Digital Twins

Modelling for Reality

A digital twin represents far more than a static computer-aided design model or a traditional simulation. At its core, a digital twin is a dynamic virtual representation of a physical object, process, or system that continuously learns and updates itself from multiple sources throughout its lifecycle.

This virtual counterpart mirrors the life of its physical twin, incorporating real-time data, historical information, and predictive analytics to provide actionable insights that would be impossible to obtain from the physical entity alone.

The fundamental distinction that separates digital twins from their predecessors lies in their living, breathing nature. Where traditional models remain frozen in time, capturing a snapshot of design intent or expected behavior, digital twins evolve continuously.

They ingest streams of sensor data, adapt to changing conditions, and maintain bidirectional communication with their physical counterparts. This persistent connection transforms them from static representations into intelligent companions that can diagnose problems, optimize performance, and even predict future states before issues manifest in the physical world.