need to be changed, in real time, so that we end up with what we want when we're done," said Stobbe.
Follow-up projects expanded to electrical resistance tomography - which measures changes in a current's voltage and electrical potential - X-ray computed tomography, ultrasound and neutron detection, with an emphasis on lattice structures and other complicated geometries.
The group also uses NDE to inspect processing parameters like sonication - using ultrasonic waves to create vibrations and improve homogenization - in laser-based metal AM. In a recent paper published in Communications Materials, the group and collaborators at Pennsylvania State University and Argonne National Laboratory proved they could use high-speed synchrotron X-ray imaging for these measurements. The technique is the first step toward understanding sonication's impact on printing, which will help manufacturers optimize the process to improve part quality.
"A lot of things happen in these AM processes that affect the part, but without using NDE techniques, it's kind of a black box," said Rosenberg. "With ingenuity and good physical understanding, you can open that box to see what's happening inside, and that will hopefully help you control the process."
Enabling the future
The group plans to continue evolving, improving and generalizing a variety of NDE techniques for metal AM, since different techniques are better at measuring different types of information. They also hope to train machine learning algorithms for real-time monitoring and error correction during the print to improve success.
The information they collect along the way will be crucial to enabling widespread adoption of metal AM, and they hope that their work will also help raise awareness of the opportunities for NDE in the emerging field.
"There's a real gold rush aspect to it," said Stobbe. "You're out there doing or measuring things that you know no one has ever done or measured before because this is a new technology, and that's certainly exciting."
Other contributors to the work include MED's Rosa Morales, Jordan Lum, Edward Benavidez and collaborators at the University of Colorado, Boulder.
