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Applied Computer Science and Industry 4.0

Module name (EN):
Name of module in study programme. It should be precise and clear.
Applied Computer Science and Industry 4.0
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Industrial Engineering / Production Management, Bachelor, ASPO 01.10.2021
Module code: DBWI-310
SAP-Submodule-No.:
The exam administration creates a SAP-Submodule-No for every exam type in every module. The SAP-Submodule-No is equal for the same module in different study programs.
P740-0028, P740-0029
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
-
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
7
Academic Year: 3
Mandatory course: yes
Language of instruction:
German
Assessment:
2 graded exams:
 
- Exam 1 (Applied Computer Science: Duration 90 min., 100 pts.)
  This exam is written in the 5th semester (Block 5A) according to the exam schedule.
 
- Exam 2 (Industry 4.0: Duration 90 min., 100 pts.)
  This exam is written in the 6th semester (Block 6A) according to the exam schedule.
 
The reason for dividing the examination into two parts, one of which is written in Block 5A (5th semester) and the other in Block 6A (6th semester), is to distribute the workload evenly.
 
The module grade is calculated as follows:                 
43% of the points in Exam 1 “Applied Computer Science”        
57% of the points in Exam 2 “Industry 4.0”


[updated 08.05.2023]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

DBWI-310 (P740-0028, P740-0029) Industrial Engineering / Production Management, Bachelor, ASPO 01.10.2022 , study year 2, mandatory course
DBWI-310 (P740-0028, P740-0029) Industrial Engineering / Production Management, Bachelor, ASPO 01.10.2021 , study year 3, mandatory course
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
The total student study time for this course is 210 hours.
Recommended prerequisites (modules):
None.
Recommended as prerequisite for:
Module coordinator:
Prof. Dr.-Ing. Jürgen Kohlrusch
Lecturer: Prof. Dr.-Ing. Jürgen Kohlrusch

[updated 11.06.2021]
Learning outcomes:
Applied Computer Science:
Basic concepts of computer science will be taught and applied to simple problems. Students therefore receive an introduction to programming in this module. After successfully completing this module, they will understand the term "algorithm" and be familiar, for example, with algorithms for searching and sorting data. They will be familiar with different data structures. They will be able to implement algorithms for simple problems. Students will be aware of the increasing importance of computer science for engineering disciplines.
 
Industry 4.0:
In the future, the influence of digitalization will cause profound changes in the world of work in industry and commerce. In the "Industry 4.0" sub-module, students will become familiar with the factors that influence future processes in industry and what challenges they may face. Students will be able to identify and describe the differences between business processes that are already automated today and a fully networked "smart factory" as envisaged by Industry 4.0 in the future. They will be familiar with so-called cyber-physical systems and understand how structured, semi-structured and unstructured data can be processed in large quantities ("Big Data"). They are familiar with the basics of artificial intelligence and can recognize its practical potential in future business areas.
 
The "Applied Computer Science and Industry 4.0" module will increase and strengthen students’ professional competence.


[updated 08.05.2023]
Module content:
Content: Applied Computer Science:
• Algorithm: Definition and meaning
• Data structures
• Introduction to programming
• Application to, for example, search procedures, as well as to simple and higher sorting procedures
 
Content: Industry 4.0:
• Introduction to Industry 4.0
  o Smart home, smart car, smart factory - Applications
  o Humans in the digitalized environment - Augmented, virtual and mixed reality
  o Production data acquisition (PDA) and machine data acquisition (MDC)
  o Legal challenges
 
• Cyber-physical systems
  o RFID, GPS
  o Network technology, server clusters
  o Data security, backup and data protection
  o Robotics and human/machine collaboration
 
• Big Data and Artificial Intelligence (AI)
  o Structured, semi-structured and unstructured data
  o Volume, Variety, Velocity, the "V´s" of Big Data
  o Introduction to Hadoop, HDFS and Mapreduce
  o How artificial neural networks and fuzzy logic work
  o Swarm intelligence
  o Big Data and AI in practice

[updated 08.05.2023]
Recommended or required reading:
• R. Sedgewick, K. Wayne (2014): Algorithmen und Datenstrukturen (4. Auflage); Pearson, Hallbergmoos
• J. Bewersdorff (2018): Objektorientierte Programmierung mit JavaScript; Springer Vieweg, Wiesbaden
• A. Bauer, H. Günzel (Hrsg.): Data-Warehouse-System – Architektur, Entwicklung, Anwendung; dpunkt Verlag; Heidelberg
• P. Chamoni, P. Gluchowski (Hrsg.): Analytische Informationssysteme – Business Intelligence-Technologien und -Anwendungen; Springer Verlag; Berlin/Heidelberg
• J. Freiknecht: Big Data in der Praxis – Lösungen mit Hadoop, HBase und Hive. Daten speichern, aufbereiten, visualisieren; Carl Hanser; München
• Th. Schulz: Industrie 4.0: Potenziale erkennen und umsetzen, Vogel Business Media
• R. M. Wagner: Industrie 4.0 für die Praxis, Springer Gabler

[updated 08.05.2023]
 
[Fri Dec 27 18:13:52 CET 2024, CKEY=aaiui4a, BKEY=aswwing2, CID=DBWI-310, LANGUAGE=en, DATE=27.12.2024]