In their efforts to increase the energy efficiency of their production equipment, companies come up against three implementation hurdles: a lack of transparency regarding energy consumption, the implementation of less effective measures due to the high level of machine complexity and the low motivation of workers to implement the measures in operation. An assistance system that is independent of the equipment can remove these hurdles.



The assistance system developed uses machine learning algorithms to analyze the electrical power requirements of the equipment measured by sensors in real time. Based on this, KPIs are calculated, the value of which determines whether a suitable measure is suggested. Workers operate the assistance system via an HMI. This not only displays the measures to be implemented, but also uses gamification elements to incentivize their implementation. The decisive factor here is the eco-score, which summarizes the current energy efficiency of the WZM plant.

is summarized.