Project Description

The brewing and beverage industry is characterized by relatively high resource consumption. A significant portion of this consumption is attributable to the cleaning of beer kegs, a process that requires large amounts of water, energy, and cleaning chemicals. Many facilities still operate with rigid cleaning programs and high safety margins to ensure hygienic cleanliness. The actual degree of contamination in the kegs is often not taken into account, leading to avoidable resource consumption and additional costs.
The goal of the smartKEGclean research project is to make the beer keg cleaning process intelligent, condition-based, and significantly more efficient. Together with M+F Keg-technik GmbH & Co. KG, we are developing a modular, AI-supported cleaning system that analyzes circulation data from the kegs prior to cleaning and sensor data throughout the process, assesses the level of contamination, and automatically adjusts process parameters such as rinse times, temperatures, and chemical dosing. The goal is to reduce water, energy, and chemical consumption while maintaining consistent hygiene standards.

The project is funded by the Federal Ministry for Economic Affairs and Energy (BMWE). On behalf of the IPEM Chair, our research associate Fabian Kost is serving as the project’s operational manager.