3 Ways OT-IT Integration Helps Manufacturers Future Proof Their Factories

Synchronize Digital Twins Across IT and OT for Real-Time Simulation

Increasing numbers of manufacturers looking to tap into Industry 4.0 technology are synchronizing digital twins across IT and OT. By linking live telemetry from programmable logic controllers and other OT systems into IT-based simulation platforms, organizations can model production environments in real time — testing process adjustments without disrupting output.

Tools such as NVIDIA Omniverse, for example, can help manufacturers build end-to-end digital replicas of their production lines.

Tim Mirth, senior specialist solution architect for edge business at Red Hat, says real-time simulation represents a major shift for industrial IT.

“Within industrial, timing is everything, and it can’t be off, even by milliseconds,” he explains. “Being able to simulate that in a digital landscape means you no longer need specialized hardware just to validate performance. IT has matured to meet OT’s real-time requirements.”

However, using these new tools effectively requires cultural changes in addition to technological adoption.

“There’s a difference in lingo between IT and OT,” Mirth notes. “You can use the same words, but they mean completely different things.”

He stresses the need for organizational leaders to train IT teams to be OT-conscious, adding that building trust through accurate digital twins is key to modernizing industrial architectures without sacrificing reliability.

“Once you’ve built the digital twin and shown that it works with the same quality and performance OT teams expect, you can move toward a more modern architecture within the facilities,” Mirth says. “That’s when the value of IT and OT working together really becomes clear.”

WATCH: How manufacturers can turn raw data into insights.

Integrating High-Speed 5G and Time-Sensitive Networking

The convergence of private 5G and TSN is beginning to redefine how factories communicate and coordinate critical processes. Together, they promise wireless flexibility with the performance industrial automation demands.

“The challenge in the OT space is that it’s extremely expensive and time-consuming to run wires,” Mirth says. “OT would love nothing else but to remove some of those wires and go wireless. But historically, wireless has not been trustworthy in this space.”

Private 5G addresses that by delivering more reliable wireless in interference-heavy environments, while TSN ensures sub-millisecond precision across devices.

“One of the promises of 5G is that it can work better in those environments by being a little bit more reliable,” Mirth explains. “Another aspect is you need determinism — you need to know that the data is coming in a timely manner.”

That precision is crucial in high-speed operations such automotive robotics, where thousands of movements per second must be perfectly timed.

“The trick is to get the two protocols to sync together,” Mirth says. “Then you would be able to troubleshoot errors and improve processes in ways that weren’t possible before.”

EXPLORE: The multicloud is helping manufacturers get better analytics.

Federated Machine Learning Across Distributed OT Assets

Federated machine learning lets AI training happen at the edge, so sensitive OT data doesn’t need to be centralized.

For industries such as energy and oil, remote sites can run local anomaly detection models tailored to their specific environments, while still contributing insights to corporatewide safety protocols.

CDW’s cloud platform can help aggregate those insights securely to strengthen enterprisewide operations.

Mirth explains training at the edge allows models to adapt to site-specific conditions — such as humidity, heat and chemical interference — that affect equipment behavior.

“Having it local to that thing, only really caring about what’s happening at that particular device, makes a lot of sense,” he explains. “It helps improve processes, spot anomalies and support preventive maintenance — critical in industries like oil and gas where it’s never stopping.”

He adds connectivity gaps at remote sites make this approach even more valuable.

“Often, the communication is intermittent at best,” Mirth says. “By not relying on the cloud, machine learning can still happen locally, keeping operations running.”

Ultimately, manufacturers that take advantage of digital twins, private 5G networks and federated learning can benefit from greater control and visibility into their factory operations.