Research Data for Research Activity "Virtual Climatization"

Machining workpieces on machine tools is an inherently energy intensive process. To achieve ever increasing tolerance requirements, thermal disturbances on machine tool and workpiece and resulting thermo-elastic deformations need to be addressed. Instead of cooling whole shopfloor environments and machines, desensitizing the process against temperature changes has the potential to reduce the carbon footprint of machining processes.

To develop models for machine tool error prediction due to temperature, a comprehensive and diverse data set is essential. It includes data sources that capture relevant information about the machine tool's thermal behavior and its corresponding error. Hence, an experiment moving a machine tool with a fixed path is run for several hundred times with the same path for each run. Simultaneously, the actual machine position is measured using a laser tracker and component temperature is tracked.

https://git-ce.rwth-aachen.de/mark.sanders/bzt-data