Private 5G networks for industrial IoT
IoT has become a part of our everyday lives and is now a critical part of efficient industrial operations. The benefits of private 5G make it an optimal connectivity platform in many industrial environments, enabling multiple key IoT use cases and a wider digital twin philosophy.
What is IoT?
The Internet of Things (IoT) is a concept that has been used since the early 2010’s to describe a network of connected devices and objects that are embedded with sensors, software and other technologies so that they can connect with one another and exchange data over the internet.
IoT is now ubiquitous in many parts of day-to-day life. Objects such as kitchen appliances, home alarms, cars and thermostats can all be connected to the internet. These objects can collect useful data automatically and transmit it to a central system, providing insights that allow us to monitor and manage specific functions.
IoT also facilitate automation, as smart sensors enable a device to act based on the inputs that they have detected. For instance motion-activated lights turn on when they detect motion.
What is Industrial IoT?
Industrial IoT (IIoT) refers to IoT technology used in industrial settings, which generally includes sectors such as manufacturing, transportation, oil and gas, power generation, mines and ports. IoT in this context is used to enhance processes, pick up on inefficiencies and provide information, ultimately saving time and money. Another key focus for IIoT is often improving health and safety.
IoT devices can often be used independently, for instance thermostats and smart watches. Whereas IIoT devices are usually designed to provide data on specific machinery or equipment, so need to be compatible with various legacy devices and machines. One of the key differences between regular IoT and IIoT, is that failure of the former generally results in inconveniences, whereas failure of the latter can often result in dangerous high-risk situations.
How can a 5G private network can enable industrial IoT?
Industrial IoT today is enabled by various forms of connectivity, including Wi-Fi, Bluetooth, industrial ethernet, public cellular (e.g. LTE-M and NB-IoT) and more. Each of these comes with a set of drawbacks. For example:
- Wi-Fi can be unreliable and prone to interference from other devices on the network. For IIoT use cases that are mission critical, the consequences of downtime can be catastrophic.
- Although industrial ethernet provides the reliability required, cabling can prove costly and industrial ethernet is not suited to use cases that require mobility (such as asset tracking, supply chain monitoring) where devices need to be wireless.
- Bluetooth is a widely used short-range technology that benefits from low power consumption and hence long battery life but the primary limitation is its short range and challenges in providing sufficient coverage. To connect hundreds of sensors, a significant number of gateways would be required which can also prove costly.
- LTE-M and NB-IoT meet a lot of the requirements for IoT use cases (including) sufficient indoor coverage) but as these cellular wide area networks cater to IoT use cases, they limit the enterprise’s ability to support more data intensive use cases within their industrial environment (e.g. video ingest and analytics, autonomous mobile robots etc.)
Private 5G provides high speeds and low latency, but the improved reliability and consistency of connectivity is what makes it so suitable for IoT and other use cases. Some industrial setting such as ports, manufacturing campuses and warehouses require both indoor and outdoor connectivity. In these instances, a cellular network is better able to provide reliable coverage in an outdoor environment in comparison to Wi-Fi which can enable mission critical and/or mobility use cases. Such use cases include autonomous mobile robots in manufacturing and logistics, or gantry or quayside container cranes in port environments.
Private 5G vs alternative connectivity technologies
3 key Private 5G industrial IoT use cases
1. Precision monitoring and quality control
In an industrial environment, real time precision monitoring of machine performance and processes, can be highly valuable. In manufacturing, for instance, if machines are not performing as they should be the quality of products can drop of, which can be highly distributive. Reworking or discarding products is very costly, so manufacturers are looking to minimise defects. A private network enables sensors to capture high volumes of data and process this data in real time. The real time processing of data means that any issues can be detected early, preventing any further costly errors. A private network can provide the bandwidth required to stream large amount of data and also the latency required to ensure this data is processed in real time.
2. Workflow and asset tracking
Industrial environments tend to have various kinds of vehicles and materials moving across sites. Human identification and tracking of these moving parts can be slow, costly and often erroneous. Having a single coordinated view of the location of different assets can be highly valuable. 5G can connect low-power tags that are placed on equipment and materials that transmit real-time location data to the cloud, providing full visibility into the whereabouts of assets. This can enable a digital twin for traceability of inventory, reducing loss of assets and improving efficiency. As well as the low latency and bandwidth benefits of private 5G, additional coverage capabilities make it highly suitable for this use case.
3. Advanced predictive maintenance
Inspecting heavy machinery requires downtime and labour, both of which are costly. Following this, maintenance of equipment is expensive and can also lead to large amounts of unplanned downtime, further increasing costs. Equipment breakdown also endangers workers operating the equipment. A private 5G network enables sensors to be attached to critical machinery, even by retrofitting. More sensors can be added even at high volumes of data. These sensors can transmit data back to an AI predictive maintenance platform which can then issue updates and alerts when maintenance is required.
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