PROCESS AUTOMATION UNLOCKING OT/IT CONVERGENCE


Valmet explains how improved


cybersecurity is enabling the


integration of OT and IT systems to unlock real- time data flow,


accelerated decision- making and the adoption of AI


n the processing industries, operational technology (OT) systems that control and automate physical industrial operations have traditionally been isolated from information technology (IT) systems that manage data and enterprise-level functions. This separation was largely driven by cybersecurity concerns, leading to strict controls on OT networks and limiting their ability to connect with broader IT infrastructure.


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However, this division has hindered the ability to achieve critical automation advancements. Integrating OT and IT systems enables continuous data flow, unlocking full operational visibility, accelerating decision- making, and allowing for proactive problem-solving. It also lays the foundation for AI-driven process automation, which depends on secure, real-time access to external data to deliver real-time monitoring, predictive maintenance, and adaptive control. This shift is accelerating the development of systems that support secure IT/OT convergence, prompting DCS providers like Valmet to design solutions with cybersecurity and connectivity as foundational elements. “Modern distributed control systems must now enable open yet secure communication across all levels of the automation architecture - bridging OT and IT environments - while protecting critical assets and data. The objective is to advance toward intelligent automation that enhances operational efficiency, increases asset utilisation, and delivers tangible cost savings across the production landscape,” says Taavi Veltheim, Manager, Global Solution Management, DCS at Valmet. According to Veltheim, Operational Technology (OT) systems in the process industries encompass the hardware and software used to control, monitor, and automate physical industrial processes. These systems are critical for ensuring the


28 OCTOBER 2025 | PROCESS & CONTROL


safe, efficient, and continuous operation of equipment such as pumps, compressors, reactors, valves, and other machinery found in industries like oil and gas, chemicals, water treatment, and pharmaceuticals. Without connectivity, linking production systems with business technologies such as analytics tools, cloud platforms, and enterprise resource planning (ERP) systems was not possible. However, connecting these environments delivers benefits by enabling continuous data flow, delivering end-to-end operational insight and allowing organisations to identify patterns, address problems proactively, and make better, faster decisions. AI-driven tools also require access to external information for effective implementation within closed, automated systems. These systems must securely exchange data beyond their immediate environment to harness the full potential of artificial intelligence, particularly generative AI.


With generative AI, even a single well-crafted prompt can potentially expose sensitive intellectual property such as proprietary processes or datasets. Therefore, organisations must strike a careful balance between enabling access to pre-trained models and external insights while enforcing strict data protection measures to safeguard their competitive knowledge and ensure responsible AI deployment.


With AI-driven tools set to transform process automation, the emphasis is shifting to the distributed control systems (DCS) that serve as a foundational component of OT, providing the essential control infrastructure that enables safe, stable, and efficient operation of continuous industrial processes. “Digitalisation initiatives have pushed DCS towards higher levels of connectivity and automation,” says Veltheim. “Today, DCS are expected to provide open and secure connectivity at all levels, including between operational and information systems.”


The integration of


operational and information systems depends on systems that can provide secure, real-time communication across multiple layers of an


organisation’s infrastructure. Distributed control systems serve as critical enablers.


This feature is an extract from a longer piece that can be found at:


https://processandcontrol mag.co.uk/securing-the- future-of-process-automat ion-through-ot-it- convergence/


However, this shift introduces a new layer of complexity: securing the convergence point where data from physical operations intersects with enterprise IT systems. This is where modern distributed control systems play a pivotal role.


To meet these challenges, Valmet has launched the newest generation of its DNA distributed control system. Valmet DNAe was built with IT/OT convergence in mind, offering seamless connectivity from sensors to the cloud via edge technology and industrial- standard interfaces. The integration enables enhanced digital intelligence, paving the way for AI-powered tools at every level. Valmet approached the task by adopting the cybersecurity philosophy known as “security by design.” This school of thought emphasises incorporating security measures from the very beginning of a product’s development cycle, rather than adding them later in response to threats.


At the core of the Valmet DNAe Distributed Control System is the Trusted Information Framework (TIF), which serves as the backbone for communication and data management. Valmet DNAe incorporates endpoint protection measures such as system hardening, antivirus software and application whitelisting to reduce the risk of malware, unauthorised access and system compromise. Encryption protocols, access controls, and VPN tunneling are used to secure data transmissions by encrypting communications and restricting access to authorised users, protecting sensitive information from interception or tampering. These measures support secure remote access, enabling approved personnel to monitor, operate, and maintain all systems from any location while preserving the confidentiality and integrity of all communications.


Valmet www.valmet.com/dnae


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