Adjustment of uncertain model parameters to improve the prediction of the thermal behavior of machine tools

Computer models, which simulate the thermo-elastic behavior of machine tools, are used for optimizing machine designs and more recently for controller-integrated online corrections. Sufficiently accurate corrections of errors caused by the thermal machine behavior require quick and precise identification of uncertain and irregularly distributed parameters based on measurements. The paper presents a systematic approach to conduct parameter identification during machine commissioning. In particular, the acquisition of required data for parameter adjustment and model optimization is addressed. Finally, the procedure is demonstrated on the example of a machine tool's feed axis.