It’s a good idea to look at a map before you set off on a long car journey, and preferably a digital map with updates on road closures, extreme weather, and traffic hot spots. That map is a digital representation of the physical world. You can use it to preview what’s happening in places you can’t see – to look into the future and plan the best strategy for your journey. It could be called a digital twin of the real-world road network.
The concept of digital twins has huge potential in industry. Imagine installing a wind turbine far out in the North Sea. If you have a digital twin of that turbine – a digital representation of every component, constantly updated with sensor data from the real turbine far offshore – you can monitor performance, check for wear and tear, and anticipate problems before they occur without the need for expensive, time consuming on-site inspections. You can also run simulations of extreme weather events or proposed operational changes to help you anticipate their impact.
The many uses of digital twins
The digital twin concept is not new, but it has only become practical with the rise of the Internet of Things. The advent of the technology to embed sensors in every part of a machine or process, and the network capacity and computing power to handle their output, means digital twins are now being constructed across a wide range of industrial contexts.
Gartner has identified digital twin as a top-ten strategic technology trend for 2018*, defining them as: “a digital representation of a real-world entity or system. In the context of IoT, digital twins are linked to real-world objects and offer information on the state of the counterparts, respond to changes, improve operations and add value.”
Potential applications include:
– A digital simulation of a production line that can be examined for inefficiencies, or to test reconfigurations without the cost of taking the real production line offline.
– A digital twin of a specific asset using live sensor data to show the physical products’ operating health within a virtual environment for troubleshooting, predictive maintenance evaluation, and training.
– A digital twin as a virtual repository of a physical product’s maintenance history and technical data, becoming the single source of truth for a field or depot technician assigned to maintain, service, or modify that asset through visualization.
– Product and process prototyping – digital twins can be combined into new configurations and relationships to test efficiencies and uncover challenges in advance.
It should be noted that the digital twin concept is sometimes parsed into two distinct ideas – the digital twin and the digital thread. The distinction is based on time, with a digital twin being the digital representation of the current state of an asset, and a digital thread being the total record of all states of an asset to the present. The distinction is important for specific use cases – for example maintenance training would probably be done on a digital twin but predictive maintenance would require a long-term digital thread.
Real-world digital twin capabilities
Capgemini has developed digital twin services and technologies that concentrate on three areas: modeling business processes for digital transformation, engineering modeling applications, and digital twin platform services – integrating the capability into IT and operational landscapes.
Working with industrial and engineering software experts AVEVA, Capgemini has developed an enterprise-ready digital twin platform we call Digital Asset Lifecycle Management (DiALM). Deployed with partners in the nuclear, oil and gas, and rail sectors, DiALM has significantly improved asset management (for ISO 55000 compliance), as well as enhancing collaboration between the disciplines that contribute to asset safety, efficiency, and profitability.
Digital twins go global
Digital twin and digital thread capabilities have enormous potential for enabling future operating models, revenue streams, and relationships. They provide the opportunity to use the potentially vast data output of IoT technologies to create new value.
Digital twin technology will also play a growing role in enabling the global cooperation required by the ever-increasing complexity of manufacturing processes, supply chains, and maintenance. For all these operations, it is far more efficient for a globally dispersed team to have access to the same digital models of assets.
Like the road maps we all know and rely on to help us plan, the digital twins help us predict real-world outcomes. They help optimize assets over their lifetimes, reduce maintenance costs, reduce downtime, and even enable us to build new micro services—based on simulations in the virtual world.
Alban Alev Principal Engagement Manager, Capgemini Application Services France