What edge computing represents and why it holds the key to Industrie 4.0 implementation
Its benefits and applicable use cases
The role advancement in interconnected technologies such as 5G wireless networks plays in edge computing deployments
The profile of edge computing and its usage in industrial facilities continue to soar because of its ability to enhance the implementation of Industrie 4.0 and support cloud computing frameworks. With the advent of edge computing, also known as Multi-access Edge Computing (MEC), strategic deployments of Industrie 4.0 in the deepest parts of brownfield and greenfield factories is now possible.
What is edge computing?
Edge computing refers to the use of connected devices such as mobile edge devices for example wearables, smartphones and handheld HMIs, as well as the more commonly seen HMIs and Industrial PCs, to execute real-time applications at the network edge. The ability to execute applications at a network’s edge means these applications no longer have to go through a centralized processing platform to be addressed.
Factory owners and facilities that utilize IoT solutions generally struggle with accessing computing resources in real-time due to the use of a centralized computing resource like the cloud. Although the cloud has helped, the need for low latency and high-bandwidth processing to automate processes in real-time meant that using just the cloud wasn’t enough. Edge computing solves the low latency and processing challenge Industrie 4.0 implementations face. Edge computing means almost every smart device will serve as an edge computing conduit in the future.
In edge computing, a resource-constrained edge device also collaborates with cloud platforms when the need for complex analysis or more computing resources arises. An example is storing shop-floor data, which can amount to multiple terabytes. In this situation, the limited storage capacity of a device means it must transfer the data to the cloud. Edge devices also receive data packets from the cloud to handle specific tasks; so, an edge computing architecture consists of the device, application servers, and wireless networks for data transfer.
Edge computing also provides a means to reduce the workload on cloud platforms. If the expectations of 50 billion edge connections deployed across the world by 2022 come to pass, then every device accessing the cloud will surely strain available networks including 5G. To avoid overwhelming networks and the cloud, MEC moves a large chunk of data processing applications to individual devices.
Edge computing is also expected to bring diverse professionals from different industries together to simplify the application of Industrie 4.0. Important stakeholders that hold the future to enhancing its application include those from the telecommunications industry, hardware and software vendors, cloud service providers, and original equipment manufacturers.
Application of edge computing
Edge computing applications are expected to cut across every industry in which real-time data processing is required. Although the manufacturing industry is expected to be the biggest gainer from edge computing, smart cities, healthcare, logistics and supply chain management, and the agriculture industry will benefit from its application in multiple ways.
In manufacturing, edge computing creates a more-affordable pathway to implement large-scale Industrie 4.0 business models. The edge accomplishes this by ensuring standalone devices serve as nodes that expand the computing network within a manufacturing facility. The data captured, processed, and transferred can then be used to monitor machine performance or integrate data-driven processes within the manufacturing shop floor.
Edge computing also enhances the safety initiatives within greenfield facilities. One example is the use of wearables to control autonomous guided vehicles which go off their intended route.
In the healthcare industry, MEC provides multiple avenues for medtech vendors to explore when providing value-based devices to customers. It can keep track of patient vital signs and health condition to tailor patient care to be more efficient or alert professionals about changes in patient condition. The interconnected environment that it enables also leads to a safer, more secure city environment. MEC provides a means of tracking missing individuals or using robotic hardware in search and rescue missions. The interconnectivity also means city-wide systems such as transportation can be better tracked and managed to reduce accidents while improving the services they offer.
The role of 5G in edge computing
5G networks are expected to dominate the wireless scene in the coming years due to the low latency and high-bandwidth data transfer they support. 5G is being developed as an industrial networking tool, unlike its predecessors, and it is expected that 17.6% of all traffic will be 5G related by 2023.
The industrial nature of 5G networking means it will end up providing the connectivity required to enable edge computing deployments within facilities and a wide range of outdoor applications. Other networking solutions such as Bluetooth 5 technology and mesh networks are also expected to feature heavily in edge devices. A combination of edge devices and Bluetooth Mesh networks will bring resilient and reliable data transfers across facilities in remote geographical locations that may limit the propagation of 5G.
What are your edge computing and deployment strategies?
Edge computing provides multiple use cases that vendors and service providers can explore to increase revenue generation across diverse industries. The revenue generation opportunities for hardware vendors include developing wearables that offer low-latency processing. While for software developers, the opportunity to develop applications and tools for edge computing environments exist.
Outside the businesses that thrive on providing MEC services, consumer enterprises can deploy edge computing to accomplish diverse tasks depending on your market position. As stated earlier, MEC can provide the foundation needed to develop a functional condition-monitoring strategy, predictive maintenance strategy, or a data-driven production optimization process within a factory.
Developing a deployment strategy starts with identifying the use case or specific process you intend to optimize. The definition then provides the springboard needed to discover and choose vendors providing edge solutions that meet your specific needs and can be integrated into existing factory systems. A deployment strategy that takes into consideration both existing and new systems will ensure end-users of edge computing reap the rich rewards it offers.
The future of Industrie 4.0 and cloud computing will be shaped by the use of distributed and decentralized computing solutions. Edge computing provides the decentralization and resilience needed to shape that future.