A digital twin is a dynamic, virtual model of a physical object, process, or system. Unlike a simple 3D model, a digital twin is a living simulation, continuously updated with real-time data from sensors on its physical counterpart. This allows it to mirror the state, behavior, and performance of the real-world asset. By bridging the physical and digital worlds, it enables advanced analysis, predictive maintenance, and optimization without impacting the physical object itself.
The concept was first publicly introduced by Michael Grieves at the University of Michigan in 2002 as a conceptual model for Product Lifecycle Management (PLM). The term was later popularized by NASA in a 2010 technology roadmap, where they applied the concept to simulate and test spacecraft under extreme conditions, famously creating digital twins of their capsules for the Apollo program.
Digital twins are a cornerstone of Industry 4.0 and are increasingly used across various sectors. In manufacturing, they optimize production lines and predict equipment failure. In urban planning, they create 'smart cities' by modeling traffic flow and energy consumption. The energy sector uses them to manage wind farms and oil rigs, while in healthcare, they are used to create virtual models of organs for surgical planning and personalized medicine.