Digital Twins – realistic, virtual replicas of physical assets, systems or processes that can monitor performance, model scenarios and make insight-driven decisions – are becoming a hot topic as businesses rush to be part of the Industrial Internet of Things. They’ve seen how companies like Rolls Royce have used digital replicas of their engines to rapidly model years of engine behaviour and performance, so they can more accurately predict and deliver maintenance requirements for their customers while reducing cost of service. Such benefits mean no one wants to miss out.
Often, though, the businesses that have already invested in Digital Twins are puzzled about why they’re not getting the returns they’d hoped for. They come to us and ask what’s stopping them making the most of the technology and how they can seize the opportunities while avoiding the pitfalls. Our experience tells us there are three critical steps businesses must take:
Most businesses interested in Digital Twins have an idea of what they are, but to invest in the right way they need a greater understanding of what the technology is capable of.
This is an issue with technology in general. It’s developing so quickly that it’s a challenge for businesses to keep up. Our smart supply chain report, for instance, found that 60 per cent of organisations have only a basic understanding of how to apply technology and what the implications might be.
Without knowing what the technology can deliver, companies risk facing two bad options with Digital Twins: implement the technology and hope it brings value, or do nothing and risk missing an opportunity to push the business forward. Small-scale demonstrations are, in principle, a good way to start using new technology but you should only set them up to help with a clear plan, rather than because you’re uncertain of the potential of a full-scale implementation.
Digital Twins can help in various ways. They can monitor the performance of an asset, process or system. They can model the effects of different scenarios. And, in their most evolved cognitive form, they can make decisions about how to make improvements, whether it’s a production line, an engine design or a supply chain.
Most have a good understanding of the benefits of harnessing data through IoT sensors, such as being able to fix machinery before it breaks. Digital Twins give more insight into that data by inferring the causes of issues and predicting what effect different responses will have.
There are various levels of maturity and complexity, and no single approach is the ‘best’ way to go. You might only need to monitor an asset and not a site, for example. But it’s important to know the options early and what they might mean for the whole organisation. That will help you make better decisions as you choose how to use the technology and implement it.
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Like any other technology or business tool, Digital Twins need a specific reason to exist in your organisation. No business says to its IT department: “Get us into the cloud by the end of November” and leaves it at that. They have specific strategic reasons for wanting what the cloud has to offer. And those reasons dictate which services will go into the cloud, in what order and with which provider. It should be the same with Digital Twins. Organisations might think they’re ticking a digital strategy box by starting with a small Digital Twin demonstration, but to succeed and progress, it’ll need a specific problem to solve.
We’ve recently helped a client in the nuclear industry spot how a Digital Twin can help tackle a particular problem: identifying steam losses through 25km of piping across a site and thereby evaluating the return on investment for maintenance decisions. The Digital Twin monitors a targeted area of the plant and the effect of different system configurations, making it possible to automatically identify precursor events before a major fault and trigger a maintenance operation. We’ve also created tools within the digital twin that calculate the cost of the maintenance and compare it against the benefits, allowing the client to prioritise maintenance tasks. This Digital Twin has reduced operating costs by 30 per cent and halved unplanned maintenance. By controlling the steam losses, the client has also cut carbon emissions by 25 per cent.
This focus on specific business problems lowers the risk of a project fizzling out after the initial demonstration because the results weren’t what you’d hoped.
A Digital Twin is more than just a technology investment. If you’re introducing it to monitor production in your factory, it makes sense that the production team needs to know how it will work, how their roles could change, what’s expected of them and what’s at stake for the business. But the rest of the business needs to know too because the results could well reach beyond the production line.
What a Digital Twin tells you can have far-reaching effects, from how you handle data to how you make decisions. You could well find a Digital Twin uncovers options your organisation has never had to consider before. You might sometimes have to make decisions based on these new options in real time. And they’re likely to cut across organisational boundaries. This will have implications beyond technology, including your data and security, operating model, governance and people and culture. All these areas need to be part of your planning when it comes to implementing and adopting Digital Twins.
Digital Twins are a powerful technology. They have the potential to make an impact right through the business. But to get that value, you’ll need to give the Digital Twin a specific brief, rather than implementing it and hoping it will find its own way to reward you. Once the technology solves its first tightly defined problem, excitement will grow, the business case will be more solid and the desire to do more will be stronger. You’ll then need a plan for how to handle the wider impact, from changing how the board operates to making people comfortable with taking orders from machines.