Unlocking digital competitiveness in the OT domain

16 May 2024

Marcel Kelder looks at the barriers and benefits of taking a new technology approach to ensure successful and secure OT/IT convergence.

A digital factory can be considered to be an autonomous but interconnected facility within an industrial ecosystem that leverages digital technologies such as artificial intelligence (AI), Internet of Things (IoT), and data analytics to optimise operations, enhance productivity, and enable real-time decision-making. 

As the trend for digitalisation and autonomy increases, previous automation pyramids no longer work due to their traditional hierarchies. A new approach is required – the technology stack – which is used for transferring Operational Technology (OT) data and Industrial Internet of Things (IIoT) data from the production environment to the cloud. 

The architecture of industrial automation is shifting its technology stack toward a model with the IIoT, Edge Machines and 4G/5G mobile connections, while still addressing the unique requirements of industrial operations – namely safety, availability, and security. This evolution reflects the need to seamlessly connect devices, sensors, systems, and applications within industrial environments, enabling real-time decision-making, predictive maintenance, and efficient resource utilisation. 

IIoT
Those driving Internet of Things (IoT) applications – which seamlessly integrate smart devices with Cloud-based apps – have already embraced the IoT technology stack. This foundational and interconnected architecture plays a crucial role in designing IoT products like smart speakers, health and wellness devices, and thermostats. The same smart IoT devices serve as the foundation for IIoT sensors. These sensors are industrial-grade and certified, equipped with integrated sensors and computing functions, and connected to OT systems via wireless communication technology. 

IIoT devices have a crucial role play in monitoring and controlling various aspects of industrial processes, such as liquids, gases, vibration, temperature, device position, and flow. 

The traditionally wired OT devices and IIoT devices, although both operating within the OT domain, serve distinct purposes. OT devices are designed for control and safety, connected to critical systems such as distributed control systems. Availability and safety are the key focus in OT to ensure smooth and safe operations, however this comes at a price.

IIoT is specifically designed for the production environment, where it utilises devices for less critical applications such as monitoring of less critical assets. Unlike traditional 4-20 mA devices, the cost of deploying IIoT devices is significantly lower – approximately by a factor of 10. The costs associated with traditional OT devices encompass various components such as wiring, power supply, marshalling, programming, and maintaining updated documentation. Adding IIoT devices in the OT domain will enable organisations to improve visibility across the entire production plant. 

Proof of Value initiatives have showcased companies effectively implementing IIoT devices alongside Cloud-based algorithms for predictive maintenance. The return on investment (ROI) for these implementations can often be realised in under a year, primarily due to reduced inspection cycles and fewer unforeseen downtimes.

With the advent of IIoT devices, LoRaWAN has made its way into the OT domain. This is a low-cost Low Power Wide Area (LPWA) network that is deployed in a star-of-stars topology. It operates through gateways (access points) that relay messages between end-devices and a central network server, including the cloud. Notably, LoRaWAN employs unique 128-bit keys for both network and application security. 

Edge gateway 
Collecting and storing OT data is expensive due to the license and deployment cost for data historian systems, and the amount of data generated is constantly growing and evolving. These budget constraints can partially be solved using the cloud and the edge server technology as the platform for storing and processing OT and IIoT data. 

Many of these data historian systems are using OPC Data Access (OPC DA) as the connection with control systems and other systems. This interface has significantly impacted the OT landscape by enabling seamless communication across various OT components. However, it is essential to note that OPC DA, despite being a robust set of specifications, does not inherently address security concerns within its interface specifications. With the introduction of OPC Unified Architecture (OPC UA), security has seen significant enhancements as this standard is designed to address cybersecurity. Its comprehensive security features are integrated into the overall design, making it a good choice for serving as a secure gateway between various OT systems, including OPC DA servers, and the edge server.

An edge server acts as the central data hub, connecting the OT domain with the Cloud environment. Its primary function involves managing secure data traffic and performing on-site data processing to minimise latency when necessary. These servers adopt open architectures, allowing seamless integration with standardised protocols like OPC UA and Message Queuing Telemetry Transport (MQTT). 

MQTT is the most common interface between the OT edge machine and the cloud. On the same platform, various applications coexist, facilitating the algorithms in conjunction with machine learning on-premises.

The cloud 
Many companies have already made substantial investments in the cloud, primarily focusing on the IT domain. However, with the emergence of IIoT devices, extending the cloud’s capabilities for OT applications becomes a challenge because an IT cloud differs from an OT cloud in fundamental ways. An OT cloud has a dedicated architecture that hosts process data and OT applications. Unlike traditional cloud services, which are often public or hybrid, the OT cloud is typically deployed in a private cloud or even within the company’s own data center. OT cloud environments are purpose-built for managing process and production data in conjunction with industrial applications, such as asset performance management solutions and digital twins. These applications play critical roles in optimising industrial processes and ensuring efficient operations. The architecture of an OT cloud must seamlessly interface with OT systems, including edge machines, and handle real-time data streams. These data streams need to be conditioned and classified before it is used in native OT applications. Developing a custom OT cloud can be resource-intensive. As a result, many companies choose to outsource their OT cloud and integrate it with their existing customer IT cloud through a cloud-cloud connection. This approach allows them to leverage OT data expertise without overhauling their entire cloud infrastructure.

Commitment to an innovative approach – overcoming initial obstacles and leveraging cutting-edge solutions such as IIoT, edge and cloud – will set a new standard for the OT domain. It underscores a broader industry trend towards digitalisation and cloud integration, highlighting the critical role of adaptability, collaboration, and technological excellence in achieving safe operational sustainability and efficiency.

Marcel Kelder is a Business Development Consultant for Yokogawa.


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