3D printing scalability: more than a hardware problem (Authentise Weekly News-In-Review – #114)

One of the major hindrances to 3D printing’s expansion right now is scalability. How can a process tailored and designed for customization also be an ideal candidate for the highly systematized environment of a production facility? How can it be employed to retain its features like agility and flexibility while providing the level of performance required to make a business profitable? The answer is multifaceted, and it has to do with the technology itself as well as the infrastructure that we build around it. Researchers are working towards designing printing techniques that are both reliable and efficient at various scales, and significant strides have been made in that regard. In parallel, one must consider the surrounding pieces of this puzzle, such as an automated pipeline and a smart, data-driven decision-making platform. It just cannot work if you couple 3D printing technologies with the old way of making factories work. In many respects, we must rely on AIs and robotic systems to make informed decisions. We are already starting to make this vision come to life, with IIoT networks feeding into simulations and triggering automated processes. Authentise is the leader in data-driven automation for production scale 3D printing: we already use machine learning algorithms to drive our estimation processes and thorough automation features throughout our 3Diax platform, and are excited to show you more of what we are working on very soon!

Israeli company announces tiny triumph in micron-level 3D printing

Nanofabrica micron-level 3D-printed part

Startup Nanofabrica (Tel Aviv) announced that it has developed an AM platform that provides an end-to-end bespoke process for manufacturers seeking micron and sub-micron levels of resolution and surface finish. Nanofabrica’s AM process is based on digital light processing (DLP), which is combined with adaptive optics to achieve repeatable micron levels of resolution. This tool in conjunction with an array of sensors allows for a closed feedback loop.

Read the full article on Plastic Today.

Scalable platform 3D prints bone

3D printed construct

Researchers from Syracuse University have achieved significant progress towards the engineering of large-scale bone tissue scaffolds. Stephen Sawyer and colleagues have designed, built and tested a scalable platform for the structured growth of bone mineral using only a commercially available 3D printer and inexpensive materials. The design surpassed previous difficulties associated with the supply of oxygen to bone growing cells. Traditional designs relied on oxygen diffusion through the cell containing structure, which had, until now, limited the size of bone structures that could be built.

Read the rest here.

Brain code can now be copied for AI, robots, say researchers

Modeling robotics on the human brain

Researchers at the Korea Advanced Institute of Science and Technology (KAIST), the University of Cambridge, Japan’s National Institute for Information and Communications Technology (NICT), and Google DeepMind have argued that our understanding of how humans make intelligent decisions has now reached a critical point. Robot intelligence can be significantly enhanced by mimicking strategies that the human brain uses when we make decisions in our everyday lives, they said.

Read the full article here.

We are going to exhibit at AMUG! Come visit us at booth #37 from March 31st – April 4th.

AMUG_2019_Booth_Map

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

The problems, and solutions, to the IIoT (Authentise Weekly News-In-Review – #110)

The Industrial Internet of Things (IIoT) is taking hold on many industrial settings, and yet we are still far from reaping its true benefits. There are multiple reasons for this, and they have to do with the technical limitations of dealing with a large number of sensors and data, how to interpret it correctly and efficiently and how to create a reliable mesh network to tie it all together. AI may look promising for data handling and predictive systems. However, there are many angles to iron out before these make feasible solutions. AI’s prowess on self-teaching may fall short when, to be useful, it would have to learn and predict countless possibilities of a complex industrial setting. Established technologies, or novel combinations of them, can bring exciting opportunities to the table. RFID tagging for warehouse traceability is a dream come true for spoiling inventories while merging long-range connectivity with cloud services can satisfy a large portion of IIoT applications.

How IIoT and RFID deal with perishable inventory

Screen Shot 2019-02-25 at 11.17.42 AM

In North America alone, billions of dollars of food spoil before reaching customers each year. In the pharmaceutical industry, temperature-sensitive products are regularly damaged due to inappropriate shipping and storing conditions. To gain better visibility into the location and the condition of perishable inventory items, businesses can turn to RFID and IIoT technologies.

Read the full article at Smart Industry.

Is Artificial Intelligence the Answer for IIoT?

Many AI methods are self-taught, so they avoid the need for process mapping and other tedious analytical processes, making it seem to be the right fit for IIoT. Yet, only a few methods will apply. The most useful methods are not greedy for impossible amounts of data. They focus machine learning in explainable ways. The rest will fail badly.

Read more here.

Using LoRa and Google Cloud for IIoT Applications

Image of a gateway communicating with the cloud on LoRa

Pairing LoRa connectivity with the Google Cloud Platform (GCP) can serve a wide range of industrial IoT (IIoT) use cases. The longevity and resilience of LoRa paired with GCP’s robust architecture and commitment to scalable innovation provides industrial operators with the tools they need to build the world of tomorrow.

Read more here.

 

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