Resource efficiency and energy consumption more and more become high-profile quality attributes of modern machine tools. The energy consumption of machine tools, plants and facilities must be significantly reduced related to the value added in order to stay competitive, but not least in liability towards our environment.
This article presents a model based simulation and prediction of the expected energy consumption of machine tools using a comprehensive simulation environment, which serves as a basis for energetic optimizations. The simulation system will be exemplarily presented by reference to turning and milling operations. This system is extended by adaptive control and optimization of the energy states of the machine tool through application of artificial neuronal network controller networks and additional expert knowledge data-base.
Seifermann, Stefan: Methode zur angepassten Erhöhung des Automatisierungsgrades hybrider, schlanker Fertigungszellen.