5G Edge computing will be the brains behind Industrial IoT

The Industrial Internet of Things (IIoT) is one of the most important trends in modern manufacturing. IIoT adoption promises to maximise efficiency, improve safety, make supply chains more flexible and more, but these benefits won’t come automatically. Manufacturers must turn to 5G Edge computing to capitalise on the IIoT’s full potential. Industrial Journalist, Emily Newton, further explores.

What is 5G Edge computing?

Edge computing distributes computing tasks across a network of nearby smart devices. Like the Cloud, it reduces the hardware strain on each endpoint through distribution, but unlike a conventional Cloud, it doesn’t rely on distant data centres. By using local endpoints, it reduces latency and brings data analysis closer to the source of the data.

5G Edge computing bolsters the edge through the speed and capacity of 5G networks. Distributing compute tasks across multiple devices requires considerable throughput and bandwidth to work correctly. 5G – promising speeds of 20Gbps and supporting 1,000 more devices per meter than previous networks — is an ideal solution.

Edge computing helps distribute loads to make the most of 5G’s capacity, while 5G’s speed brings the most out of Edge computing’s distribution and latency. Together, these technologies pave the way for higher, more effective IIoT adoption.

How 5G Edge computing improves Industrial IoT

The Industrial IoT is possible without 5G Edge computing, but only in a limited capacity. Here’s a closer look at how implementing these networks will improve IIoT applications.

Accelerated data analytics

One of the most significant advantages of 5G Edge computing for the IIoT is it streamlines the analytics process. The IoT provides plenty of data to help manufacturers gain insight into their operations, but processing that information typically means sending it to remote data centres. Even with today’s fast Internet speeds, that can introduce latency and reliability issues.

In an industrial setting, a delay of just a few seconds could cause significant problems. Imagine if a robot failed to recognise a human employee in time and caused a collision. Edge networks can reduce Cloud latency by 30%, preventing those accidents.

Faster analytics is more than a matter of safety – it enables connected robotics and sensors to respond to changing conditions in near-real-time. Digital twins would also be more practical, as they’d keep up with their real-world counterparts more closely.

Enabling hyperautomation

These faster data analytics processes let manufacturers expand on automation, too. Automated systems are popular in industrial settings for their efficiency and consistency, but they need assistance with workflow changes. Higher IIoT adoption would boost communication in robotic workflows, helping them adapt and enabling broader automation.

Edge computing and 5G’s latency and capacity improvements can bring IoT connectivity to more automated systems. That interconnectivity lets machines earlier in the process alert downstream equipment of any changes or irregularities, making them more adaptable. This flexibility makes automation more practical, allowing manufacturers to make the most of it.

As automation becomes more versatile, manufacturers could enable hyperautomation, which optimises entire processes through automation instead of improving one aspect at a time. This shift would make industrial facilities more cost-effective, efficient and less wasteful.

Improved cybersecurity

Another way 5G Edge computing will support the Industrial IoT is through security improvements. As manufacturers implement more endpoints, they increase their attack surface, leaving them more vulnerable than they often realise. This trend led manufacturing to become the world’s most targeted industry in 2022, but new networks promise improvement.

Because Edge computing spreads data storage and processing across the entire network, it reduces single dependencies. Consequently, cybercriminals can’t take down the whole system by targeting one vulnerability.

Faster speeds and lower latency also minimise the chances of intercepting this data in transit. Similarly, because 5G Edge networks enable such fast processing, automated monitoring tools can respond in less time. If a breach does occur, manufacturers can contain and mitigate it before it causes widespread damage.

Increased supply chain visibility

5G-powered Edge networks will also expand on the IIoT’s ability to boost supply chain transparency. Organisations must manage multiple vendors and part numbers, which can make gaining insight across the entire supply chain difficult. The IoT’s real-time reporting is a step in the right direction and 5G and Edge computing take it further.

Many companies already use the IoT to gain visibility into their supply chains. 5G Edge computing lets them do so faster and with more devices, enabling quicker responses and providing a more comprehensive picture.

IoT tracking solutions provide data on each shipment from various sources, then Edge computing’s speed enables near-real-time analysis of this information. This quick review can give manufacturers instant insight into incoming delays or disruptions. Their in-facility IoT-connected robots can then automatically adjust to them.

Higher flexibility

These wider, faster networks will also help manufacturers use the IIoT to become more flexible. Domestic boiler manufacturer Worcester Bosch uses 5G to run real-time machine sensors that detect and respond to production line problems before they occur. Without this rapid communication and computation, these machines wouldn’t be able to adjust in time, turning changes into considerable disruptions.

5G-powered Edge networks also let companies roll out programming changes and new features quickly. They can then employ the latest artificial intelligence technologies or adjust to new best practices without disruption, enabling a quicker return on investment.

As supply chain and workforce conditions shift, automated machines’ roles will likewise change. In a conventional setup, that would take considerable time and adjustment. Companies can issue these changes across the entire facility simultaneously with 5G Edge computing and trust the IoT-connected machines will be able to process it quickly.

Remaining challenges and the path ahead

The potential for 5G Edge computing for Industrial IoT applications is impressive, but it’s important to remember some obstacles remain. One of the most significant is the availability of these technologies.

The vast majority of Edge-enabled IoT devices are consumer electronics. Enterprise-grade systems are growing, but not as quickly, so manufacturers face fewer options, which may limit their applicable use cases. That will change over time, but it may hold IIoT’s growth back for now.

Similarly, 5G networks aren’t as widespread as other connectivity platforms. That issue will fade with time and investment, but it will inhibit growth in the near term, like with limited edge devices.

The upside of these issues is that both are a matter of time and technological development. Manufacturers may have to manage their expectations and invest slowly, but if they stay on top of developing trends and approach cautiously, they can take their IIoT investments to the next level.

The IIoT needs 5G Edge computing

The Industrial IoT has massive potential but needs faster connections, more bandwidth and improved computing resources to capitalise on it. 5G Edge computing provides those upgrades.

5G Edge networks are still relatively new, but as they grow, so will their possibilities. Manufacturers that capitalise on this technology early and carefully could see significant growth in the future.

Emily Newton is an industrial journalist with over five years of experience writing technical articles for the manufacturing, engineering and electronics sectors.

There’s also plenty of other industry editorial at IoT Insider’s sister publication, Electronic Specifier. And you can always add to the discussion at our comments section below or on our LinkedIn page here.