Optimising OEM data for smarter electronics systems

Challenge: Turning raw machine data into real operational value

A company of innovators who tackle problems head-on, Convergix Automation Solutions took action on an issue facing both its OEM and SI customers. The Convergix team noticed that many manufacturers had access to machine data, but not machine data that they could actually use to make decisions. Many of the original equipment manufacturers (OEMs) and systems integrators (SIs) that Convergix serves attempted to monetise dashboards too early, offering visuals without delivering real analytical insight to their own customers.

This left those customers without the clean, contextualised data required to understand performance trends, identify early warning signs of anomalies or degradation, or uncover new value streams.

At the same time, traditional approaches to predictive maintenance focused on detecting machine faults as they were about to occur. This was far too late in the process to take meaningful action. Without consistency in data collection across machines and facilities, both OEM and SI customers struggled to make their operations more predictable, efficient or digitally mature.

Convergix knew that if customers were ever going to extract value from machine data, whether for remote support, further optimisation or AI-driven insights, they needed a foundation of clean, standardised, on‑machine data that could be trusted.

Solution:

To address this challenge, Convergix developed Intuition, an on‑machine performance monitoring platform included as a standard on every machine it ships. Designed from the ground up to reduce the common pitfalls of early data monetisation, Intuition focuses first on capturing clean, contextualised machine data before any advanced analytics are applied.

The foundation of the solution is FactoryTalk Optix, chosen for its flexibility, OPC UA connectivity and ability to run entirely on‑prem. Data is stored in InfluxDB and SQL, visualised through Grafana dashboards, and enriched through time‑series tags selected in collaboration with process experts.

By standardising the way its machines collect data, regardless of controller type or customer environment, Convergix created a consistent ‘single layer’ of truth. This trusted source of truth equips OEMs and SIs to provide their customers with remote support, machine‑to‑machine comparisons, plant‑level visibility and AI‑ready analysis.

“We didn’t want to predict faults. Predicting a failure is far too late. We went after what leads to the fault: machine performance,” said Jared Comer, Senior Application Specialist, Digital Solutions, Convergix Automation Solutions.

The architecture of Intuition allows customers to operate entirely on-prem with no subscription requirements, while still supporting future layers of predictive maintenance, machine learning and autonomous decision-making.

Result:

With Intuition, Convergix customers now have access to trusted, high‑quality data that immediately improves machine visibility and long‑term decision-making. The shift from fault prediction to performance‑based indicators enables operators to catch issues earlier, reducing unexpected downtime and improving throughput.

What began as an OEM‑focused enhancement quickly expanded to full‑scale retrofit deployments across major customer facilities. By standardising and unifying data practices across machines, Convergix also created more connections among its OEM and SI businesses, allowing each side to open new opportunities for the other.

Most importantly, customers now have a useful, fully on‑prem foundation for future analytics and AI.

“Everybody keeps talking about artificial intelligence and predictive maintenance, but no one’s really been able to crack the nut. We feel like we’re really close, if not already there,” Comer said.

With Intuition, Convergix created not just a performance-monitoring solution, but a scalable foundation for digital transformation. It prepares customers for the next generation of predictive, autonomous and data‑driven manufacturing.

Image credit: iStock.com/vm