Monitoring 3D prints – more than just a business boost (Authentise Weekly News-In-Review – Wee
We at Authentise are champions of the idea that 3D printing data must be exploited anywhere it is to be found. This often times comes from the printers themselves, offering KPIs on successful print rates and more. Yet even more information can come from external monitoring systems, which that can provide you with data from within the process itself. The benefits of running a monitoring system are numerous, from helping you identify, and potentially correct, issues from within the process, to giving an unprecedented look at still little-known physical phenomenons. Metal printing, for example, is still grounds of research, as we try to understand the dynamics of precise powder melting and the behavior of very hot particles. Another example would be to track 3D printed objects, based on the unique printing “signature” of each printer (like vibrational micro-defects), and thus being able to tell which printer produced it.
High-Speed Cameras Used to Monitor 3D Printing Process
In a thesis entitled “Process Monitoring for Temporal-Spatial Modeling of Laser Powder Bed Fusion,” a student named Animek Shaurya studies the use of high-speed video cameras for in-situ monitoring of the 3D printing process of nickel alloy 625 to detect meltpool, splatter, and over melting regions to improve the quality of the print.
Read more at 3DPrint.com
New NIST method measures 3D polymer processing precisely
Researchers at the National Institute of Standards and Technology (NIST) have demonstrated a novel light-based atomic force microscopy (AFM) technique–sample-coupled-resonance photorheology (SCRPR)–that measures how and where a material’s properties change in real time at the smallest scales during the curing process. […] Surprising the researchers, interest in the NIST technique has extended well beyond the initial 3D printing applications. Companies in the coatings, optics and additive manufacturing fields have reached out, and some are pursuing formal collaborations, NIST researchers say.
Read the rest here.
This is how researchers can now track 3D printed guns, weapons
According to academics from the University of Buffalo, there is a way to use the ‘fingerprint’ of 3D printers to accurately trace items printed through the machinery, which may include counterfeit goods, guns, and other weaponry. No in-fill patterns are the same, and this is the key to tracking down a specific printer.
“3D printers are built to be the same. But there are slight variations in their hardware created during the manufacturing process that leads to unique, inevitable and unchangeable patterns in every object they print,” says Wenyao Xu, Ph.D., associate professor of computer science and engineering in UB’s School of Engineering and Applied Sciences and lead author of the study.
Read the full article here.
Senvol Developing Machine Learning for US Navy for Additive Manufacturing
Senvol has publicly announced that it is developing data-driven machine learning AM software for the U.S. Navy’s Office of Naval Research (ONR). Senvol’s software analyzes the relationships between AM process parameters and material performance. ONR’s goal is to use Senvol’s software to assist in developing statistically substantiated material properties in hopes of reducing conventional material characterization and testing that is needed to develop design allowables.
Read more here.
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