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Bachelor seminar Predictive Maintenance

(in German: Bachelorseminar Predictive Maintenance - )

Module-ID: FIN-INF-120489
Link: LSF
Responsibility: Prof. Dr. Myra Spiliopoulou, Prof. Dr.-Ing. Benjamin Noack
Lecturer: Prof. Dr. Myra Spiliopoulou, Prof. Dr.-Ing. Benjamin Noack
Classes: Seminar PredMa_BSeminar 
Applicability in curriculum:

Abbreviation

PredMa_BSeminar

Credit Points

5

Semester

every

Term

ab 3.

Duration

1 Semester

Language

english

Level

Bachelor

Intended learning outcomes:
When successfully completing this seminar, the students can:

  • read scientific articles given to them on introductory topics of predictive maintenance
  • discuss these articles and reflect on them
  • compare the methods that appear in these articles and discuss the pros and contra of each method in comparison to other methods
  • summarize article contents on predictive maintenance in a report and present them
  • formulate questions on these articles and answer questions formulated by other seminar participants

Content:
In this seminar, the participants will learn about

  • challenges and methods for data acquisition in industrial processing
  • data analysis tools in predictive maintenance
  • process modeling, fault detection, and state prediction

Workload:
28 h in presence (consultation meetings, presentations) / 96 h self-study for:

  • Reading and Understanding of Provided Papers
  • Writing an essay
  • Presentation and question answering

Type of examination: Teaching method / lecture hours per week (SWS):

Referat und Hausarbeit (Presentation, Discussion, Scientific Article)

Seminar (2 SWS)

Prerequisites according to examination regulations: Recommended prerequisites:

none

  • Lineare Algebra and Calculus
  • Underpinnings of data analytics
  • Underpinnings of signal processing
Media: Literature:

Scientific articles on Predictive Maintenance;
choice of articles depends on topic assignment and is given to each student together with the assignment

Comments: