Do you have a digital twin?
30 July 2018
When the concept of ‘digital twin’ was sprung onto the unsuspecting manufacturing sector at Hannover Fair in 2015, many did not know what to make of it. Ken Christie, UK director at EPLAN, explains why the digital twin is a trend that’s worth adopting.
Named one of Gartner’s Top 10 Strategic Technology Trends, a digital twin is an accurate virtual model of a process, product or service. The behaviour of this model can almost always be analysed more easily and at lower cost than the behaviour of its real-world analogue. It is also possible to try out new ideas quickly and easily on the digital twin without the risks inevitably associated with experimentation in the real world.
Smart components that use sensors to gather data about real-time status, working condition or position, are integrated within a physical item or machine component. The components are connected to a cloud-based system that receives and processes all the data the sensors monitor. This input is analysed against business and other contextual data.
The way in which companies use digital twins varies greatly, depending on their industry sector. Sometimes they are used in the early design stages to investigate how a component or device will perform. Another frequent application for digital twins is to simulate the operation of a new machine or the device before it is used in a live manufacturing environment. In this way companies can greatly reduce the costs – and the risk of errors – associated with product development.
With the aid of digital twins, engineers can explore the impact of design alternatives without purchasing the components and spending the time necessary to try out multiple versions of a project in the real world. The simulations made possible by digital twin technology allow designers to find out early in the design process whether the project will meet customer requirements or whether modifications will need to be devised and evaluated before physical manufacture commences.
A convenient and cost-effective way of generating a digital twin is by using a computer aided engineering (CAE) software platform. Take for instance the example of a 3D model of a control cabinet. The model is built up and validated according to the real product. This is then the central digital instance for all further processes along the life-cycle of the product. Production, test, commissioning, operation, conversion – they can all be improved and streamlined this way.
What’s more, some of these platforms also provide access to a data portal that includes extensive and comprehensive information about components from a huge range of manufacturers. With this combination of powerful design tools and accurate component data, engineers have everything they need to start generating a digital twin easily and quickly.
But digital twins are not just for the early stages of design; they can also be successfully employed once the machine is built and working! In this situation the digital twin can be used for training staff so that they work more efficiently and make fewer errors, and it can also be used to analyse the behaviour of a machine or system – as an aid to fault-finding, for example, or to examine how it would cope with product changes – without the need for costly and disruptive downtime.
More often than not, digital twins are visualised via 3D CAD solutions. These technologies create a digital product description where the user feels like they are inside the experience rather than watching it on a screen in front of them.
Digital twins and VR are valuable resources. Not only do they help to improve productivity by making fault-finding faster and easier, with a consequent reduction in downtime, but they also allow technicians to inspect malfunctioning equipment in a completely safe way, by working on the digital twin rather than the real thing.
Another important benefit this technology is enabling is that the PDM/PLM system can provide a complete view of the product or machine lifecycle. Thanks to a capability called digital thread, multiple viewers from different departments can look at the same interface of a digital twin by using the same underlying data streams. The beauty of the set-up is that each individual viewer will gain access to their own visualisations as well as supplemental data sources that they are interested in, based on their job role.
Digital twins rely on robust data and analytics, collected at every stage of the product lifecycle. This information allows the designers and users of equipment to make modifications and improvements at each stage. And, thanks to the decentralised and free flow of data, all interested parties can add their know-how and expertise to the project and see it evolve like a living, breathing organism.
The future direction of digital twins and virtual reality is still unscripted for the manufacturing sector. Smart factories and Internet of Things have laid the foundation for a strong and complex knowledge base that is constantly evolving. Perhaps, as a result of this, the applications of digital technology will, in the not so distant future, stretch far beyond human imagination and physical capabilities.
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