Join Expo Room
During the conference you can access the expo room and meet project members for discussions, Q&A and more. Join using the following link:
Time table
- 12:30 - 13:00 (CEST): I4.0 Algae Production Testlab
- 13:00 - 13:30 (CEST): Cyber Physical Brewing Demonstrator for Machine Learning based Recipe Optimization
- 13:30 - 14:00 (CEST): Enabling IDS use cases with retrofit IoT - The IPS Adept-Cell
I4.0 Algae Production Testlab
Algae, an organic product created from salt water and sunlight, offers a huge diversity of products in medicine, energy and agriculture. Current industrial algae production is disjointed and highly inefficient, which may be greatly enhanced with finer control and monitoring techniques provided by the UTS Industry 4.0 Algae Testlab. Our technology integration provides complete process monitoring enabling the application of data science to provide early warning and mitigate adverse process conditions. Process history stored over time will provide a rich dataset to accelerate product development for SMEs.
Further Reading
Funding
Cyber Physical Brewing Demonstrator for Machine Learning based Recipe Optimization
The DaPro project focuses on data-driven process optimization in the beverage industry based on machine learning. The RIF Institute for Research and Transfer has built up a cyber physical brewery demonstrator to present the developing modules on a micro scale. The focus is on the architecture for machine learning using IoT technologies. In a practical examples, the recipe optimization of beer using machine learning methods is presented.
Further Reading
- Parallel Expo Session with focus on a data science toolbox
- Project homepage
- Technologieprogramm Smarte Datenwirtschaft
- DLR project management agency
Enabling IDS use cases with retrofit IoT - The IPS Adept-Cell
This session will take a deep dive into the IDS use case developed at an automated industrial handling cell of the IPS - the Adept-Cell. Get to know different approaches regarding the IoT hard- and software, applications and technologies used to enable IDS, e.g. predictive maintenance and variance analysis, and take the opportunity to ask hands-on questions regarding the live system. Ask about challenges, methods and personal experience with the architecture. Both an open source as well as commercial solutions will be presented and discussed.