Basics of mechanical manufacturing with the SkillsMagazine

The course content covers the hands-on fabrication of components for the “Stacking Magazine” module using various machines, tools and processes.

The focus is on drilling and forming using semi-finished parts from the learning kit. In addition, the basics of milling and turning are taught, with practice parts being produced during the turning process.

Another key focus is additive manufacturing: Components are designed using CAD and then manufactured using additive processes.

These parts are then assembled with other components to form a functional module. The course concludes with the mechanical and electrical assembly of all manufactured parts and standard components, as well as the full commissioning of the stacking magazine, ensuring that students receive comprehensive training in the manufacturing processes, assembly and commissioning of mechatronic systems.

Basics of Automation Technology with SkillsConveyor

SkillsConveyor provides you with practical training in the basics of commissioning technical systems. You assemble and wire mechanical and electrical components, test signals and troubleshoot malfunctions.

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You learn how relay controllers work, build and test control circuits using contactors, relays, pushbuttons and limit switches, and practice troubleshooting.

You will deepen your knowledge of AC motors by wiring and operating motor controllers with protective devices and switchgear.

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You will also program simple control tasks using Siemens LOGO!, understand Boolean logic and demonstrate your skills in both theory and practice.

Finally, you will learn PLC programming, create programs for a conveyor belt and integrate sensors to test your skills.

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Machine Learning in Automation Technology with SkillsConveyor

Together with SkillsConveyor and the IIoT Machine Learning Kit, you’ll learn the basics of machine learning and apply them in practical scenarios.

Using an educational production system, you'll learn the basics of AI and ML in image processing, as well as the use of convolutional neural networks (deep learning).

You will use supervised learning methods and learn image classification for computer vision applications.

Finally, you will learn how systems in the IoT can be retrofitted and modernized.