Monitoring 3D prints – more than just a business boost (Authentise Weekly News-In-Review – Week 94)

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

camera2

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

182682_web

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

screen-shot-2018-10-19-at-10-17-52

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

Screen Shot 2018-10-22 at 12.15.26 AM

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.

 

We’ll be at Formnext in Frankfurt from the 13th to 16th November. Come see us at booth #B30J.

Follow us on Twitter to keep updated on AM & IIoT related news as well as updates to Authentise’s services!

The Confluence of AI and AM (Authentise Weekly News-In-Review – Week 92)

We’ve witnessed how the digital age is transforming the manufacturing industry and nowhere it is more apparent than in the contributions that AI is giving to the field. Advanced computing capabilities are being coupled with full-spectrum sensors and autonomous “thinking”. These systems are being developed in AM for a variety of benefits. First, they can help with in-process fault detection, constantly monitoring the printer for defects where the human eye can’t see and even adjust it to fix the problem on the spot. Bringing a trustworthy AI system in the fray opens up possibilities for decentralized manufacturing, where human skill isn’t needed to produce good quality, reliable parts. Such manufacturing units can be located anywhere, operate autonomously and even cooperate with one another to reach a certain goal. Authentise is presently using AI technologies to drive process estimates, providing an accurate, reliable window into your operations.

 

US Navy and Lockheed Martin Are Building AI-Driven 3D Printing Robots

Lockheed Martin

A new generation of smart 3D printers is under development which will use artificial intelligence to oversee and optimize 3D printed parts. The US Navy’s Office of Naval Research (ONR), which is funding the ambitious project, has recently announced a two-year $5.8 million contract. There are four partners working on this project, led by Lockheed Martin’s Advanced Technology Centre. The collective aim is to be able to create robots that can make independent decisions on how to optimize the production of complicated 3D printed parts.

Read the rest here.

 

Mobile Robots Cooperate to 3D Print Large Structures

A team of robot arms on mobile bases can 3D print large structures quickly

Roboticists at Nanyang Technological University in Singapore have, for the first time (as far as they know), performed “the actual printing of a single-piece concrete structure by two mobile robots operating concurrently.” The big advantage of this system is that you can use it to build structures that are more or less arbitrary in size without having to change the system all that much, since the robots themselves can define their own build volume by moving around.

Read more at IEEE Spectrum.

 

Kansas State University Researchers Develop AI System For 3D Printing Process Monitoring

Researchers from Kansas State University’s Department of Industrial and Manufacturing Systems Engineering (IMSE) have developed a new quality monitoring system for the 3D printing process. With integrated supervised machine learning, a camera, and image processing software, the researchers created a production quality monitoring system for assessing 3D printed parts in real-time.

Read the full article here.

 

We’ll be at Formnext in Frankfurt from the 13th to 16th November. Come see us at booth #B30J.

Follow us on Twitter to keep updated on AM & IIoT related news as well as updates to Authentise’s services!