The manufacturing sector serves as a prime example of how and where 5G should impact future IoT-enabled devices. Experts and analysts agree that the "fourth industrial revolution" is here and that manufacturing presents the largest revenue opportunity for IoT-related industries. This is happening in several ways.
First is data acquisition. IoT and IIoT have already enabled machines that were assembled in the pre-internet era to effectively connect to people, systems, infrastructure and newer machines. With the arrival of 5G, with its lower latency, higher throughput, lower energy consumption and mMTC (massive machine type communication) capabilities, the amount of machines and things that could be connected changes by an order of magnitude.
This means that on a 5G-driven factory floor, tens of thousands of sensors could be leveraged to ensure and optimize data acquisition—beyond what the machines on the floor could capture. As manufacturers continue to explore ways of making production more modular to support product customization, cost efficiencies should also come from 5G wireless capabilities which will reduce the amount of cabling needed.
Second, 5G supports agile, more modern architectures that should enable specific, mission-critical, operations to have (among other things) routing priority, quality-of-service, and enhanced security, thereby increasing performance and potentially decreasing downtime.
A third and last point is that 5G also supports ultra-reliable low latency communication (URLLC). URLLC allows a network to process incredibly large amounts of data with minimal delay so that applications could instantly respond to changing data. This is essential for a plethora of use cases where humans and machines (like AGVs or robots) come in close proximity to each other, as well as optimizing machine learning models like the one at Corning's fiber optic cable manufacturing facility in Hickory, N.C., where they are using Verizon's 5G technology to explore ways to enhance factory automation and quality assurance with machine learning, as well as augmented and virtual reality.