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Digital Twin & Simulation (WP)*

Niveau

Master

Learning outcomes of the courses/module

The students:
* 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

Basics and modeling:
-Introduction to digital twins, their importance and areas of application
-Communication of the theoretical principles and methods of modeling
Simulation and software:
-Overview of simulation techniques and their typical applications
-Getting to know various simulation software and practical exercises
Smart products and solutions:
-Creating and analyzing models for smart, communicating products
-Integration of digital twins into IoT systems and their advantages
In-depth concepts and applications:
-Introduction to advanced topics such as condition monitoring and predictive maintenance
-Discussion about the role of digital twins in future technology development.
Practical project:
-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.

Assessment methods and criteria

Project Work and presentation

Language

English

Number of ECTS credits awarded

4

Share of e-learning in %

15

Semester hours per week

2.0

Planned teaching and learning method

Lecture, group work, presentation and discussion of tasks

Semester/trimester in which the course/module is offered

3

Name of lecturer

Prof. (FH) DI Thomas Schmiedinger, PHD

Academic year

Key figure of the course/module

WPF.7

Type of course/module

integrated lecture

Type of course

Compulsory

Internship(s)