Critical infrastructure 2 min read
Connected industrial data: interoperability before artificial intelligence
Many industrial AI projects stall because the data does not talk to itself. OPC UA, MQTT, ISA-95 and IEC 62443 as the basis for connecting without exposing operations.
Almost every industrial company today has an artificial intelligence project at some stage. Many stall at the same point, and not because of the algorithm: plant data lives in controllers, historians, spreadsheets and maintenance systems that share no names, units or timestamps. From Medellín to Singapore, the first successful data project is usually less glamorous than expected.
The bottleneck is not the algorithm
A model that anticipates pump failures needs to know that the historian temperature, the maintenance system work order and the control system alarm all refer to the same piece of equipment. When each system names it differently, most of the effort goes into reconciling data, not analysing it.
A data model before a dashboard
The ISA-95 standard, adopted internationally as IEC 62264, provides a hierarchy to describe the enterprise, sites, areas, lines and equipment, and to define which information flows between operations and business systems. Adopting it, even partially, forces answers to questions that are usually postponed: how each asset is named, who owns that name and what happens when it changes.
Protocols that already exist
| Standard | What it is for |
|---|---|
| OPC UA (IEC 62541) | Data exchange between devices and systems, with an information and security model |
| MQTT (OASIS standard) | Lightweight publish and subscribe messaging, useful on low-bandwidth networks |
| ISA-95 (IEC 62264) | Hierarchical asset model and information exchange between operations and business |
| ISA/IEC 62443 | Cybersecurity for industrial automation and control systems |
Connecting without exposing
Connecting operations to new platforms opens paths that did not exist before. The ISA/IEC 62443 series proposes dividing systems into zones and conduits with security requirements matched to risk, so that data can flow out to analytics without anyone being able to come back in the same way to the controllers. In critical infrastructure, that separation is not optional.
Where should you start?
- Pick a specific problem with measurable value, not a platform.
- Inventory the data sources that problem needs and who manages them.
- Agree on the naming of the assets involved.
- Connect in read-only mode first, with the security architecture already defined.
- Measure the result before widening the scope.
Chosen by shared topics and use case.
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