Digital Twin
Virtual copy updated with real-time data of a physical system.
Digital twin ( twin) is a constantly updated, virtual and dynamic copy of a physical object, system or process with data from sensors in the real world. Different from a simple 3D model, digital twin reflects that moment of physical twin with real-time data flow; for example, digital bisis of a jet motor remains continuously synchronized with data from temperature, vibration and pressure sensors in the actual motor. In this way, the simulations can also be operated on scenarios that have not yet happened in the real world.
Artificial intelligence significantly increases the value of digital twins: machine learning models can predict a failure before analyzing the images of sensor data (predictable maintenance), so unplanned downtimes and cost-effective repairs can be avoided. This technology has a wide range of applications, from the optimization of production lines, to the creation of smart city planning (the simulating the flow of traffic), to the patient in the field of health. Companies such as Siemens, GE and NVIDIA are among the pioneers of industrial digital twin technology.
Artificial intelligence significantly increases the value of digital twins: machine learning models can predict a failure before analyzing the images of sensor data (predictable maintenance), so unplanned downtimes and cost-effective repairs can be avoided. This technology has a wide range of applications, from the optimization of production lines, to the creation of smart city planning (the simulating the flow of traffic), to the patient in the field of health. Companies such as Siemens, GE and NVIDIA are among the pioneers of industrial digital twin technology.