Five-Axis Machine Tool Volumetric and Geometric Error Reduction by Indirect Geometric Calibration and Lookup Tables

Abstract

Abstract Modern CNC machine tools provide lookup tables to enhance the machine tool’s precision but the generation of table entries can be a demanding task. In this paper, the coefficients of the 25 cubic polynomial functions used to generate the LUTs entries for a five-axis machine tool are obtained by solving a linear system incorporating a Vandermonde expansion of the nominal control jacobian. The necessary volumetric errors within the working volume are predicted from the machine’s geometric errors estimated by the indirect error identification method based on the on-machine touch probing measurement of a reconfigurable uncalibrated master ball artifact (RUMBA). The proposed scheme is applied to a small Mitsubishi M730 CNC machine. Two different error models are used for modeling the erroneous machine tool, one estimating mainly inter-axis errors and the other including numerous intra-axis errors. The table-based compensation is validated through additional on-machine measurements. Experimental tests demonstrate a significant reduction in volumetric errors and in the effective machine error parameters. The LUTs reduce most of the dominant machine error parameters. It is concluded that although being effective in correcting some geometric errors, the generated LUTs cannot compensate for some axis misalignments such as EB(OX)A and EB(OX)Z. The root-mean-square of the translational volumetric errors is improved from 87.3, 75.4, and 71.5 µm down to 24.8, 18.8, and 22.1 µm in the X-, Y-, and Z-directions, respectively.