Course Description
A digital twin is a dynamic virtual model of a physical asset, fed by real-time data, that enables simulation, monitoring, and prediction of performance and failure. Digital twins are becoming a cornerstone of modern asset management and predictive maintenance across energy, manufacturing, and infrastructure.
This course explains the architecture and components of digital twins, how real-time data streams are integrated into virtual models, and how AI techniques are applied for predictive behaviour and anomaly detection. Participants learn to understand, specify, and apply digital twins to improve asset reliability, optimise maintenance, and support decision-making across the asset life cycle.
What you will achieve
By the end of this training course, participants will be able to:
- Define digital twins and explain their components and architecture
- Understand the role of digital twins in asset management and predictive maintenance
- Integrate real-time data streams into virtual asset models
- Use simulation to model asset performance and failure scenarios
- Apply AI techniques for predictive behaviour and anomaly detection
- Understand digital twin platforms and enabling technologies
- Assess where digital twins add value across the asset life cycle
- Plan a digital twin implementation
How the course is delivered
The course combines digital twin architecture theory with practical examples and simulation demonstrations. Participants explore how real-time data, simulation, and AI combine to model asset behaviour.
Real-world digital twin applications from energy, manufacturing, and infrastructure ground the concepts in practice.
Designed for
This training course is ideal for:
- Asset managers and reliability engineers
- Maintenance and operations engineers
- Digital transformation and Industry 4.0 leaders
- Engineers exploring simulation and modelling
- Technical staff evaluating digital twin technology
Daily programme
- What is a digital twin
- Components and architecture
- Digital twins in asset management
- The digital twin maturity spectrum
- Real-time data streams and IoT
- Integrating data into virtual models
- Connectivity and platforms
- Data quality and synchronisation
- Simulation of performance and failure scenarios
- AI for predictive behaviour
- Anomaly detection in digital twins
- Prescriptive insights
- Digital twins across the asset life cycle
- Value assessment and use cases
- Implementation planning
- Case study workshop and review
Certification & accreditation
BII Certificate of Completion
BII Certificate of Completion Upon successful completion, participants receive a BII Development Institute Certificate of Completion with a unique reference code that is independently verifiable. Our certificates are recognised internationally and reflect successful completion of your chosen programme.
