Digital twins refer to computerized companions of physical assets that can be used for various purposes. Digital twins use data from sensors installed on physical objects to represent their near real-time status, working condition or position.
One example of digital twins can be the use of 3D modeling to create a digital companion for the physical object. It can be used to view the status of the actual physical object, which provides a way to project physical objects into the digital world. For example, when sensors collect data from a connected device, the sensor data can be used to update a "digital twin" copy of the device's state in real time. The term "device shadow" is also used for the concept of a digital twin. The digital twin is meant to be an up-to-date and accurate copy of the physical object's properties and states, including shape, position, gesture, status and motion.
In another context, Digital twin can be also used for monitoring, diagnostics and prognostics. In this field, sensory data is sufficient for building digital twins. These models help to improve the outcome of prognostics by using and archiving historical information of physical assets and perform comparison between fleet of geographically distributed machines. Therefore, complex prognostics and Intelligent Maintenance System platforms can leverage the use of digital twins in finding the root cause of issues and improve productivity.