Automation Manufacturing Software

STIWA Educational Content

Training material for higher technical colleges, universities of applied sciences and universities

Knowledge, data and experience
out of practice


In addition to exciting projects and internships, we provide free digital educational equipment to students, and educational institutions such as higher technical colleges, universities of applied sciences, and universities with a focus on mechatronics, automation or similar disciplines in order to help develop expertise in innovative automation solutions. We want to support the training process with realistic use cases and data sets at an early stage.

Simulation/ Virtualization

(virtual start-up of a machine)


The "Virtual Start-Up" exercise and training environment provides a realistic experience of the start-up process without the need for a physical automation machine. With the help of provided simulation components, the real behaviour of the system can be mirrored using virtual or real controls (PLC). Scenarios can be created, tested and compared easily, quickly and flexibly by different users.

A separate user licence is required to access this training environment.

Interested educational institutions are welcome to contact us.

DataScience AI Datasets

In the digital era, the STIWA Group recognizes the importance of data and thus offers high-quality datasets from real-world applications for free.

The FLADI dataset, emerging from the research project INTERACTIVE, aims at leveraging AI to enhance production quality, featuring 4281 samples of product variants for use in machine learning within automation. You can find more information about the project here.

Within its Preanalytics division, STIWA focuses on refining a broad spectrum of laboratory processes, including but not limited to sample preparation and sorting. These efforts represent just a segment of the comprehensive automation and optimization initiatives, supported by three specific datasets. These datasets are aimed not only at enhancing workplace efficiency and laboratory throughput but also at providing insights into the behavior of sample submitters, thus covering a subsection of the laboratory processes.

Access to the data sets can be requested here.

Elisabeth Eder
STIWA Educational Content

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