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General information
Complex Automation Systems
Complex Automation Systems
ME121
KomplSysAuto-01-MA-M
Prof. Dr. Wree, Christoph (christoph.wree@haw-kiel.de)
Sommersemester 2027
1 Semester
In der Regel im Sommersemester
Englisch
Curricular relevance (according to examination regulations)
Study Subject Study Specialization Study Focus Module type Semester
M.Eng. - BT - Battery Technologies Pflichtmodul
Qualification outcome
Areas of Competence: Knowledge and Understanding; Use, application and generation of knowledge; Communication and cooperation; Scientific self-understanding / professionalism.
Students are able to apply concepts and methods for the structured design of complex automation systems (AS).
Students are able to apply concepts and methods for the structured design of complex automation systems (AS).
Students can analyze, explain, design and implement complex automation systems.
Students can discuss, solve and coherently explain complex technical problems in a team.
Students can
- define goals for learning and work processes,
- recognize, describe and explain requirements.
Content information
Lecture content:
Important standards for the design of automation systems (AS)
Procedure models for the design of AS
Possibilities of system modeling and simulation for IEC 61131-based AS
Agent-oriented software development for IEC 61131-based AS
Coordination of parallel processes with Petri nets
Motion planning for production cells
Mechanisms for identifying workpieces (vision, RFID)
Machine learning for AS
Cloud-based services for AS
Condition monitoring
Virtual reality and augmented reality for AS
AS for battery production (production machines for lithium-ion battery cells: laser cutting, welding, ablation machines; composite foil formation machines; filling and soaking process machines; degassing and sealing machines; module manufacturing machines; testing and inline process monitoring machines)

Laboratory content:
Programming of roll-to-roll foil transport system (TwinCAT)
PLC-based programming of a delta robot (TwinCAT)
Virtual commissioning of a delta robot in 3D (TwinCAT, Unity)
Programming of a production cell with transport system (Beckhoff XTS, TwinCAT)
Machine vision (TwinCAT Vision)
Object classification with machine learning (TwinCAT ML)
Vogel-Heuser, B., Bauernhansl, T., & ten Hompel, M. (eds.). Handbuch Industrie 4.0 [Handbook Industry 4.0]. Springer Vieweg.
Hippenmeyer, H., & Moosmann, T. Automatische Identifikation für Industrie 4.0 [Automatic Identification for Industry 4.0]. Springer Vieweg.
Bindel, T., & Hofmann, D. Projektierung von Automatisierungsanlagen [Design and Engineering of Automation Systems]. Springer Vieweg.
Göhner, P. (ed.). Agentensysteme in der Automatisierungstechnik [Multi-Agent Systems in Automation Technology]. Springer.
Lunze, J. Automatisierungstechnik [Automation Technology]. De Gruyter Oldenbourg
Courses
Workload
4 SWS
5,0 Credits
48 Hours
102 Hours
Module Examination
Method of Examination Duration Weighting wird angerechnet gem. § 11 Absatz 2 PVO Graded Remark
Laborprüfung 0 % Successful completion of all 6 laboratory experiments is required to pass the module.
Technischer Test 90 Minutes 100 %
Miscellaneous
PLC programming knowledge is required
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