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| Code: WIB21-WPM-T-121 |
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2V+2U (4 Semesterwochenstunden) |
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5 |
| Studiensemester: 5 |
| Pflichtfach: nein |
Arbeitssprache:
Englisch |
Prüfungsart:
Project work
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Prüfungswiederholung:
Informationen bzgl. der Prüfungswiederholung (jährlich oder semesterweise) finden Sie verbindlich in der jeweiligen Studienordnung.
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WIB21-WPM-T-121 Wirtschaftsingenieurwesen, Bachelor, Ordnung 01.10.2021
, 5. Semester, Wahlpflichtfach
geeignet für Austauschstudenten mit learning agreement
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Die Präsenzzeit dieses Moduls umfasst bei 15 Semesterwochen 60 Veranstaltungsstunden (= 45 Zeitstunden). Der Gesamtumfang des Moduls beträgt bei 5 Creditpoints 150 Stunden (30 Std/ECTS). Daher stehen für die Vor- und Nachbereitung der Veranstaltung zusammen mit der Prüfungsvorbereitung 105 Stunden zur Verfügung.
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Empfohlene Voraussetzungen (Module):
Keine.
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Als Vorkenntnis empfohlen für Module:
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Modulverantwortung:
Prof. Dr. Frank Kneip |
Dozent/innen:
Prof. Dr. Frank Kneip
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Lernziele:
After successfully completing the module, students are able to:
1. Analyze a real-world problem and derive a requirements specification with measurable criteria
2. Design, build and commission a functioning mechatronic prototype in order to solve the problem
3. Connect and program sensors and actuators on an Arduino-based microcontroller platform
4. Differentiate between potential error sources and examine their influence on the quality of the results
5. Evaluate alternative technical solutions and component choices with respect to technical performance, cost, availability and risk
6. Judge the technical and economic feasibility of their solution, including a cost estimate for a scale-up
Moreover, after successfully completing the module, students are able to:
7. Acquire suitable measurement data related to the problem
8. Apply classical methods of data analysis (e.g. descriptive statistics, time series analysis) to their own measurement data using a suitable software environment (e.g. Python, MATLAB, Excel).
9. Apply LLMs/ChatBots for AI-based data analysis methods to their own measurement
10. Interpret results of their data analysis with respect to the problem
Furthermore, after successfully completing the module, students are able to:
11. Plan and conduct a team project (work packages, schedule, budget), and present and document the results in a professional manner
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Inhalt:
The module follows a project-based approach:
Students are given or identify a real world problem themselves.
Students design and implement the solution, supported by mentoring.
The module consists of
1. Introduction and problem finding
2. Mechatronic system design and component selection
3. Implementation
4. Measurement and data acquisition
5. Classical and AI-based data analysis
6. Project management and economics
7. Presentation and documentation
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Weitere Lehrmethoden und Medien:
Team projects with milestone reviews and mentoring
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Sonstige Informationen:
Assessment:
Project demonstration, presentation and documentation
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Literatur:
* Samanta, B. (2023): Introduction to Mechatronics: An Integrated Approach, Springer, Cham.
* Rahman, M. M., Mahbub, F., Tasnim, R., Saleheen, R. U. (eds.) (2024): Mechatronics: Fundamentals and Applications, Springer, Singapore
* Hering, E., Schönfelder, G. (eds.) (2022): Sensors in Science and Technology: Functionality and Application Areas, Springer Vieweg, Wiesbaden
* Shumway, R. H., Stoffer, D. S. (2025): Time Series Analysis and Its Applications: With R Examples, 5th ed., Springer, Cham (Springer Texts in Statistics, ISBN 978-3-031-70583-0)
Trummer, I. (2025): Data Analysis with LLMs: Text, Tables, Images and Sound, Manning, Shelter Island (ISBN 978-1-63343-764-7)
* Banzi, M., Shiloh, M. (2022): Getting Started with Arduino, 4th ed., Make Community
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