Manufacturing is expected to be the leading industry beneficiary of 5G, driving over a third (36%) of the technology’s estimated $930 billion contribution to the global economy by 2030. 5G networks will be pivotal to building the smart factories of the future through applications such as asset tracking, industrial control, and product testing.
Content provided by Jo Gilbert, Technical Director and Connected Manufacturing & Production Lead at the GSMA
Despite the technology’s huge potential, traditional networks have struggled to meet the often-stringent requirements in many industrial facilities. As a result, 5G is currently used primarily to support auxiliary processes in many factories. Extending networks to core production will rely on the technology’s ability to meet the requirements of these demanding use cases. These include high uplink capacity, near-constant availability, and decimeter-level positioning capabilities.
Rising to the challenge, telecom operators are developing 5G networks with deterministic capabilities to ensure the reliability and predictability needed to support critical applications in manufacturing plants.
Meeting the Demands of Industrial Settings
While enterprise 5G has been available for some time thanks to functionality such as ultra-reliable low-latency communications, industrial use cases have been largely limited to support for enhanced mobile broadband (eMBB) scenarios. The limited deployments seen in core production have exposed shortcomings between 5G trial capabilities and the high requirements of many manufacturers.
An analysis of key applications in industrial settings points to 5 parameters pivotal to effective industrial networks:
- latency and reliability,
- jitter,
- uplink bandwidth,
- availability,
- and positioning.
For instance, manufacturers need consistent service availability – often over 99.99% – to support safety-related use cases or to avoid costly pauses in production. Uplink bandwidth requirements can also reach 600 Mbps, driven by demanding applications such as machine vision systems for quality control. Meanwhile, the introduction of location-based services, such as automated guided vehicles (AGVs), has elevated the importance of positioning capabilities. These need to be as accurate to as low as 10 cm.
Deterministic 5G networks, which rely on varying network resources and technology combinations, are paving the way for multi-dimensional service level guarantees that meet many of these tough industrial-grade requirements.
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Deterministic Networks in Action
Initial pilots in manufacturing plants across China have demonstrated the potential of various 5G deterministic technologies working in tandem.
At a steel manufacturing plant, deterministic networks delivered 586 Mbps uplink bandwidth and a low latency of 4ms to enable applications such as AI-based quality inspections and the remote control of cranes and AGVs. In doing so, the plant achieved a defect detection rate of 90%. It also reduced production capacity losses by 92% and cut the number of on-site personnel working in potentially hazardous areas by 65%.
Elsewhere, an automotive manufacturing facility deployed deterministic networks to achieve the 99.99% network availability needed for real-time production monitoring, meter-level positioning to support product transport through AGVs, and uplink bandwidth of 250 Mbps to automate quality inspections at the welding point. Among the business benefits was a 98% reduction in the production line’s annual downtime.
Selecting the Right Technologies
The superposition of technologies can directly enhance network performance. For example, the deterministic networks deployed in the steel plant were achieved through a combination of technologies including time division duplex (TDD) spectrum, 5G LAN, network and service collaboration (NSC), and frame replication and elimination for reliability (FRER).
However, techniques to reduce latency or enhance reliability will often consume radio resources, affecting key parameters such as data rates. In a 5G private network, the performance of various concurrent services may be guaranteed through network slicing and Quality-of-Service mechanisms. But when the demands of these networks cannot be met as expected, trade-offs must be made between reliability, latency, and data rates or capacity.
To simplify the technology combination in a deterministic network, decisions should be made about the features that are most critical to the required use cases. For example, it is difficult for an industrial network to have a large number of terminals while also achieving low-latency transmission. In such a case, the enterprise should consider what is most important between a high number of connections and low latency. In practice, a thorough understanding of the individual needs of an enterprise will be required to select the most suitable technology combination.
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Creating a Truly Smart Factory
While the potential for 5G in manufacturing is vast, various challenges hinder its widespread industry integration. It includes unclear business models, technical capabilities, and complexities with industrial protocol integration. The mobile industry must work to overcome these challenges before 5G networks can be incorporated at scale into primary production processes.
The integration of deterministic networks into vertical industries is largely in the exploration stage at present. Research is underway by international alliances such as the 5G Alliance for Connected Industries and Automation, the Alliance of Industrial Internet, and the Stic5G Consortium. But early deployments in China have demonstrated that these networks can yield significant commercial returns from their use in critical industrial processes, opening the door to the future digital transformation of wider vertical sectors.
To learn more about the GSMA Connected Manufacturing and Production community, available resources and details of our next Connected Manufacturing and Production forum, please visit the GSMA website.
