01
Physics model
Structural mechanics, material models, contact, and loading assumptions.
Digital Twin Engineering
Digital engineering for real medical hardware.
A digital twin is more than an FEA model: it connects a representation of a physical system to relevant data and updates or uses that representation for a defined purpose.
Pragmatic digital twinning
Build only the fidelity the decision requires.
Begin with a validated simulation workflow. Add test, manufacturing, sensor, or operational data when it materially improves prediction or decision-making.
02
Physical evidence
Bench tests, inspections, measurements, or field data appropriate to the system.
03
Decision loop
Compare predictions to observations, characterize uncertainty, and update the engineering assessment.
Terminology matters: A one-time FEA study is a simulation—not automatically a digital twin. We use “digital twin” when an explicit physical-data relationship and updating or decision process exist.
Potential use cases
Digital engineering that earns its complexity.
Examples include fatigue-life assessment informed by measured loads, virtual testing tied to bench data, and component health models using actual usage histories.
Design-stage virtual testing
Model-assisted design decisions backed by verification.
Test-correlated analysis
Compare predictions and physical observations.
Data-informed reliability
Explore changing operating conditions and uncertainty.