FEATURE Smart factories & software
DROWNING IN DATA, BUT STARVING FOR INSIGHTS
Dan Prudhoe, Senior Solutions Engineer at Solace, explains how a Unified Namespace (UNS) will re-wire the digital foundation to create a shared operational understanding that can support the next era of industrial intelligence
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here is a deep cultural and technical chasm between Information Technology (IT) and Operational Technology (OT) emerging on the digital transformation journey for manufacturers. It’s driven by an unmanageable web of brittle, point-to-point integrations that have accumulated as manufacturers connected more machines, applications, and enterprise systems. This fractured environment makes it difficult to establish a shared operational understanding across systems, even as manufacturers invest heavily in improving operational visibility. While these challenges make AI initiatives more difficult, they also expose a broader architectural problem: enabling timely decisions across increasingly connected systems. It’s no wonder that only 29% of manufacturers are using AI or machine learning at the facility or network level. Enter the Unified Namespace (UNS), an
increasingly important architectural pattern that allows manufacturers to organise operational information into a real-time, contextualised representation of the factory. By creating a shared semantic representation of factory operations, a UNS improves operational visibility and makes information easier to discover and consume across OT and IT. As manufacturers become more successful in organising operational information, they naturally expose the next architectural challenge: enabling independent systems to react to operational changes using a shared operational context.
The manufacturing industry is entering an era defined by the fusion of real-time information and intelligent autonomy. Factories no longer succeed by simply collecting data or optimising isolated workflows; they win by
18 October 2026 | Automation
enabling continuous awareness, intelligent interpretation, and coordinated action across people, machines, enterprise systems, and supply chain partners. This shift reduces decision latency by ensuring the right information reaches the right people and systems while outcomes can still be influenced. This requires operational information to move the moment something changes, flowing across equipment, lines, plants, and enterprise systems without friction. Traditional request-response and poll-based integration architectures were not designed for a world where machines, systems, people, and now intelligent AI agents need to continuously exchange information and respond in real time.
The factory of the future needs something
different – the UNS, a digital system that allows the entire operation to sense, understand, and react in real-time. Over the last decade, manufacturers have invested heavily in automation, industrial IoT, analytics platforms, digital transformation initiatives, and increasingly AI. These technologies have created more data than ever before, but they have also exposed a deeper architectural challenge. Information is often scattered across manufacturing execution systems (MES), enterprise resource planning platforms (ERP), supervisory control systems (SCADA), sensors, and countless other industrial applications. Each system requires custom development, transformation logic, and maintenance. The result? A disconnected ecosystem. This fragmentation creates problems. Data becomes difficult to access, teams spend valuable time integrating applications rather than improving operations, and context is
lost between systems. For instance, a machine can generate a signal indicating a potential failure, but that insight isn’t useful if it doesn’t immediately reach the maintenance team, production planners, or enterprise systems that need to respond. Manufacturers certainly need better operational data, and initiatives like UNS are helping make that possible. As operational visibility improves, however, organisations also need architectures that allow people, systems, and applications to respond consistently to changing conditions. This is where the next evolution of UNS begins. Rather than forcing every system to communicate through custom integrations, UNS creates a common semantic structure that makes operational information easier to discover, consume, and act upon. Instead of asking, “How do we connect this machine to this application?”, manufacturers can begin asking, “How do we expose operational information once so it can be reused by many independent applications, systems, and agents?” That change matters as the collaboration between humans, automation systems, and intelligent technologies deepens. This composability allows new applications, analytics, and AI capabilities to be introduced without continuously revisiting existing integrations. However, as manufacturers move toward
more autonomous operations, manufacturers need to be able to recognise meaningful changes, distribute those events reliably, and enable systems to respond immediately. A well-structured UNS provides the shared
structure and context, but it needs an event- driven foundation underneath it to make that information actionable across OT systems,
automationmagazine.co.uk
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