What is a digital twin?

When an expensive component of a critical mechanical system fails, operations can be seriously impacted. Work stops, a replacement must be ordered, and a technician scheduled. If only you could know two weeks in advance when this critical part would fail. What if the part itself could tell you?

Digital twin refers to the creation of digital models of real-life objects using data from sensors on the objects themselves. More than a simulation, a digital twin is a living model. It allows the user to inspect an object or physical system remotely, or interact with it in a sandbox environment.

The digital twin comes as a natural extension of the Industry 4.0 movement, at the convergence of increased IoT adoption, better and cheaper sensors, and exponential growth in computing power. These advances have allowed simulations and physics models to move from the design phase to monitoring, and even to predictive analytics.

The digital twin removes reliance on physical proximity and introduces the possibility of predictive analytics through simulation. The applications span multiple industries, from optimizing transportation routes, to monitoring performance in manufacturing, to a surgeon digitally exploring a copy of a patient’s heart anatomy to prepare for the surgery.

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