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Digital Twin Simulation (elective course)

Niveau

master’s degree program

Learning outcomes of the courses/module

The participants:
• understand the fundamentals of modeling and are able to apply them
• are familiar with typical applications and benefits of simulations
• are familiar with simulation domains and simulation software for smart products and solutions
• are able to create models and simulation workflows
• are able to interpret simulation results
• are able to define a smart connected product
• are familiar with the concepts of the digital twin, condition monitoring, and predictive maintenance

Prerequisites for the course

none

Course content

Fundamentals and Modeling:
-Introduction to digital twins, their significance, and areas of application
-Presentation of the theoretical foundations and methods of modeling

Simulation and Software:
-Overview of simulation techniques and their typical applications
-Introduction to various simulation software tools and practical exercises

Smart Products and Solutions:
-Development and analysis of models for smart, connected products
-Integration of digital twins into IoT systems and their benefits

Advanced Concepts and Applications:
-Introduction to advanced topics such as condition monitoring and predictive maintenance
-Discussion of the role of digital twins in future technological development

Practical Project:
-Planning and implementation of an individual digital twin project to apply the knowledge acquired

Recommended specialist literature

* Pfeffer J.; Produkt-Entwicklung: Lean & Agile; München; 2019
* Schröder A.; Agile Produktentwicklung: Schneller zur Innovation – erfolgreicher am Markt; 2018

Assessment methods and criteria

Written exam or seminar thesis

Language

English

Number of ECTS credits awarded

4

Semester hours per week

Planned teaching and learning method

Lecture, group work, presentation, and discussion of assignments

Semester/trimester in which the course/module is offered

3

Type of course/module

Type of course