The Growing Need for Private 5G Networks in Manufacturing Plants
Traditionally, data generated from wired & Wi-Fi-based instrumentation devices installed in manufacturing plants are processed either on the local premises or in the public cloud to control the behavior of these devices. Typically, these devices require highly reliable connectivity for quick communications, a latency of less than 1ms, secure data management and data storage, proper traffic isolation between different critical applications running in the factory, and guaranteed QoS for day-to-day operations managed over the private network.
With potentially hundreds of thousands of critical sensors and control systems used in larger factory environments, 5G private network implementations are increasingly finding a way. 5G networks will be powered by massive, distributed computing, located closer to sensors and machines, and capable of applying artificial intelligence and machine/deep learning algorithms to handle huge amounts of industrial and critical data within the factory environment. A 5G factory has a private network design with its own 5G network built in, where 5G devices, RAN, and core are integrated into a complete ecosystem from end-to-end. A private 5G network does not interface with or leverage resources and functionalities from the public 5G MNO network. However, a private 5G frequency is used when a factory creates its own private 5G network, whereas an MNO’s publicly licensed frequency can be used if the MNO builds a private 5G network for a factory. MNOs’ public 5G networks can be used as backup to an existing private 5G network, enabling it to connect all the manufacturing equipment and devices installed in a factory environment to a public 5G network if the private 5G network fails for any reason.
Network redundancy inside the factory: Why it matters and how to design it
Today, manufacturing is experiencing another inflection point. This time, the technology that’s changing everything is high-performance 5G systems which itself can enable a powerful interplay of disruptive, enabling technologies such as distributed cloud and edge computing, massive IoT, AI and automation, among others.
At Ericsson, we believe the convergence of cellular 5G systems with wired Ethernet-based time-sensitive networking (TSN) delivers the most optimal redundant network design for today’s manufacturing enterprises, offering fully deterministic end-to-end connectivity, and meeting all key requirements on industrial communication technology. We believe this model will be essential to realizing all major industrial automation use cases in the future.
Smart Manufacturing at Audi
Some 5,300 spot welds are required to join the parts that make up the body of an Audi A6. Until recently, production staff used ultrasound to manually monitor the quality of spot welds based on random sampling. Now, however, engineers are testing a smarter way of determining weld quality. They are using AI software to detect quality anomalies automatically in real time. The robots collect data on current flow and voltage on every weld. An AI algorithm continuously checks that those values fall within predetermined standards. Engineers monitor the weld data on a dashboard. If a fault is detected, they can then perform manual checks.
Flight of the navigator – the Airbus quest to build, run its own multi-market 5G network
Airbus’ decision to go it alone, separately from traditional telco operators, is down to security, which remains the north star for digital change in just about every Industry 4.0 scenario. “The data has to be stored on our campus without external connectivity. That is one of the main reasons for selecting private networks.” The only data flowing out of is network data, for network control; all the industrial data remains locked into the edge networks.
But back to the use cases, which are the things on Castagnino’s mind, actually. Private cellular is being used already in Toulouse and Hamburg for site surveillance, flight-to-ground data offloads (“95 percent of the volume”), quality inspections, automated guided vehicles (AGVs), collaborative robotics, digital twins “the shop floor with digital mockup”, private mobile radio (PMR), and asset tracking (“Supply Chain 4.0”, including via international roaming).
Industrial Internet of Things: Real-time remote control of smart factory between Korea and Finland
The Electronics and Telecommunications Research Institute (ETRI) announced that it has succeeded in demonstrating the Industrial Internet of Things service that controls and monitors smart factory facilities and robots in real-time at home and abroad at the same time.
The core of successfully demonstrating the technology is ultra-low latency communication technology. The communication delay between a distance of over 10,000 km is less than 0.3 seconds. It has been demonstrated that factory facilities in Gyeongsan, Gyeongsangbuk-do can be controlled in real-time seamlessly from the University of Oulu in Finland.
TELUS: Solving for workers’ safety with edge computing and 5G
Together with Google Cloud, we have been leveraging solutions with the power of MEC and 5G to develop a workers’ safety application in our Edmonton Data Center that enables on-premise video analytics cameras to screen manufacturing facilities and ensure compliance with safety requirements to operate heavy-duty machinery. The CCTV (closed-circuit television) cameras we used are cost-effective and easier to deploy than RTLS (real time location services) solutions that detect worker proximity and avoid collisions. This is a positive, proactive step to steadily improve workplace safety. For example, if a worker’s hand is close to a drill, that drill press will not bore holes in any surface until the video analytics camera detects that the worker’s hand has been removed from the safety zone area.
Yokogawa and DOCOMO Successfully Conduct Test of Remote Control Technology Using 5G, Cloud, and AI
Yokogawa Electric Corporation and NTT DOCOMO, INC. announced today that they have conducted a proof-of-concept test (PoC) of a remote control technology for industrial processing. The PoC test involved the use in a cloud environment of an autonomous control AI, the Factorial Kernel Dynamic Policy Programming (FKDPP) algorithm developed by Yokogawa and the Nara Institute of Science and Technology, and a fifth-generation (5G) mobile communications network provided by DOCOMO. The test, which successfully controlled a simulated plant processing operation, demonstrated that 5G is suitable for the remote control of actual plant processes.
Nokia creates the perfect pint with 5G technology
Nokia and the University of Technology Sydney (UTS) have announced the successful operation of the world’s first private wireless and 5G connected digital microbrewery. The state-of-the-art facility forms part of UTS’s Industry 4.0 research site and enables thirsty researchers to perfect the art of brewing in the twenty-first century using digital automation.
Utilizing a cloud-based digital twin of an actual brewery to optimize the brewing process, UTS’s Industry 4.0 Nano-Brewery, is part of its new Advanced Manufacturing and Industrial Data Science testbed developed at the UTS Tech Lab. The Nano-Brewery forms part of an international production network, with an identical physical twin set up at TU Dortmund University in Germany. The 5G connected brewery captures and monitors production data at every step of the brewing process and uses this data, together with data from the physical twin in Dortmund and a digital twin in the cloud, to optimize the process.
AI on 5G: inspiring use cases for innovation-hungry businesses
The Ericsson-NVIDIA concept we presented at MWC delivers AI applications at the edge of a high-performance 5G Cloud RAN, allowing for data to be processed on-premise to provide real-time decisions and alerts. Running AI and 5G on the same Cloud infrastructure lowers total cost of ownership and pre-integration makes it much easier for enterprises to adopt AI on 5G solutions.
NVIDIA’s AI-on-5G Platform opens a new technical playbook by delivering AI applications at the edge over a high-performance, software-defined 5G RAN. It’s a homogenous scale-out platform (a rack of 1RU telecom-grade servers running both AI and 5G workloads) that is easily expandable from small to large deployments. Thanks to its modular architecture of AI, 5G, compute and orchestration/management stacks, it can support different customer configurations too.
The Money Is in the Verticals – How Analytics Unlocks 5G Value
In 2019 the race to launch commercial 5G services was hot, with both the USA and South Korea claiming firsts. Gaining early competitive advantage was key for many communications service providers (CSPs). So much so that initial 5G subscription plans for consumers were in many cases set on a par with those for 4G or only slightly higher. 5G SA changes all that by implementing a service-based architecture and the road to value creation is not that steep because native AI/ML analytics capabilities fully harness the power of 5G and enable value extraction and creation for multiple vertical use cases.
DeepSig Achieves Industry’s First AI-Native 5G Call & Why You Should Care
While AI is already used today to help manage wireless networks, AI’s usage in directly learning the signal processing algorithms to transmit and receive wireless signals is unprecedented. Proving AI’s advantages and implementations in 5G radio access components has started now with DeepSig’s AI software demonstrated in the industry’s first 5G AI-Native end-to-end call. DeepSig applies a leading form of AI called deep learning, uniquely implemented inside the physical layer of a 5GNR radio access network. The AI enhanced 5G network performs live over-the-air 5G data connections between smartphones and the internet. This not only proved a deep neural network can be implemented into a working 5G radio access network but more importantly demonstrates reduced processing load and power consumption, reduced latency, and improved signal quality and coverage.
Using blockchain to share and monetize telecoms assets
Weaver Labs will be the open telecommunications partner in the Track & Trust project, which aims to deliver a scalable, cost-efficient communications platform and network combining satellite, IoT mesh and blockchain components, serving mostly supply chain use cases. The end solution will be a modular product that will provide a plug and play communication network that allows for end-to-end tracking of the supply chain. This will start from the initial supply of goods/aid and extend all the way to the last-mile shipments, even when limited or no telecommunication infrastructure is available.
Accelerating mining safety and smart mines with limitless connectivity
Digitalization can have a tremendous impact on safety, giving mine operators a clearer picture of the full breadth of operations, monitoring critical factors like air quality and tunnel strength. An optimized mine, especially one with the latest in 5G-enabled private networks, can give miners those crucial seconds that can save lives.
As private wireless networks, including the latest generation in 5G, help revolutionize mission critical industries across the country, mining stands out as a place where connectivity can foster major improvements, from safety to efficiency and productivity to better sustainability. Mine operations can be optimized by collecting and analyzing tracking data on the precise location and performance of vehicles, equipment and personnel.
This Robotic Avatar Welds, Cuts, Lifts While Controlled By A VR Operator Over 5G
Guardian XT is the latest “highly dextrous mobile industrial robot” from Sarcos. Think of it as the top half of your body with super-strong arms, configurable attachments for different tasks, a built-in battery pack, cameras and sensors for eyes, and a 5G connection for taking orders from a remote operator who sees what the robot sees via a VR headset and wears a motion capture suit so the robot does what he or she does.
With different attachments on its arms, Guardian XT can weld, sand, grind, cut, inspect, and more. Over time the company will be developing more quick-swap attachments for more capabilities, just like an excavating company might purchase different buckets or attachments for its machinery as different jobs have varying requirements. Plus, there’s a three-fingered robotic hand coming that can hold and use many of the tools a human uses today.
John Deere foresees private 5G at its factories worldwide
The $546,000 John Deere spent to acquire 5 CBRS spectrum licenses last year has started the manufacturer on a path it says may eventually lead to private 5G networks in all its factories.
5G will be replacing Wi-Fi in the manufacturing facilities, and Ronning said the number of access points needed to cover the factory floors will drop. “It’s an order of magnitude less radios than what we’re accustomed to,” he said, adding that the 5G radios extend coverage to the area outside the factory as well.
Eventually, other devices and machines on the factory floor will also become more autonomous, Ronning said. “We view this as a key initiative to help us adopt machine learning and AI,” he explained. “As we move forward with further adoptions of those types of technologies we are going to be heavily leveraging the 5G work that we’re doing today.”
This is why railway communications needs great network design
A solid network design is the foundation to deliver on stringent performance requirements associated with mission-critical railway communications and to deliver on consumer expectations, which remain unchanged regardless of being at home or sitting on a train moving at 500km/h.
Network design has the potential to identify the optimal site locations to deliver the target performance at the best TCO, but its complexity cannot be overlooked. While cell planning tools exist, operating them for the right outcome is not trivial and requires highly skilled experts connected to a global knowledge base to keep up to date with the latest industry developments and realize the potential of 5G-based FRMCS.
Industry 4.0 and the Automotive Industry
“It takes about 30 hours to manufacture a vehicle. During that time, each car generates massive amounts of data,” points out Robert Engelhorn, director of the Munich plant. “With the help of artificial intelligence and smart data analytics, we can use this data to manage and analyze our production intelligently. AI is helping us to streamline our manufacturing even further and ensure premium quality for every customer. It also saves our employees from having to do monotonous, repetitive tasks.”
One part of the plant that is already seeing benefits from AI is the press shop, which turns more than 30,000 sheet metal blanks a day into body parts for vehicles. Each blank is given a laser code at the start of production so the body part can be clearly identified throughout the manufacturing process. This code is picked up by BMW’s iQ Press system, which records material and process parameters, such as the thickness of the metal and oil layer, and the temperature and speed of the presses. These parameters are related to the quality of the parts produced.
How to use simulation as a network optimization tool
Imagine watching a live football match in a crowded stadium which causes an expected surge in network traffic. This surge is usually handled by adding a base station. Thanks to advancements in simulators to support multi-user and multi cell coverage as, it can now be used to replicate certain aspects of a real networks. In this blog post we reveal how a radio network simulator can be used to simulate these scenarios and decide on an ideal location for base station placement.