Abstract: The disclosure relates to a method for determining an occupancy situation of containers in an installation, the method comprising: using at least one camera for capturing the occupancy situation of the containers in the installation and obtaining a captured occupancy situation, analyzing the captured occupancy situation and obtaining an analyzed occupancy situation, and controlling the installation based on the analyzed occupancy situation. Furthermore, the disclosure comprises a device comprising at least one camera and a control device with instructions that are stored thereon and that, when executed by a processor, cause the control device to execute the method.

Abstract: The invention relates to a method and to a system for automatically detecting a malfunction of a device in the food industry or the beverage industry, in particular for predictive maintenance. By means of a digital twin of the device, simulation data are produced for a plurality of malfunctions. Subsequently, a machine learning algorithm is trained on the basis of the simulation data and the plurality of malfunctions. The trained machine learning algorithm is then used to detect a malfunction of the device on the basis of operating data of the device. The invention further relates to a method and to a system for determining an optimized production plan for the production of one or more products by means of one or more production lines in the food industry or the beverage industry.