Digital Twins for Ships, Offshore Platforms, and Marine Infrastructure
Introduction
Digital Twins act as the “virtual nervous system” for modern marine assets, providing a high-fidelity replica of physical reality in a digital space. Digital Twins are the cornerstone of “Remote-First” engineering support, allowing senior engineers to troubleshoot offshore wind farms or complex platforms from a central hub without the need for expensive and risky site visits.
In emerging economies, Digital Twins serve as a vital tool for workforce development and infrastructure leapfrogging. They support immersive “Activity-Based Design” and training, enabling a transitioning workforce to master complex systems in a safe virtual environment before engaging with physical assets. This course explores how to build these virtual frameworks in regions with varying levels of digital infrastructure.
From a lifecycle perspective, Digital Twins enable managers to simulate “what-if” scenarios for refits, dry-docking, and decommissioning. By integrating IoT sensors with virtual replicas, delegates can move past static asset management and into a world of dynamic, real-time lifecycle optimisation that significantly lowers total cost.
Learning Outcomes
1. Design digital twin frameworks that allow for seamless remote asset management.
2. Evaluate lifecycle improvements through virtual simulation and stress testing.
3. Implement “Cyber-Physical” monitoring systems for offshore infrastructure.
4. Optimise dry-docking cycles through predictive digital twin modelling.
5. Facilitate “Innovation Sprints” within a virtualised ship environment.
6. Develop a strategy for integrating twins with existing ERP and maintenance systems
Learning Objectives
1. Understand digital twin architectures and their reliance on high-fidelity sensor data.
2. Apply simulation models to analyse the structural health of offshore platforms.
3. Evaluate lifecycle management improvements using data-driven decision models.
4. Identify the data infrastructure requirements for twins in low-connectivity regions.
5. Map the flow of information from physical sensors to virtual replicas.
6. Assess the impact of digital twins on reducing physical inspection risks for the crew.