Modern control systems, production-related software systems and digitisation solutions (Industry 4.0) have been implemented in the Automation Technology Laboratory and are gradually being further developed in research work. The complete spectrum of the automation pyramid from the sensor-actuator level to control technology (e.g. PLC) and the MES level (Manufacturing Execution Systems) is mapped.


The industrial use of these systems is taught to students by means of practical application scenarios. In the practical course, they learn to classify important terms of automation technology and production-relevant software systems. The aim of the internship is to build up a deeper understanding of the language, goals, potentials, working methods and technical realizations of automation and software engineering.

In bachelor and master theses the development and implementation of new MES and digitization solutions is carried out together with industrial partners. The solutions are tested in the laboratory and the results are then transferred to the partners.

CampusAnsbach
Room51.1.1
Study programmes N.N.
Contact personsProf. Dr.-Ing. Jürgen Göhringer
Dierk Seifert

 

Laboratory equipment

MES software / PPS software

  •     MES system Siemens SIMATIC IT - Scheduling Preactor (10 workstations)
  •     MES systems Hydra of the company MPDV (8 workstations)
  •     functions: Detailed planning, order control, BDE/MDE, tool management, product tracking, KPIs/OEE

Virtual engineering

Software for system modelling and programming (Festo Ciros)

Pneumatics / Electropneumatics

Festo-pneumatics and electropneumatics, circuit design, simulation, Festo-PC training software

Control engineering

PLC programming system (Siemens SIMATIC TIA Portal), PLC controlled drilling station (Festo), SIMATIC S7 controls (real/virtual) and HMI Festo training software PLC Wago PLC with OPC UA

Robotics

Kuka robot KR6 R900 development environment for virtual robot programming (Kuka simulation, 15 workstations)

Cloud Software

Cloud solution with reporting and machine learning concepts for the monitoring of SPS-controlled plants (proprietary development)