Mechanistic Approach for the Evaluation of Machine Tools Quasi-Static Capability
One of the greatest challenges in the manufacturing industry is to increase the understanding of the error sources and their effect on machine tool capability. This challenge is raised by the complexity of machining systems and the high requirements on accuracy. In this paper, a mechanistic evaluation approach is developed to handle the complexity and to describe the underlying mechanisms of the machine tools capability under quasi-static condition. The capability in this case is affected by the geometric errors of the multi-axis system and the quasi-static deflections due to process loads. In the assessment of these sources a mechanistic model is introduced. The model is composed of two parts, combining direct and indirect measurements. The direct measurement modelling method was applied to predict the effects of individual axis geometric errors on the functional point of machine tools. First, the direct measurement is employed to allow measuring each single machine tool axis motion error individually. The computational in the direct measurement model calculates the deviations from a given toolpath in the work space. Then, indirect measurements are used to determine the static stiffness and its variation in the workspace of machine tools. A case study demonstrates the applicability of the proposed approach, where laser interferometry was implemented as direct and loaded double ball bar as indirect measurement. The methodology was investigated on a three and a five axis machine tool and the results demonstrate the potential of the approach.
KeywordsAccuracy Static stiffness Machine tool
The authors wish to thank Dr Mikael Hendlind for research contribution on kinematic modelling and M.Sc. Jonny Gustafson for his contribution in the laser interferometer measurements. Centre for design and management of manufacturing systems (DMMS) at the Department of Production Engineering at KTH Royal Institute of Technology is acknowledged for financial support.
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