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

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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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Digitizing the manufacturing infrastructure (Authentise Weekly News-In-Review – Week 100)

At Authentise, we are advocates of the idea that data is the new driving force of every industry. Through it, we are finding new ways to address our current limitations and replacing the physical with the digital. Flexibility is the keyword here. Technologies like AM enable us to do away with traditional warehouses and produce spare parts on-demand. This enables companies to save a great deal on maintenance costs, inventory upkeep, and material/production waste. CAD data can be stored throughout the product’s history and replacement parts can be printed even after the product has run its course. Digitizing the pipeline offers the chance to reinvent parts’ designs based on new generative optimizations. These are in turn based off of FEM analysis, which can improve the part’s performance while reducing its weight greatly. A few concerns are still being thought through: IP protection, part qualification and more, but its promise is already being realized.

Digital Inventory: How 3D Printing Lets Manufacturers Rely Less On Warehouses Of Stuff

Digital inventory” is a concept increasingly bandied about in supply chain management. More than a buzzword, the underlying principle is that rather than stock a physical warehouse with mass quantities of spare parts that may or may not be in demand at any given time, including parts for now-obsolete original products, design files for components can be stored digitally and made on demand.

Read the full article here.

FIT AG presents ‘Spare Parts on Demand’ additive manufacturing solution at Formnext

SPOD FIT AG

FIT AG has presented its ‘Spare Parts on Demand’ (SPOD) solution at Formnext which employs additive manufacturing to produce industrial replacement components. It has come about as companies continue to work towards implementing digital inventories which lean on additive manufacturing rather than storing parts is warehouses that have been produced by conventional means. The reason being to save on cost and time.

Read more here.

The Designer Changing The Way Aircraft Are Built

The use of massive computing power to conjure radical new designs automatically – a process known as generative design – is revolutionising the way human designers work, letting us build things we previously couldn’t have imagined. Instead of waiting for inspiration to hit, computers go looking. Handed a set of design constraints – such as making it lightweight, strong and low-cost – generative design software identifies and assesses hundreds or thousands of candidates that all fit the bill, before selecting the pick of the crop.

Read more here.

 

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