The adoption of Industry 4.0 is being driven by its ability to address the challenges faced by today’s users of industrial automation control systems, allowing them to increase competitiveness by optimizing their operations. More precisely, this adoption provides greater process transparency, which in turn allows businesses to better manage their activities.

Transparency is all about being able to extract more data from processes and analyze it to gather meaningful information to get a better and deeper comprehension of what is happening on the factory floor. In fact, it is not possible to know how to improve and control a process if there is not a clear understanding of what it is doing.

This need to extract process information has led to the rise of the Industrial Internet of Things (IIoT), as it provides an effective framework to generate, collect, share and analyze data. This solution is based on the Internet of Things (IoT) with the idea of connecting physical assets, such as sensors and actuators, to controllers and higher-level systems to monitor, control and manage them.

In practice, the IIoT applies the IoT to industrial activities, such as manufacturing. The result is an ecosystem of sensors, machinery and people all connected together that offers a granular view of operations and enables control of any variable that could affect production. The two technologies not only differ in their areas of application, but in their performance capabilities. For example, the IIoT was developed to handle highly time critical processes, such as high-speed packaging machines. Therefore, it required very reliable and predictable communication methods to connect devices such as sensitive and precise sensors to highly sophisticated, advanced controls and analytics. Collected together, these properties as are known as determinism, which is an essential requirement for industrial Ethernet applications.

While the IIoT offers an effective technology platform for Industry 4.0 applications, its foundation is a suitable network with the necessary level of determinism to share all data generated by a process. This transparency depends on convergence, i.e. the ability to combine multiple types of traffic on a single network, which in turn depends on determinism.

The technology that automation is moving towards to address this need for convergence is Time-Sensitive Networking (TSN).

The transformative potential of Industry 4.0-oriented digital technologies in manufacturing is widely
recognised. However, the “explosion” of data these have created is a double-edged sword. On the
one hand, the data has the potential to be transformed into valuable information that can deliver
actionable insights for optimising processes. But on the other, if not managed well, this data threatens to become a tidal wave that will overwhelm companies and create more problems than it solves.

Key to the management of this data is a converged, high bandwidth network infrastructure in order
to succeed with value-adding digital transformation strategies. In simple terms, convergence is
the concept of allowing everything to share the same network architecture to communicate,
hence avoiding the complexity and cost of multiple networks. The ideal system should be the
foundation of high-speed, real-time deterministic communications between disparate devices
and systems, allowing data to be shared across the entire enterprise, regardless of its source or
destination. The ultimate aim is to provide the process transparency required for fully optimised
operations by allowing the data to flow from its source to where it can be processed to obtain
actionable insights and then fed back into the process. This does not just apply to supervisory
systems. Having real-time control and coordination of multiple different shop floor or operational
technology (OT) systems is also critical.

This white paper explores the network technology that can address these challenges, Time-
Sensitive Networking (TSN). TSN can deliver four specific benefits to a range of industries,
specifically:

1. Reduce costs, shorten project timelines and increase uptime by simplifying network
architectures and hence machine designs. By employing convergence, systems no longer
need multiple network types to handle all process traffic.

2. Deliver greater process transparency and optimised operations. As a consequence of
converged network architectures, having data flow to where it is needed is simplified. As we
discussed above, this is the key to managing processes in the best way.

3. Greater productivity, as optimised processes will run in the most productive way.

4. Better integration of OT and information technology (IT) systems, as a converged stream of
data can be shared from the factory floor to supervisory systems more easily. Hence getting
the data to where it can be analysed is simplified and this further contributes to process
optimisation.