Zustandsmodellbasierte, steuerungsnahe Energieverbrauchsoptimierung von Werkzeugmaschinen

In recent years, resource efficiency and the environment protection has increased in importance for the industry. The pressure on companies based on the energy efficiency rises due to national and international policies, rising electricity prices, market competition but also directly by expectations of the society. To continue to operate efficiently, industrial companies pursue the goal to reduce their energy costs. During the operation of machine tools, especially during non-productive times, electrical energy is wasted, because, although power saving states are state of the art, these are not used efficiently. Therefore, in this work, the aim is pursued to bridge interruptions in production energy-optimally. A configurable, energy-model-based solution for the optimization of energy consumption during production interruptions is developed. First, a method is analyzed and developed that allows the use of the operating state model for calculating consumption and detection of the current operating state during the operation of machine tools. In order to define and parameterize this model with significantly reduce effort, a method for partially-automated state modeling is developed. It also allows the integration of expert knowledge. The configured operating state model can then be used in the optimization of energy consumption. To complete the work, a method for model-based energy consumption optimization is developed. The optimization method uses a graph-based search algorithms for the determination of the energy-optimal operation state sequences during non-productive times. The applicability of the developed methods is validated on the demonstration machine Exeron Digma HSC600 within a control framework