Why could ignoring Digital Twins mean double trouble?
Live data was radioed from the front line to update the location of these models and allow for better, more strategic decision making. Digital twins take this concept in the present day – and involve coupling a physical asset or process to a virtual or digital representation – with an output enabling a function or action.
Digital Twins have the potential to be powerful, but with so many definitions, options and applications, they are yet to fully take flight in industry. At Digital Catapult, we increasingly see that many companies either do not know what digital twins are, or are left scratching their heads when it comes to applications or benefits to their business.
Multiple digital technologies are required to get the most out of digital twins – such as artificial intelligence, high-performance connectivity, visualisation techniques, and IoT with powerful compute and simulation requirements – which are potentially complex and expensive today. This leads to another barrier to their adoption: namely businesses being assured that they will get a good return on investment, by proving their worth as efficiently and cost-effectively as possible.
Fully predictive digital twins have the capability to dynamically automate decision making both in operation and planning and forecasting; we’re a little way off this being mainstream, but this use case is starting to emerge and could be completely transformative when it comes to cutting costs, waste and improving assets’ lifecycles.
They are particularly helpful for complex systems which would otherwise be hard to address by a person in real-time. As with all digital innovation, digital twins should be fully embedded in strategic digital transformation programmes or challenges that need solving from the outset. Tacking them on as an afterthought at the end of a project would be like starting from scratch. If this happens, companies can enter a ‘pilot purgatory’, where new concepts get stuck between seed and shelf.
Alongside sectors like engineering and architecture, manufacturing invests one the highest levels of R&D spend in the UK, but investment tends to be focused on product innovation rather than digital technology applications. That said, manufacturing is an area where advanced digital technologies such as digital twins can have the most direct impact, for example optimising the production process or design, or predictive maintenance for equipment or in-life products. For this reason, we are starting to see some leading digital twin implementations in the manufacturing area.
Research centres like the recently launched University of Exeter’s DIGIT Lab are working with Digital Catapult to pinpoint these challenges, and help large businesses use digital technology to transform their business strategies, as we start to look beyond challenges like coronavirus and plan for growth.
Thankfully, we are seeing many customers turn up the heat when it comes to experimenting with advanced technologies. Over the last few years, many have seen pretty much all areas of their lives go ‘digital’, which means the bar is naturally high.
There’s a big expectation from organisations that wherever technology could be developed or applied for gains, it should be – though I’d caution that isn’t always necessarily true. However, sustainability and resilience are two priority challenges that are emerging.
