Engineers at Lawrence Livermore National Laboratory (LLNL) have developed a way of optimizing the properties of any parts produced via Liquid Metal Jet (LMJ) 3D printing.
Instead of adopting a costly high-speed videography-based approach, the LLNL team has devised a means of combining near-field detection with simulation, to focus on just one parameter when analyzing jetted materials. Leveraging their methodology, the researchers say it’s possible to identify the causes of nozzle issues in real-time, before adjusting a printer’s settings to “guarantee part quality.”
“Our results demonstrate that in-situ monitoring of LMJ is possible with millimeter-wave detection methods,” said the study’s lead author Tammy Chang. “This is exciting because it means we could replace computationally expensive high-speed, high-resolution optical diagnostics to enable real-time performance evaluation and feedback control, to ensure high-quality printed metal parts.”
Diagnosing LMJ issues in-situ
‘Liquid Metal Jetting’ describes a process whereby tiny metal droplets are fired at high speed from a nozzle, to form layers that can be built up into homogeneous parts, in a similar approach to that of inkjet printers. Compared to laser-based systems, however, LMJ machines don’t require the use of hazardous metal powders, thus they potentially offer a safer means of reaching the same ends.
As the technology has continued to find new applications, its performance has also come under greater scrutiny, and nailing down optimal parameter sets has proven to be difficult within certain applications. This is largely due to the fact that jetted materials can be affected by a multitude of factors, ranging from droplet size and jet timing, to velocity, flow rate and temperature.
While high-speed videography is frequently used to analyze LMJ in-action, the approach can only really be employed for a few seconds, as due to processing restrictions, large volumes of data takes days to sieve through. To make real-time analysis more plausible, the LLNL team has therefore developed a scalable approach, that relies more on simulation than capturing gigabytes of information.
Factory-ready LMJ monitoring?
The engineers’ revised diagnostic approach, involves placing an open-ended waveguide perpendicular to a printer during production, so that any jetted droplets pass through the electromagnetic field of its aperture. By doing so, it’s possible to capture the dynamics of metal droplets in-situ, in a way that necessitates the collection of far less data than is required when using video analysis alone.
To put their method into practise, the LLNL team inserted an aluminum waveguide into an LMJ 3D printer’s build chamber, and set up cameras at opposite sides of the system to capture the results. Interestingly, by focusing on one parameter at a time, the researchers were able to accumulate enough data to gain fascinating insights into the behavior of droplets via electromagnetic simulations.
During jetting, for instance, the team were able to non-invasively identify the precise impact that droplet spacing and diameter have on the properties of printed layers. Through further evaluation of their data, the engineers were also able to find the reason behind a clogged print nozzle that occurred in their experiment, as there was an ‘observable variation’ in the wavelengths captured when it happened.
As it turned out, a tension had built up on the nozzle’s surface which prevented the material from being fired, and caused the droplet to stick in place until the printer’s next pulse ejected it. If deployed within a factory environment, the researchers therefore believe their approach could be used to determine the quality of deposited drops in real-time, allowing manufacturers to minimize print failures.
“Getting a clean ejection of a single drop that falls straight down is key to achieving good print quality,” concluded study co-author Andy Pascall. “High-speed videography works well in a lab-scale environment where we are testing new print parameters, but will never work in production. This type of diagnostic will be very useful in a production environment.”
While the LLNL diagnostic tool is currently capable of detecting features down to a size of 400–500 𝜇m, the team say that the frequency of their set-up could be raised in future to enable the monitoring of 50–100 𝜇m droplets. Alternatively, using other signal processing methods, it may even be possible to turn it into a closed-loop system, in which data can be used to adjust printing parameters on the fly.
AM’s material jet methodologies
Like many advanced production processes, material jet 3D printing is the subject of constant R&D, in which engineers are attempting to hone its mass manufacturing capabilities. That being said, it would be a mistake to think that the technology hasn’t found end-use applications already, as several firms across the industry now market technologies which could justifiably be called ‘material jetting.’
Stratasys, for example, continues to make significant strides forward with its Polyjet technology, and opted to launch the desktop J35 Pro earlier this year. Designed to make the company’s material jetting process accessible to those working in an office setting, the system is said to be ideal for protoyping both consumer and electronic goods as well as academic applications.
With Multi Jet Fusion (MJF), HP has developed another well known-material jetting technology, which has been adopted by 3D printing providers around the world. What’s more, as the compatibility of its machines have broadened, so have their applications, and the likes of Materialise has previously launched dedicated materials that are designed to unlock the potential of HP systems.
Elsewhere, material jetting specialist XJet has found end-use dental applications for its ceramic-compatible Carmel 1400 3D printer, via a collaboration with Straumann. The system’s high-throughput and soluble support compatibility are said to be beneficial to the firm, in that its dental professionals are now able to spend more time with patients, as they don’t have to worry about post-processing printed parts.
The researchers’ findings are detailed in their paper titled “Millimeter-wave electromagnetic monitoring for liquid metal droplet-on-demand printing,” which was co-authored by T. Changa, S. Mukherjee, N. N. Watkins, E. Benavidez, A. M. Gilmore, A. J. Pascall and D. M. Stobbe.
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Featured image shows the LLNL team’s experimental material jetting diagnostic set up. Image via the Journal of Applied Physics.
