The Stack

Getting to grips with digital twins

Digital twins has become one of those industry buzz terms that inevitably creates pressure on companies to evaluate whether it’s a technology that could be beneficial or to dismiss as just another hot-ticket media fad, writes Ali Nicholl, head of engagement at IOTICS. We’re probably all vaguely aware that digital twins have a role to play in our increasingly digitalised world if we’re to fully embrace Industry 4.0. But there are at least two generic misconceptions that seem to put unnecessary obstacles on the pathway to adoption. The first is that digital twins are simply virtual representations of individual assets such as a sensor or component. Second is that the technology can’t be applied to large-scale systems and processes or people and places. Both of these misinterpretations of digital twin functionality can be reframed.

What is a digital twin?

Before breaking open these ‘twin’ misconceptions, it’s important to understand exactly what is a digital twin is. Despite the daunting volume of reading material available on the subject, the concept is remarkably simple and can be summed up in one sentence: a digital twin is a virtual representation of a physical entity. In manufacturing, automation and machine processes the benefits should be obvious – in the most fundamental analysis they’re simply a digital evolutionary extension of putting a dial or a meter (or similar piece of rudimentary analogue instrumentation) on the other end of a wire to create a basic visualisation of what’s going on at the remote business end of, say, a thermocouple or a pressure sensor. And that’s the basis of the first myth. As with so much of what happens in today’s digital space, the transition is ‘smarter’ than just replicating heritage analogue technologies and processes. 

In fact, the notion of digital twinning opens up a new world of interacting with the process in a way that was previously unimaginable. This is because digital twins broker access to data sources, add meaning through semantic data models and extract events to be routed within and beyond organisational boundaries. This generates actionable insights in real-time that can be communicated to stakeholders in your supply chain, clients and partners. It’s a lot more than a digital display. The digital twin creates a virtualisation of any data point – people, places, processes, things – that can communicate with other data points efficiently and without compromising the original data source. These data-based virtualisations are also comprehensive in that they include all the controls necessary for the data to be read and utilised directly by machines. These controls, as well as data, are integral to a twin’s ability to autonomously interoperate and, as a result, enrich customer-centric services. Their power lies not in what they can physically show us, but how they can securely and meaningfully interact with each other and, in doing so, create secure, scalable, adaptable digital ecosystems.

It’s important to realise that digital twins aren’t intended to replace existing technology. Instead, they extend capabilities, increase flexibility and mitigate the risk of businesses failing. Rolls-Royce is harnessing twin-based interoperable ecosystems to deliver its next generation Customer Service 4.0. Elsewhere in in the Rolls-Royce business unit, its Power System division is using digital twin and event data technology to unlock more than 200 data sources, brokering interactions to create digital twins of their in-field assets and to receive real-time event insights across customer, supplier and partner boundaries.

The second myth is that scale is a limiting factor. An entire manufacturing plant can be mapped out using digital twinning technology. There can be twins of any relevant components, twins of assembly lines, even twins of the people who work there. Crucially, you can go big. Whatever the combination of technology, people and assets, enterprises can be modelled at any scale using digital twins. From there, the digital twin grants access to each of these data points individually or as a network of sources that can be combined in unlimited ways. This is a long way from mimicking discrete sensor data or even rearchitecting an entire system. It is leveraging data in a way that provides real-time insight into demand, supply, performance and operations. It is the ability for connected objects to talk to each other and work together to provide entirely new services. A software company recently claimed to have launched the world’s largest digital twin for Shell’s Bonga floating production, storage and offloading (FPSO) vessel. While the scale of this application is impressive, it is theoretically possible to extend the twinning ecosystem to an entire country or planet. Which means that when it comes to digital twins, it’s important to understand what they can do in order to get a steer on the scale and variety of applications to which they can be applied. It’s not just manufacturing that benefits from this brave new digital twin world. NTT is currently working on digital twins of human organs, which will be far more powerful than the Bonga platform twin. The applications are as limitless as the twins themselves. 

But it is the combination of scale and interactivity that holds the real potential for digital twins, with implementations expanding beyond simple visualisations to through-life ‘live’ versions of entire processes, assets and environments. This new generation of digital data twins, which model entire data estates and interact in real-time across corporate boundaries, will fully deliver on their promise and potential once they can meaningfully and securely interact with each other in a dynamic model of the world. The downside is that as interactions between twins increases, so do the implications of this complexity. Paul Miller at Forrester, in his paper Untangle the Digital Twin as Part of Your Product Strategy, uses the analogy of Russian nesting dolls to highlight how complications can stack up in hierarchical levels. 

As virtual versions of assets, systems and processes, digital twins operate in the same way. Just as these dolls need to become bigger and bigger to encase the series of dolls within, so too with digital twins. In the transport sector, such nesting can be visualised in the following sequence: individual components (for example, fan blades) form a part of more complex assets (turbines), nested inside larger system assets (engines), inside asset platforms (planes), which then form part of a service (airline route), which takes its place as part of a digital ecosystem (transportation). Irrespective of its size, each twin plays a role of equal importance to the ecosystem and is capable of interacting across corporate boundaries. Each has its value, although this may vary depending on a user’s role in the supply and demand chain, needs and focus. Factor in that the twins could be owned and operated by multiple entities and the difficulties of navigating or mapping their interrelations and interactions becomes apparent.  

Complexity goes beyond twins nested inside one another, and a simple hierarchy of twins is not going to be sufficient to model the real world. The doll analogy, while useful, is nowhere near perfect because in the world of digital twinning not everything is the same ‘shape’. A way of looking at this is that a train is not a carriage, an engine or turbocharger, and these assets probably won’t be made by the same company or be registered on the same systems. Also, the assumption that everything nests one-to-one breaks down when we consider that the train under scrutiny has multiple carriages. Then, there may be more than one dimension to nesting. Manufacturers make trains and operators run trains: but manufacturers lease trains to more than one operator, while operators run trains from more than one manufacturer.

Ultimately the key benefit of digital twinning lies not so much with what the technology can do or what problem it solves, but with what it enables us to create by harnessing the power of connection. Suddenly, a whole new world of data is available, liberating us from operational islands and allowing us to create more effective business together. Digital twin technology enables us to focus on what matters to companies, their customers and their communities. All we have to do to unlock this world is get past our ‘entry inhibition’ created by misconceptions about scale and function.

See also: Companies could save billions by ditching ‘Hotel California’ cloud for their own infrastructure: Andreessen Horowitz

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