The measures taken to improve the thermal behaviour of machine tools are based on thermal models. The models are applied to support the design process and to correct the machine tool operation in a control-based way. Especially the models for correction purposes include uncertain parameters that cannot be estimated with sufficient accuracy. Thus these parameters have to be adjusted by means of measurements. During the adjustment process, a broad diversity of machine behaviour and model characteristics has to be taken in to account. Therefore, substantial time, effort and expert knowledge are required. To identify the key expenses, a generalized and systematic analysis of the adjustment process was carried out. First, the typical design of the models, the parameters of the sub models and the current adjustment procedure were investigated. Based on the results of the analysis, support requirements were identified. Afterwards first methods and software tools for efficient support were developed. This strategy is demonstrated using the example of a hexapod strut model.

Machine tools are important parts of high-complex industrial manufacturing. Thus, the end product quality strictly depends on the accuracy of these machines, but they are prone to deformation caused by their own heat. The deformation needs to be compensated in order to assure accurate production. So an adequate model of the high-dimensional thermal deformation process must be created and parameters of this model must be evaluated. Unfortunately, such parameters are often unknown and cannot be calculated a priori. Parameter identification during real experiments is not an option for these models because of its high engineering and machine time effort. The installation of additional sensors to measure these parameters directly is uneconomical. Instead, an effective calibration of thermal models can be reached by combining real and virtual measurements on a machine tool during its real operation, without additional sensors installation. In this paper, a new approach for thermal model calibration is presented. The expected results are very promising and can be recommended as an effective solution for this class of problems.

During machining occurring losses conduct into the machine tool and lead to deformations that im-pair the machining accuracy. Thus, high effort is invested into the compensation of thermo-elastic er-rors. One new approach is to use the information extractable from part programs in combination with CNC controller systems to forecast occurring losses in terms of a look ahead function. The method al-lows the evaluation of part programs with respect to its thermal influence on the machine tool. There-fore, the method is applied on selected part programs, resulting loss distributions are discussed in terms of their thermal impact, and potential follow-up strategies are stated.

No abstract