SEFPRO event - GABY Kolloquium 2025
Past event

GABY Kolloquium 2025

The GABY Kolloquium 2025 will take place in Bayreuth, Germany, on July 23, 2025

This year’s edition will focus on “Applications of Artificial Intelligence in Glass Manufacturing” and will be hosted at the University of Bayreuth.

About the Event

Glass Service is thrilled to participate to the GABY Kolloquium 2025, held on July 23, 2025, in Bayreuth, Germany

Hosted at the University of Bayreuth, this year’s edition will focus on the potential applications of Artificial Intelligence in glass production.

Bringing together voices from both research and industry, the event will feature a series of exciting presentations highlighting innovative AI-driven approaches and their relevance to the future of glass manufacturing.

Join us for a day of knowledge sharing, collaboration, and forward-thinking discussions at the heart of glass innovation.

Join Glass Service to the GABY Kolloquium 2025

Abstract: Use of AI in the tub simulation

Batch and cullet melting mark the initial stages of the glass melting process. The stability of this phase—affected by factors such as pull rates, cullet levels, glass color, raw material variations, rheological behavior, and the batch charger—is essential for maintaining optimal glass quality in gas-fired furnaces. Given the potential instability, continuous 24-hour monitoring and corrective control measures are necessary to minimize quality fluctuations.

Moreover, the increasing levels of electric boosting—driven by decarbonization efforts—have the potential to alter glass convection loops, shifting the batch further downstream in the melting process.

In cold-top melting furnaces, batch thickness plays a crucial role in insulating the hot glass melt and reducing heat loss. However, fluctuations in pull rates and cullet levels can significantly affect batch thickness. Until now, no system has been capable of accurately measuring batch thickness or integrating this parameter into an automated, model-based predictive furnace control system.

This paper will present the latest advancements and findings related to both gas-fired and cold-top electric melters, utilizing AI Neural Network Software to identify batch behavior in glass melting furnaces. 

Image
Figure - Abstract GABY Kolloquium
Figure 1. Batch cover over a Hybrid melter using more than 55% electric boosting (LMFV France).

Author

Erik Muijsenberg
Erik H.P.H. Muijsenberg
Business Development Director - Glass Service Group

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