Cursusaanbod

Introduction to Digital Twins

  • Concepts and evolution of digital twins
  • Use cases in manufacturing, energy, and logistics
  • Digital twin architecture and lifecycle

System Modeling and Simulation

  • Modeling dynamic systems with Simulink
  • Physics-based vs. data-driven modeling
  • Visualizing systems with Unity

Real-Time Data Integration

  • Using MQTT and OPC-UA for connectivity
  • Streaming data with Node-RED
  • Ingesting sensor and machine data into the twin

AI and Machine Learning in Digital Twins

  • Integrating AI models for prediction and optimization
  • Using TensorFlow or PyTorch with live data
  • Training models on simulation outputs

Visualization and Dashboards

  • Designing user interfaces for twin monitoring
  • 3D and 2D visualization options
  • Custom dashboards with real-time insights

Case Study: Building a Digital Twin Prototype

  • End-to-end design of a manufacturing asset twin
  • Data integration and machine learning setup
  • Deployment and testing in a simulated environment

Maintaining and Scaling Digital Twins

  • Lifecycle management and updates
  • Interoperability and standards
  • Scaling to multiple assets or processes

Summary and Next Steps

Vereisten

  • An understanding of system modeling or industrial operations
  • Experience with Python or similar programming languages
  • Familiarity with data integration concepts

Audience

  • Digital transformation leaders
  • Plant IT personnel
  • Data architects
 21 Uren

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