Twinning Part 2: Digital Twins in the Real World

In our previous blog, we established the essential elements of a digital twin:

  • The digital twin is a functional, system model of the real-world object.
  • The digital twin’s data elements relating to the real-world object include: identity, time series, current data, contextual data and events. You can use the twin to query the state of the real world object and receive updates and notifications.

To date, digital twins are predominantly used in the Industrial Internet of Things, and certainly in engineering and manufacturing. For example, GE is exploring the technology for aircraft engines. Instead of relying solely on a probability based maintenance schedule and lifecycle management, a digital twin of a given engine will tell an airline or manufacturer exactly when one of its parts will fail, or whether immediate repairs are needed after the aircraft encounters a sudden hailstorm. In these cases, the real-world data taken by sensors on the engine is fed into the digital twin (itself an accurate model of the physical engine), and that digital engine can then model how any damaged or aging components might respond to that aircraft’s next flight without having to take the aircraft out of service to run diagnostic tests.

Where is digital twinning headed in the future? Digital twins of humans could include rich biometric and medical data for analysis and predictive diagnosis. Digital twins of an organization could help define the details of business processes and ecosystem interactions for strategic and operational decision making, and advanced simulation. Sophisticated models of places are underway, so in the future we’ll have digital twins to support smart cities.