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

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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

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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

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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

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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.

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How AI is changing the face of manufacturing, and much more (Authentise Weekly News-In-Review – Week 85)

As AI is getting a foothold in pretty much every corner of the digital world, industries like manufacturing have a lot to gain by employing its perks. We at Authentise know very well the power of machine learning and the many other tools that enable our customers to get deeper, insightful looks into their production and save time in production. The next generation in Additive AI will likely be in-print monitoring platforms. The way these technologies are affecting every industry scared people into thinking that there’s going to be less room for human employees. Not only will there be value in the collaboration between humans and AIs, but new types of jobs will be created because of it. On a side note, it’s also interesting to see how 3D printing is enabling new computing paradigms to be researched, closing the loop beautifully.

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.

New Supply Chain Jobs Are Emerging as AI Takes Hold

Companies are cutting supply chain complexity and accelerating responsiveness using the tools of artificial intelligence. Through AI, machine learning, robotics, and advanced analytics, firms are augmenting knowledge-intensive areas such as supply chain planning, customer order management, and inventory tracking. What does that mean for the supply chain workforce? It does not mean human workers will become obsolete. In fact, a new book by Paul Daugherty and H. James Wilson debunks the widespread misconception that AI systems will replace humans in one industry after another. While AI will be deployed to manage certain tasks, including higher-level decision making, the technology’s true power is in augmenting human capabilities — and that holds true in the supply chain.

Read the rest at Harvard Business Review.

This AI Calculates at the Speed of Light

Researchers from UCLA on Thursday revealed a 3D-printed, optical neural network that allows computers to solve complex mathematical computations at the speed of light. […] researchers believe this computing technique could shift the power of machine learning algorithms, the math that underlies many of the artificial intelligence applications in use today, into an entirely new gear.

Read the full article at Discover Magazine.

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Matches made in heaven: the crossroads of innovation (Authentise Weekly News-In-Review – Week 62)

Technologies have often found it beneficial to tap into innovations, sometimes from quite different fields, to find new potential directions to explore. Considering 3D printing’s flexibility, it’s only logical to see it being employed to uplift the possibilities of this or that application. For example, AM enables a new generation of implants to include sensors embedded in them, for a better fit and smarter monitoring respectively. Similarly, in a little validation for us: IIoT is making helping Enterprise Resource Planning (ERP) systems make most of its functions, feeding live, relevant and actionable data to businesses. The matrix of explorations is endless, and combining experimental technologies is showing us new ways to manufacture, design and ultimately, thing about innovation.

Renishaw Case Study: Benefits of Smart Implants with Sensor and 3D Printing Technologies

Renishaw and Western University previously set up the Additive Design in Surgical Solutions (ADEISS) Centre on the university’s campus, which brings together academics and clinicians to work on developing novel 3D printed medical devices. The institute is currently developing technology in the sensor implant field, and recently introduced its smart hip concept, which uses accelerometers and temperature sensors to collect patient data, which is later communicated to a remote device.

Read the full article here.

IIoT And ERP: Powerful Combination Fueled By Data

The IIoT bridges the shop floor and ERP software to allow for the creation and sharing of data in real time. With machine connections, such as programmable logic controllers (PLCs) and sensors, production data is linked to lot, serial and batch details for a seamless flow of information through the cloud. Utilizing data from sensors and other Big Data sources helps businesses analyze data quickly and make better informed decisions. Businesses can better monitor inventory replenishment, sales demands, parts replacement — they can improve virtually any business process to reduce operational and maintenance costs. This is exactly the approach Authentise is following with our data-driven MES.

Read more at Manufacturing Business Technology.

Combining augmented reality, 3D printing and a robotic arm to prototype in real time

Robotic Modeling Assistant (RoMA) is a joint project out of MIT and Cornell that brings together a variety of different emerging technologies in an attempt to build a better prototyping machine. Using an augmented reality headset and two controllers, the designer builds a 3D model using a CAD (computer-aided design) program. A robotic arm then goes to work constructing a skeletal model using a simple plastic depositing 3D printer mounted on its hand.

Read the full article at TechCrunch.

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Quality assurance will guarantee AM’s future (Authentise Weekly News-In-Review – Week 25)

AM is transforming the way engineers approach a design problem with enhanced manufacturing possibilities. Nonetheless, there are some crucial steps that need to be taken in order to make AM safe and reliable enough to meet industry standards. Already the scene is making giant strides in its effort to assure quality and the main areas to consider are three: CAD models preparation, AM material inspection and in-print monitoring. Better hardware and dedicated software by Nvidia is making dealing with complex designs much more efficient, unconstrained by performance issues and with new tools to approach AM-specific design issues. Powder micro-structure needs to be within certain parameters for optimal sintering: Carnegie Mellon developed a machine-vision system to classify AM metal powders. For in-print monitoring, GE published new patents to determine the quality of a print from acoustic signatures during the process.

Authentise has developed platforms that take advantage of every major monitoring device. Companies like Nike and Ricoh are using this data-enriched perspective to make smarter decisions on their manufacturing operations.

Read more about it here!

How GPUs Can Kick 3D Printing Industry Into High Gear

GVDB Voxels printed a 3D statue (L) of a complex image (R) with minimal materials and structural support.

At last month’s GPU Technology Conference, HP Labs and NVIDIA described how they’ve worked together to overcome these challenges using NVIDIA’s new GVDB Voxel open source software development kit. […] Hoetzlein said the SDK is designed for simple efficient computation, simulation and rendering, even when there’s sparse volumetric data. It includes a compute API that generates high-resolution data and requires minimal memory footprint, and a rendering API that supports development of CUDA and NVIDIA OptiX pathways, allowing users to write custom rendering kernels.

Read more on NVIDIA’s blog.

Carnegie Mellon develops machine vision autonomous system for metal 3D printing

Assessing the powders at the CMU lab. Photo via CMU College of Engineering.

Research from Carnegie Mellon University’s (CMU) College of Engineering has developed an autonomous system for classifying the metal powders used for 3D printing. Using machine vision technology, the system can identify specific microstructures in the additive manufacturing metal powders with an accuracy of greater than 95%. Metal powders are used in powder bed fusion 3D printers. Understanding the quality of the material is essential to the integrity of the resulting parts. The CMU engineers expect their system to be applied by the 3D printing industry within the next five years as part of the Carnegie Mellon University’s NextManufacturing Center aims.

Read the full article here.

GE publishes patents for powder bed fusion acoustic monitoring processes to qualify metal 3D printed parts

Direct Metal Laser Melting solution from GE Additive. Photo via GE Reports/Chris New

GE has published two patents for additive manufacturing acoustic monitoring processes. Referring specifically to powder-bed fusion techniques, GE hopes to simplify the qualification of printed parts with an in-situ monitoring method using acoustic waves. In turn, the company intends to improve the workflow of 3D printing functional metal parts. […] According to the patent, the acoustic monitoring process may take place upon completion of the build or it, “may take place in real time.” It uses a “known good” (fig. 4)workpiece as comparison, which means the acoustic profile generated by the sensors is compared to the profile of the already qualified part.

Read more about the patent here.

 

Don’t forget to come back next week for another News-In-Review and to check our Twitter feed for more AM and IIoT related news and Authentise service updates!

IIoT, stepping stones to a smarter manufacturing framework (Authentise Weekly News-In-Review – Week 23)

Every business, in manufacturing and otherwise, is coming face to face to the reality of present day interconnected capabilities. The Industrial Internet of Things is often described as the next logical step of the industrial world: after hardware automation comes smart, data-driven, connected way of doing things. The possibilities are astounding and, for many businesses, daunting to achieve, fearful as they are of investing time and money in systems and practices they don’t really understand. Fortunately, first steps are relatively easy to make: Sensors are becoming extremely cheap, making the hardware investment very feasible. “Digital twins” are an example of intuitive, data-driven interfaces for predictive enterprise management. We’re also lowering barriers by becoming more sophisticated: Edge computing lightens the network’s costs compared to trying to eat the cake whole.

PS: Check out what Authentise is doing with IIOT – connecting printers to drive automation and insight for additive manufacturing . 

Research proposes 3D printed sensors to work as warnings in extreme environmental conditions

Researchers at King Abdullah University of Science and Technology, have used 3D Printed sensors to test for levels indicative of forest fires and industrial leaks. This photo is of a controlled fire by Sustainable Resource Alberta, started to promote diversity and create a wall to future fires. Photo by Cameron Strandberg, 38449766@N03 on Flickr

A research team from King Abdullah University of Science and Technology (KAUST) in Saudi Arabia, has published a paper proposing 3D printed disposable and wireless sensors for monitoring large areas. The proof-of-concept study shows the potential of 3D printing as a low-cost method of making fully integrated wireless sensors, which can be utilized in extreme environmental conditions such as forest fires and industrial leaks.

Read the rest of the article here.

Seeing double–digital twins & the future of IIoT

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Digital twin technology has been trending in the news for quite a while, yet it should be no surprise that it’s in the Industrial Internet of Things where the concept of a virtual representation of a physical product or system will be the most valuable. The digital twin paradigm enables manufacturers to do two things–operate factories efficiently and gain timely insights into the performance of the products manufactured in these factories.

Read more about “Digital Twins” on Smart Industry.

Three reasons why edge architectures are critical for IIoT

[IIoT] data is only valuable if it can be accessed and acted upon quickly, efficiently and safely. Effectively accessing data can be especially challenging when you have “things” — such as sensors, devices, flow computers and more — that live on remote areas of the network. […] The data from these remote sites has the potential to generate valuable business, but is often too far away, too expensive or too insecure to transmit for time-critical operations. Edge computing devices can solve the challenge of making this data available in real time.

Read more at IoT Agenda.

 

Keep following us on Twitter, where we share interesting news and updates to our services, and be sure to come back next week for another edition of the News-In-Review!

Authentise Monitor: Cutting-edge computer vision algorithms to detect 3D print failures

We are very excited to tell you that we are releasing a technology critical to address the high failure rate of printers, which can be between 25 to 70% in some cases, according to our partners and users.

The service monitors the print progress using any off-the-shelf webcam combined with Authentise’s cutting-edge computer vision algorithms. If it detects a deviation from the intended build progress, the user is informed by email or text. They can also pause the print remotely and address the failure later, saving time and lost material.

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You can learn more on http://vision.authentise.com.

This is the first time desktop 3D printer users have access to advanced failure analysis systems. We are gathering sign ups on the service website for a private beta. It will be out now in January and reach general distribution in Q1 of 2015.