Understanding machine tool performance is important for specifying or comparing machines and for determining capability for production. Machine accuracy has generally been described by the linear positioning accuracy and repeatability of the axes. This specification neglects all other geometric effects such as angular, straightness and squareness errors which can have a significant effect upon the true precision capability of such machines. A more comprehensive way to define a machine’s precision would be to specify the accuracy for the full working volume of a machine tool, i.e. the Volumetric Accuracy (VA) taking into account all geometric errors. Existing methods for describing the volumetric accuracy recognised by the standards organisations are the diagonal and step-diagonal methods. These are designed, in part, to be rapid to reduce machine downtime but compromise accuracy and extensibility if used in isolation. The reduction in accuracy is described in detail in the ISO standard 230 part 6 . This paper describes a definition of VA and a methodology for calculating and reporting the performance of a 3-axis cartesian machine tool that significantly reduces ambiguity compared to other methods and supports a broader range of performance assessments. Error measurement methods are discussed with respect to accuracy and test time. An example model is discussed highlighting the ease with which 3D positioning error can be calculated then methods for efficiently determining the proposed volumetric accuracy. The method is extensible in that the data and model describe the machine volume completely and therefore enables a variety of performance assessments for machine comparison or process capability. Examples are provided showing the difference in accuracy using variable volume assessments and also an example part profile. The method also enables easy calculation of the percentage contribution of each geometric component at the volume positions most affecting the volumetric accuracy enabling targeted correction with maximum performance benefit
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