The previous two decades of IT and internet were characterized by the replacement of traditional products and services with their digital counterparts. Books transformed into e-books, printed newspapers became digital, music discs are now streamed on-line, conventional signatures were replaced by digital signatures and so on. These transformations are driving the digitization of the various industrial sectors such as news, media and publishing amongst others.
During the past few years, we are also witnessing the digitalization of industrial processes as part of the industrial internet and the rise of fourth industrial revolution (Industry4.0). The digitization of industrial processes is quite different from the digitization of the above listed examples i.e. of media and publications. In particular, industrial processes have a strong physical dimension, as they are composed of machines, automation devices and other forms of operational technology. Contrary to paper and audio devices, physical devices in the industry cannot be simply replaced by a software program, although it is desirable to control them through software. In this context, the digitalization of industry mandates a bridge between the physical and digital world. The development of a digital bridge between a physical object and a software that controls it, is recently empowered by a very powerful concept which is called “digital twin”.
A digital twin is a dynamic digital representation of one or more physical devices in the cyber world, which acts as a bridge between the physical and digital world. Specifically, a “digital twin” has the following characteristics:
Based on these properties, digital twins can be created for machines, vehicles, tools (e.g., screwdrivers), work stations, engines, turbines, HVAC (Heat Ventilation and Air Conditioning) systems and more. In principle, any physical object can have a digital representation. In practice, such digital models are created and persisted in a cloud computing infrastructure. Their synchronization with the actual physical device is enabled by the deployment of sensors that convey the physical world context to the digital representation. Data from the sensors are used in order to continually collect information about the status of the device and to update the digital twin accordingly. Likewise, digital operations on the digital twin are reflected on the physical object, thanks to the deployment of appropriate actuating functions and devices. In this way, data about the physical devices can be derived instantly which could also be used to analyze against data about a specific business context. On the other hand, a digital twin provides the means for controlling devices and processes in a much flexible and cost-effective way as it’s easier and cheaper to configure IT processes as opposed to operational technology process (e.g., configuration of controllers and industrial devices). This is a great foundation for improving business results, reducing costs and ultimately transforming business operations in many different industrial sectors.
Controlling physical processes and automation operations based on IT is a primary use of digital twins. Another major use case concerns the exploitation of data from the digital twin in order to simulate operations, evaluate what-if scenarios and ultimately take optimal decisions. Along these general lines, some more specific use cases for digital twin are as follows:
As evident from the above-listed examples and use cases, digital twins are used in conjunction with a rich set of other digital technologies, which enable various simulation and control operations. As a prominent example, Big Data analytics is one of the technologies that is used in order to forecasts based on the data of the twin. Likewise, Industrial Internet of Things technologies are closely affiliated to digital twins since these are used to keep them synchronized to the physical world. As another example, cyber-physical systems are an integral element of most of the digital twin applications that involve real-time actuation and control of field operations. The rising momentum of all these technologies are indicative of the opportunities that are now available due to the deployment and use of digital twins.
In the near future we will see a wider deployment and use of digital twins in more industrial sectors and use cases, including consumer settings. It is highly likely that product vendors will provide a digital twin application along with their products. This application will be accessible based on a cloud subscription and will be used to provide accurate information about the status of the product. Take cars as an example: In the future, car owners will be able to access intelligent information about their vehicle in the cloud, based on access and visualization of its digital twin. Furthermore, APIs for digital twin programming will emerge, which will enable a wide range of AI and AR applications. Overall, a lot of exciting opportunities for digital twins lie ahead: Stay tuned.
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