Reusing engineering design in operations
A hybrid digital twin originates during design, utilizing design models to capture intent and specs. Reduced Order Modeling (ROM) technology enables complex CFD and FEA models for real-time applications, broadening possibilities for complex systems.
Look-ahead performance
Monitoring assets in the field is valuable, but predicting future behavior is ultimately where digital twins provide maximum value. Hybrid digital twins are critical for look-ahead performance prediction in unbounded conditions.
Designing for data and learning from data
A hybrid digital twin embodies a synergy between data and simulation where the simulation provides more data for data models. In contrast, sensor data from the field teaches the model about operational performance.
Closing the design loop
By continuously learning from field data, an updatable twin shows which components and parameters change over time. This information can predict the remaining useful life of a piece of equipment. Tracking this is valuable for predictive maintenance and design teams to see whether equipment performs as expected.
