Process / pipeline

Digital Twin Simulation — Hybrid Virtual Replica

Digital Twin Simulation, first conceptualised by Michael Grieves at the University of Michigan around 2002 and formally described in his 2014 white paper, creates a continuously updated virtual copy of a physical system by fusing real-time sensor data with a mechanistic (physics-based) model and machine-learning components. The twin mirrors the physical asset's current state and projects its future behaviour, enabling fault detection, predictive maintenance, and operational optimisation without disrupting the real system.

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Sources

  1. Grieves, M. (2014). Digital Twin: Manufacturing Excellence through Virtual Factory Replication. White Paper, University of Michigan. link
  2. Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H. & Sui, F. (2018). Digital Twin-Driven Product Design, Manufacturing and Service with Big Data. The International Journal of Advanced Manufacturing Technology, 94, 3563-3576. DOI: 10.1007/s00170-017-0233-1

Related methods

ScholarGateDigital Twin Simulation (Digital Twin Simulation (Hybrid Physics-ML Virtual Replica)). Retrieved 2026-06-04 from https://scholargate.app/en/simulation/digital-twin-simulation