The Edge of Innovation: How 5G is Transforming Manufacturing

The next era of industrial transformation is underway as 5G connectivity and edge computing enable smarter, more flexible manufacturing.

New use cases like collaborative robots, augmented reality, and predictive maintenance that leverage ultra-low latency and real-time data processing are emerging across factory floors.

Leading manufacturers are architecting edge computing solutions to unlock these innovations while maximizing performance, reliability and data privacy.

“Edge computing is critical for supporting the kinds of advanced use cases manufacturers want to implement with 5G,” said Dr. Rolf Riemenschneider of the 5G Alliance for Connected Industries and Automation (5G-ACIA).

This consensus mirrors recent data on the growth of the edge computing market. ResearchandMarkets.com forecasts the global industrial edge computing market will reach $15.7 billion by 2026, expanding at a 24% annual growth rate. Manufacturers are propelling much of this growth as they invest in edge infrastructure to enable new smart manufacturing capabilities.

What exactly is edge computing, what use cases does it support, and why are manufacturers embracing it now?

Below we explore the key drivers and real-world examples of industrial edge computing adoption based on a close reading of the 5G-ACIA white paper, “Industrial 5G Edge Computing — Use Cases, Architecture and Deployment.”

Edge Computing Unlocks New Manufacturing Use Cases

Edge computing brings storage and processing power closer to the data source by hosting applications at the “edge” of the network rather than in a centralized cloud. This enables very low latency since data doesn’t have to travel long distances back and forth. Edge servers can also pre-process data before transmitting it, reducing bandwidth needs.

For manufacturers, these capabilities can facilitate use cases with stringent real-time requirements that couldn’t feasibly run in the cloud. “Edge computing enables manufacturers to leverage advanced technologies like artificial intelligence, augmented reality, and collaborative robotics by supporting their latency and bandwidth needs,” said Mike Leff, Vice President at AT&T.

We’re now seeing these use cases gain traction in factories:

• Mobile robots — Autonomous mobile robots rely on edge computing to analyze sensor data in real time so they can navigate safely. A centralized cloud architecture would have too much latency for the split-second course corrections mobile robots need to make. With an edge server on the factory floor handling these time-sensitive computations, mobile robots can confidently perform material transport, inventory scans and other tasks.
• Augmented reality (AR) — AR overlays digital information onto a user’s real-world environment. In manufacturing, AR can guide production workers through complex processes and provide just-in-time training. But the number crunching required for AR — like mapping the environment and positioning 3D overlays — is too intensive for individual smart glasses. Edge computing allows this processing to happen locally, so workers can benefit from AR without any lag time.
• Predictive maintenance — Sensors on production equipment generate massive volumes of data for analyzing machine health and predicting maintenance needs. Transmitting all this data to the cloud for analysis would require substantial bandwidth. Edge computing enables predictive maintenance algorithms to run on local servers, analyzing data in near real-time and keeping only summary insights or maintenance alerts. This approach minimizes bandwidth and keeps sensitive equipment data on-premises.

These examples illustrate the expanded set of use cases manufacturers can explore by leveraging edge computing alongside 5G and IoT. But what exactly does an edge computing architecture entail?

Navigating the Edge Computing Deployment

Implementing edge computing requires evaluating factors like node location, legacy system integration, and public vs. private infrastructure. Manufacturers must balance performance needs with complexity and security considerations.

According to the 5G-ACIA report, a key decision point is where to deploy “edge nodes” relative to the data source. Options include:

• On-premises edge: Locating nodes within the factory floor environment, either close to specific equipment or in an on-site data center. This provides the lowest latency but may require integrating with legacy networking.
• Near-premises edge: Situating nodes nearby the facility, such as in a localized hub serving multiple plants. This adds a bit more latency but can simplify deployment.
• Far edge data center: Leveraging an existing off-site data center from a colocation provider or mobile operator. Farther proximity increases latency, but allows leveraging existing infrastructure.

Manufacturers also need to consider how edge nodes integrate with internal networks and systems. “You likely have data sources and applications scattered across different locations and environments,” said Leff. “Your edge architecture needs to connect this technology ecosystem.”

Options include dedicating 5G network resources solely for edge connectivity or utilizing existing LAN, Wi-Fi and industrial ethernet. Legacy hardware, firewalls and NAT routing may complicate deployment. Leveraging standards like 5G-TSN and OPC UA can streamline integration.

Finally, manufacturers must decide whether to build a private on-premises infrastructure or utilize public multi-tenant edge solutions. “Private edge, while more complex, is the best option for use cases involving highly sensitive data or needing air-gap security,” Leff explained. For less sensitive applications, public edge can provide easier deployment on managed infrastructure.

Architecting for the optimum blend of latency, security and flexibility requires cross-functional collaboration. “IT, OT and connectivity teams all need to come together to design an edge framework tailored for their environment and use cases,” said Riemenschneider.

Standards Evolve to Support Edge Computing Growth

As edge computing gains momentum, technology standards bodies are updating architectures and specifications to ease adoption. Groups like 3GPP, ETSI and the Linux Foundation are driving standards convergence around 5G and edge.

“Standards make integration and interoperability easier for manufacturers. They provide a common framework for edge computing platforms from different vendors,” said Leff.

Specific standards developments include:

• 3GPP Release 17 — Introduces capabilities like platform awareness, improved QoS and time-sensitive networking support that optimize 5G networks for edge computing.
• ETSI Multi-access Edge Computing — Provides an architecture and computing interface for integrating edge applications across different virtualization infrastructures.
• Linux Foundation Akraino Edge Stack — Creates open source software for managing workloads across edge, IoT and cloud environments. Includes blueprints tailored for industrial use cases.

Cross-industry collaboration in these standards bodies is important to ensure edge computing evolves to meet manufacturing’s needs. “3GPP and 5G-ACIA are aligning around vertical industry priorities. This will accelerate realization of new 5G-enabled use cases,” said Riemenschneider.

Manufacturers don’t need to wait for every standard to be perfectly defined before exploring edge computing. “Take incremental steps to pilot edge-connected devices and applications on existing infrastructure now,” Leff recommended. “This will uncover what capabilities to prioritize from standards bodies as they progress.”

Unlocking the Smart Factory of the Future

The manufacturing industry sits on the cusp of a new era of smart connected production driven by 5G and edge advancements. As networked sensors, AR devices, robots and machines proliferate across factory environments, managing and deriving value from all this data becomes critical. Edge computing serves as the key enabler.

“The edge is unlocking use cases that seemed like distant futures just a few years ago,” said Riemenschneider. “But this is just the beginning. We need to keep implementing technology like 5G and edge in real-world environments to refine abilities like determinism, reliability and security to factory-grade levels.”

Standards alignment and systems integration also remain works in progress. “There will be challenges around interoperability, data harmonization and skill gaps as manufacturers implement edge computing,” said Leff. “Ecosystem collaboration will be essential to smooth adoption.”

The convergence of connectivity, cloud and edge is reshaping supply chains as well. “Edge computing distributed across a logistics network creates possibilities for new levels of visibility, automation and resilience,” said Leff.

Despite inevitable hurdles, manufacturers embracing edge solutions today will gain valuable experience that informs their digital transformation strategies. “Companies that invest now in use cases, talent and partnerships to harness the edge put themselves in the best position to lead the future of smart manufacturing,” concluded Riemenschneider.

Here is a closing summary on the opportunities 5G and edge computing present for manufacturing:

The Next Wave of Manufacturing Progress

As this article has explored, 5G connectivity and edge computing represent fundamental advancements that will shape the next era of manufacturing innovation. When combined with complementary technologies like AI, AR, robotics and digital twins, this new platform unlocks transformative potential across the factory environment.

The business benefits span from the supply chain to the shop floor and everywhere in between. Granular visibility into logistics and operations allows dynamically optimizing processes. Augmented workers can perform tasks more accurately and safely. Production lines rapidly adapt to change through advanced automation. Products are designed perfectly the first time. Whole value chains become more responsive to customer needs.

Achieving this future does require thoughtful edge computing strategies and upskilling workforces. But early adopters are already realizing advantages today through focused use cases. And an expanding partner ecosystem eased by common standards helps accelerate implementations.

“We are just scratching the surface of what’s possible in the world of connected industries,” said Riemenschneider. “5G and edge computing provide the foundation.”

Equipped with these modernization tools, manufacturers can build smarter factories, launch innovative offerings and deliver new levels of customer value. The transformative impact across the global industrial economy promises to be profound. Edge and 5G usher in the next wave of manufacturing progress.

Daniel Davenport is an Atlanta-based automotive expert specializing in software-defined vehicles, connected mobility ecosystems, and smart manufacturing. With nearly three decades of experience, he currently serves as a Hybrid Network & Cloud Solutions Specialist at NTT and is an AWS Certified Cloud Practitioner