Manufacturing is at a pivotal moment. Industry 4.0 has evolved from buzzword to baseline, and leaders are now tasked with enabling flexible, resilient operations at scale—often across hundreds of sites, each with its own mix of legacy systems and modern platforms.
We see a common thread in the conversations we’re having with manufacturers across the country: It’s time to modernize the foundation. Not just for the sake of transformation, but to support real-world needs like safety, uptime, data-driven decision making, and security.
That’s why we’re focused on helping manufacturers shift to composable, edge-ready architectures—infrastructure that’s secure, scalable, and optimized for rapid deployment. These environments give both IT and OT teams the tools they need to innovate safely, drive automation, and monitor performance in real time. They also help bring shadow IT efforts out of the dark, giving engineering teams a supported path to experiment and scale.
Why Edge Is Now
Edge computing has become essential for manufacturers. From real-time safety systems to predictive quality analytics, more workloads are moving to the point of use. This reduces latency, avoids costly data egress, and allows teams to act on insights when and where they matter most. Whether it’s AI inferencing on a line or data acquisition for digital twins, edge is where the action is.
For instance, Baxter International implemented edge computing by deploying wireless sensors to monitor equipment vibration and temperature. This approach enabled real-time anomaly detection, reducing unplanned downtime and maintenance costs across their global manufacturing sites.1
But managing edge at scale is no small feat. Many operations leaders are juggling deployments across remote sites with limited local IT support. That’s where tools like AIOps—artificial intelligence for IT operations—come into play. With the right platform, manufacturers can automate infrastructure monitoring, speed up incident response, and ensure uptime across distributed environments.
Smarter Operations with AIOps
Manufacturers are increasingly adopting AIOps to help:
- Monitor and respond to IT/OT incidents in smart factories
- Predict infrastructure failures to minimize downtime
- Automate anomaly detection across supply chain systems
- Optimize edge performance in remote and rugged environments
AIOps gives teams the visibility and automation they need to manage complexity and keep operations running smoothly.
A real-world example is General Electric’s implementation of AI-driven predictive maintenance. By analyzing sensor data, GE was able to anticipate equipment failures before they occurred, leading to significant improvements in efficiency, cost savings, and operational uptime.2
Security as a Foundation, Not an Afterthought
Of course, none of this works without a strong security foundation. Today’s manufacturers face a layered threat landscape—one that includes traditional cybersecurity risks, as well as emerging AI-related vulnerabilities like prompt injection or untrusted model outputs.
To address this, we’re helping manufacturers adopt advanced security tools like Cisco Hypershield for micro-segmentation and AI Defense for monitoring AI risks. These tools extend protection beyond the network, down to the kernel, virtual machine, and container level—essential for securing modern edge workloads.
For example, IronHeart Manufacturing enhanced its cybersecurity posture by implementing Cisco Hypershield. This solution provided deep workload visibility and enforcement, allowing the company to detect malicious behavior and control lateral movement in case of an attack.3
Access control is also top of mind. Managing who can interact with edge systems—whether it’s internal teams or third-party vendors—requires federated identity frameworks, protocol-specific controls, and full auditing. Alignment with standards like ISA/IEC 62443 and NIST is critical to maintaining both compliance and operational integrity.
The Bottom Line
Modern manufacturing demands a new kind of IT strategy—one that’s agile, secure, and built to support innovation at the edge. Whether you’re modernizing brownfield environments or building greenfield sites from the ground up, Connection can help you design and deploy an infrastructure that delivers on today’s priorities while preparing for what’s next.
If you’e ready to bring visibility, speed, and security to your industrial IT strategy, engage our Manufacturing Practice today to get started.
- https://aws.amazon.com/solutions/case-studies/baxter-monitron-case-study/
- https://www.linkedin.com/pulse/ai-case-study-saturday-predictive-maintenance-alastair-ppt6e
Ryan Spurr
Ryan Spurr is the Director of Manufacturing Strategy and a Helix AI Advisory Director with 25 years of experience in manufacturing, information technology, and portfolio leadership. He leads Connection's Manufacturing practice, go-to-market strategy, client engagement, and advisory services focusing on artificial intelligence, information technology, and operational technology that make manufacturers more digitally excellent.
