Digitalization

14:00 - 15:30: From Kilns to Code – Building Digital Readiness in the Ceramics Industry
Florian Bliesch, Adesso

15:30 - 16:00: Simulation in Powder Metallurgy and Ceramics – Current State and Potentials of AI Applications
Yuanbin Deng

16:00 - 16:30: Data-driven and Future-proof: A Roadmap for AI in the Ceramics Industry
M. Eng. Tobias Steffen, Research Associate & AI Innovation Manager, Forschungsgemeinschaft Feuerfest e. V. (FGF)

The ceramics industry is facing unprecedented challenges. Demographic changes are shrinking the skilled workforce, and global competition is intensifying. To remain competitive, digitalization - especially the integration of artificial intelligence (AI) - is no longer optional, but rather, essential. This talk outlines a strategic roadmap for embedding AI sustainably in the sector. The roadmap is structured around three interconnected pillars:
Companies, associations, and a vibrant community each play pivotal roles in driving this transformation. Together, they create an ecosystem that addresses current challenges and unlocks new opportunities for innovation and efficiency. Through collaboration, best practice sharing, and trust building, the industry can position itself at the forefront of technological progress, ensuring long-term resilience in a dynamic global market.

16:30 - 17:00: ATN-Ceram develops AI model for wear prediction and process optimisation in grinding processes
Alexander Do, ATN-Ceram GmbH

Since 2021, ATN-Ceram GmbH has been working with the Fraunhofer Institute for Information Technology (FIT) to develop and optimise an AI model for predicting the wear behaviour of ceramic grinding beads in agitator bead mills. In close cooperation with mill operators, process data analyses were carried out. A data strategy has been developed to train the AI model with high-quality data.

During model development, mobile measuring kids for recording energy inputs and physical process parameters, such as temperature and vibration intensity, were also tested and optimised. These mobile measuring kids enable automated data collection, independent of specific mill types and process control systems. The recorded process data is transferred to a secure data room, enabling the grinding process to be monitored and optimised.

With the help of the AI model, significant deviations in process data are detected at an early stage. This enables countermeasures to be initiated in good time before operational disruptions can occur.

This concept, developed by ATN and consisting of three modules – AI model, secure data room, and mobile measurement kid – can be customised to suit specific customer requirements and is therefore suitable for process optimisation and the optimisation of maintenance intervals, to support predictive maintenance.