14414 - Data Analytics and Process Modelling Modulübersicht

Module Number: 14414
Module Title:Data Analytics and Process Modelling
  Datenanalyse und Prozessmodellierung
Department: Faculty 3 - Mechanical Engineering, Electrical and Energy Systems
Responsible Staff Member:
  • Prof. Dr. rer. nat. Röntzsch, Lars
Language of Teaching / Examination:English
Duration:1 semester
Frequency of Offer: Every winter semester
Credits: 6
Learning Outcome:

The students learn to develop, evaluate and validate models, design experiments and analyse data. The focus is placed on practical applications, particularly in energy and process technology. Students are also familiarised with soft sensors and digital twins.

Contents:
  1. Basic Descriptive Statistics and Data Visualisation
  2. Theoretical Foundation for Statistical Analysis
  3. Regression Analysis
  4. Design of Experiments
  5. Input-State-Output Systems
  6. Process Modelling and System Identification
  7. Soft Sensors and Digital Twins
Recommended Prerequisites:

Good knowledge of advanced mathematics as well as physics or a basic engineering subject (e.g. electrical engineering, mechanics or thermodynamics) at the university bachelor's level

Mandatory Prerequisites:None
Forms of Teaching and Proportion:
  • Lecture / 2 Hours per Week per Semester
  • Exercise / 2 Hours per Week per Semester
  • Self organised studies / 120 Hours
Teaching Materials and Literature:

Supplementary lecture materials and exercise assignments are made available via the Moodle learning management system. They are intended solely to support and accompany the lectures and exercises and cannot substitute for regular attendance, active participation, and the preparation of individual notes during class.

Further literature:

  • Shardt, Yuri: Statistics for Chemical and Process Engineers. A Modern Approach. 2nd edition (2022). DOI: 10.1007/978-3-030-83190-5.
  • Shardt, Yuri (2023): Using MATLAB to Solve Statistical Problems. DOI: 10.1007/978-3-031-40299-9.
  • Shardt, Yuri (2024): Using Excel to Solve Statistical Problems. DOI: 10.1007/978-3-031-65449-7.
Module Examination:Final Module Examination (MAP)
Assessment Mode for Module Examination:
  • Written exam (120 min)
Evaluation of Module Examination:Performance Verification – graded
Limited Number of Participants:None
Part of the Study Programme:
  • Master (research-oriented) / Artificial Intelligence / PO 2022 - 1. SÄ 2024
  • Master (research-oriented) / Control of Renewable Energy Systems / PO 2025
  • Master (research-oriented) / Elektrotechnik / PO 2019 - 1. SÄ 2020
  • Master (research-oriented) / Elektrotechnik / PO 2023
  • Master (research-oriented) / Energietechnik und Energiewirtschaft / PO 2021 - 1. SÄ 2024
  • Abschluss im Ausland / Maschinenbau / keine PO
  • Master (research-oriented) / Mathematical Data Science / PO 2025
  • Master (research-oriented) / Mathematics / PO 2025
  • Master (research-oriented) / Power Engineering / PO 2016 - 1. SÄ 2023
  • Master (research-oriented) - Double Degree / Power Engineering / PO 2016
  • Master (research-oriented) / Wirtschaftsingenieurwesen / PO 2019
  • Master (research-oriented) / Wirtschaftsingenieurwesen / PO 2025
  • Master (research-oriented) - Reduced Semester / Wirtschaftsingenieurwesen / PO 2025
  • Master (research-oriented) - Reduced Semester / Wirtschaftsingenieurwesen - dual / PO 2025
  • Master (research-oriented) - Co-Op Programme with Practical Place / Wirtschaftsingenieurwesen - dual / PO 2025
 This module has been approved for the general studies.
Remarks:

Students are expected to bring a laptop to the exercises.

Module Components:
  • Lecture/exercise Data Analytics and Process Modelling
  • Exam Data Analytics and Process Modelling 
Components to be offered in the Current Semester: