Date: | 10 February 2027, 09:00 – 17:00 (CET) | Price: | Free (for eligible participants) | |
Format: | AI:AT Webinar, ONLINE (Zoom) | Target audience: | Industry, public admin, academia | |
Language: | English | Organizer: | AI:AT |
Struggle with data for your industrial AI applications scattered throughout different data silos? Learn how to efficiently integrate data with technologies such as Asset Administration Shell (AAS) and OPC UA and build scalable AI solutions, such as predictive maintenance or machine chatbots.
The basis for most modern AI applications is a proper amount of high-quality data. However, especially in the manufacturing context, this data is traditionally scattered across a vast amount of distributed, unconnected, heterogeneous data silos. In this training, you will discover how to efficiently integrate this data into your AI models using digital twins. More precisely, you will work with technologies such as Asset Administration Shell and OPC UA to build a common data layer as virtual representation of your physical assets.
In the practical exercises, you will work with:
- Use Case 1: A machine chatbot that allows users to interact with machine documentation. You will scale the application of this chatbot by enabling it to automatically discover the correct documentation associated with each machine.
- Use Case 2: A predictive maintenance service that predicts failures of different devices based on live data. You will scale this predictive maintenance application by connecting it to live data from many different, heterogeneous machines.
Learning Outcomes:
After attending this full-day hands-on workshop, you will be able to
- understand challenges associated with scaling AI solutions to whole manufacturing sites
- efficiently integrate data from different data silos into your AI applications
- start implementing the machine chatbot and predictive maintenance examples in yousr own organization
Agenda
09:00 | Motivation and Introduction Digital Twins, Introduction of used technologies: Asset Administration Shell (AAS Designer), OPC UA (Python SDK provided by Traeger) and working environment for the hands-on part |
10:30 | Break |
11:00 | Introduction of use case 1: Machine Chatbot |
12:00 | Break |
13:00 | Hands-On Labs for use case 1 |
14:00 | Introduction of use case 2: Predictive Maintenance |
15:00 | Break |
15:30 | Hands-On Labs for use case 2 |
16:30 | Wrap-Up |
17:00 | End |
Target audience
Developers, innovation engineers and data scientists who want to scale AI applications in a manufacturing setting.
This webinar is open and free of charge for all participants from academia, industry, and public administration from EU and/or EuroHPC JU member countries.
Entry level & prerequisites
Participants are expected to be familiar with the Python programming language. The rest will be covered as part of the course. So you do NOT need any prior experience with AI development, Asset Administration Shell, OPC UA, or other digital twin technologies.
Speaker
Daniel Lehner (AI Factory Austria AI:AT)
Dr. Daniel Lehner works as expert in AI knowledge transfer at AI Factory Austria AI:AT. He also works as a consultant and trainer at TwinTech, helping companies to efficiently exploit the potential of digitalization through the use of artificial intelligence and digital twins. In addition to his work with various companies, he also draws on his many years of experience in researching digital twins and artificial intelligence at Johannes Kepler University in Linz.
Location
This course is offered as LIVE ONLINE WEBINAR via Zoom.
If there is sufficient interest, we may offer an additional in-person attendance option in Vienna.
Registration
Registration is required, the link to the registration form can be found on the top of this page in the menu on the left. Please register with your official institutional email address to prove your affiliation.
You will get the Zoom link in the automatic confirmation by email (subject starting with "[Indico] Registration"), please check your Spam/Junk folders). We will also send 1–2 reminders before the webinar.
Please do not hesitate to contact us at training@ai-at.eu if you have any questions.
Organizers
This webinar is organized by AI Factory Austria AI:AT.
Acknowledgements
AI Factory Austria AI:AT has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101253078. The JU receives support from the Horizon Europe Programm of the European Union and Austria (BMIMI / FFG).