Digital Twin & Simulation (WP)*
Niveau
Master
Learning outcomes of the courses/module
The participants:
• understand the basics of modeling and can apply these
• know typical applications and advantages of simulations
• know simulation areas and simulation software for smart products and solutions
• can create models and simulation processes
• can interpret simulation results
• can define a smart communicating product
• are familiar with the concepts of digital twin, condition monitoring, predictive maintenance
• understand the basics of modeling and can apply these
• know typical applications and advantages of simulations
• know simulation areas and simulation software for smart products and solutions
• can create models and simulation processes
• can interpret simulation results
• can define a smart communicating product
• are familiar with the concepts of digital twin, condition monitoring, predictive maintenance
Prerequisites for the course
none
Course content
• Introduction to digital twins, their importance and areas of application
• Communication of the theoretical principles and methods of modeling
• Overview of simulation techniques and their typical applications
• Getting to know various simulation software and practical exercises
• Creating and analyzing models for smart, communicating products
• Integration of digital twins into IoT systems and their advantages
• Introduction to advanced topics such as condition monitoring and predictive maintenance
• Discussion about the role of digital twins in future technology development.
• Planning and implementing your own digital twin project to apply what you have learned
• Communication of the theoretical principles and methods of modeling
• Overview of simulation techniques and their typical applications
• Getting to know various simulation software and practical exercises
• Creating and analyzing models for smart, communicating products
• Integration of digital twins into IoT systems and their advantages
• Introduction to advanced topics such as condition monitoring and predictive maintenance
• Discussion about the role of digital twins in future technology development.
• Planning and implementing your own digital twin project to apply what you have learned
Recommended specialist literature
• Nath, S. V. (2021). Building Industrial Digital Twins : Design, Develop, and Deploy Digital Twin Solutions for Real-World Industries Using Azure Digital Twins.
• Zhang, Y. (2024). Digital Twin Architectures, Networks, and Applications (1st ed. 2024).
• Blaschke, F. (2024). Implementation and Benefits of Digital Twin on Decision Making and Data Quality Management. (1st ed.).
• Digital Twin Technology. (2023). IntechOpen.
• Tao, F., Zhang, M., & Nee, A. Y. C. (2019). Digital twin driven smart manufacturing.
• Zhang, Y. (2024). Digital Twin Architectures, Networks, and Applications (1st ed. 2024).
• Blaschke, F. (2024). Implementation and Benefits of Digital Twin on Decision Making and Data Quality Management. (1st ed.).
• Digital Twin Technology. (2023). IntechOpen.
• Tao, F., Zhang, M., & Nee, A. Y. C. (2019). Digital twin driven smart manufacturing.
Assessment methods and criteria
Project
Presentation
Presentation
Language
English
Number of ECTS credits awarded
4
Semester hours per week
Planned teaching and learning method
Lecture, group work, presentation and discussion of tasks
Semester/trimester in which the course/module is offered
3