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The evolution of digital twins – moving beyond the buzzword

‘Digital Twins’ has become a common phrase in engineering. It is used to describe everything from Computer Aided Design (CAD) models to predictive maintenance techniques. This can mean the phrase has become a “buzzword”, often supporting over-promised product solutions.

The excitement surrounding digital twins is due to their ability to provide valuable insights and improve products and processes. They can be a valuable tool for industries involved with large-scale products or projects such as maritime design and consultancy, asset monitoring and sustainment, environment and climate solutions, and defence and security. With such potential for success, it’s no wonder digital twins have become such a catchphrase in engineering and beyond.

What is a digital twin, really?

The official definition from ISO30173:2023 describes a digital twin as “a digital representation of a target entity with data connections that enable convergence between the physical and digital states.”

In plain language, it’s a dynamic model that evolves with its real-world counterpart - mirroring its performance, responding to changing conditions, and providing insights that inform smarter decisions.

But it’s important to stress that a digital twin isn’t a single product. It’s a system of systems; a fusion of simulation, data management, and visualisation that together enable powerful, evidence-based decision-making. The real value lies not in having a twin for its own sake, but in how it’s designed to answer specific operational questions.

At BMT, we always begin with the end in mind. What decisions are you trying to make? What risks need to be reduced? What insights would change your operation for the better? With those answers, we can build digital solutions that are targeted, cost-effective, and scalable.

The building blocks of a digital twin

Every BMT digital twin brings together three key elements:

  1. Simulation – to replicate behaviour and predict performance.
  2. Visualisation – to make complex systems understandable and interactive.
  3. Data integration – to connect the real and virtual worlds in real time.
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This architecture enables organisations to experiment safely in a virtual environment before making costly decisions in the physical one. Whether you’re optimising ship design, planning port operations, or sustaining mission-critical assets, a digital twin provides the confidence to act with clarity.

How BMT differentiates

Our digital twin ecosystem is built on decades of engineering expertise, validated models, and trusted partnerships. We combine proven simulation platforms with advanced analytics and AI - focusing always on reliability, transparency, and measurable impact.

Three of our flagship tools illustrate this approach:

BMT Deep

Advanced interactive data platform for monitoring marine assets and structural integrity – information and visualisation

A cloud-based system that integrates diverse datasets - from metocean conditions to operational data - to deliver real-time insight. With AI-powered analytics and intuitive dashboards, BMT Deep helps operators visualise performance, manage risk, and make evidence-based decisions across global fleets.

BMT REMBRANDT

Precision in simulation. Confidence in command – simulation and visualisation

Our award-winning simulator is the gold standard for navigational and manoeuvring analysis. From incident reconstruction to pilot training, BMT REMBRANDT delivers high-fidelity, data-driven environments that enhance safety and operational performance for ports, operators, and defence customers alike.

BMT RAMtr@ck

Mission-ready maintenance intelligence for maximum asset availability – simulation

BMT RAMtr@ck supports both new asset acquisition and in-service support. It forecasts maintenance requirements, optimises availability, and helps ensure mission-readiness through predictive simulation and lifecycle analytics. 

The future of digital twins

As the boundaries between the physical and digital worlds continue to blur, digital twins are evolving from isolated models into integrated ecosystems; linking assets, environments, and entire supply chains. The challenge is no longer about building a twin; it’s about ensuring interoperability, scalability, and trust.

It is important to start with the end in mind. What decisions are you trying to make? What risks need to be reduced? What insights would change your operation for the better? With those answers, we can build digital solutions that are targeted, cost-effective, and scalable.

Digital twins may have started as a buzzword, but when grounded in engineering rigour and real-world data, they become something far more powerful: a trusted partner in delivery.

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