PREDICTIVE MAINTENANCE FOR A DEVICE IN THE FOOD INDUSTRY BY MEANS OF A DIGITAL TWIN, AND OPTIMIZED PRODUCTION PLANNING

摘要

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.