Estimation and compensation of geometric errors for rotary axes are among methods to improve machining accuracy of five-axis machine tools. Studies have been conducted on various methodologies for estimating geometric errors for rotary axes, which are essential for improving machining accuracies of five-axis CNC machine tools. This paper presents a method for estimating geometric errors of a rotating/tilting table using a cross-shaped calibration artifact with a touch trigger probe. The proposed method includes rotary axes error estimation equations for angles of each rotary and tilt axis based on locations of probing points. Computer simulations were performed based on a MATLAB/Simulink and ADAMS cosimulation system using the probing cycle process to verify the proposed method. Computer simulation results confirmed the usefulness of the proposed method in terms of volumetric errors.
ISO 10791-6 specifies test conditions, BK1 and BK2, including circularly interpolated motions by simultaneous control of two linear axes and a rotary/tilting axis, for five-axis machine tools with a tilting-rotary table. Eccentricities of measured motions are used to identify position-independent geometric errors of the rotary/tilting axis. However, time-consuming alignments of measurement devices are required to execute the circular motions due to large geometric errors of the tilting axis. In this paper, a simple method is proposed to align an initial position of a tool-center-point (TCP) relative to the actual tilting axis of five-axis machine tools for application of ISO 10791-6. A ball at the tool nose with an extension fixture, supplied commercially by a double ball-bar manufacturer, is used to measure positional deviations of a ball on workpiece table at 90° command angle of a tilting axis. An alignment error of a TCP is identified simply by using a geometric relationship of the TCP and measured deviations. Then, identified alignment errors are used to calculate initial position of a TCP for fine measurements of position-independent geometric errors specified in ISO 10791-6. The proposed method is applied to a five-axis machine tool and verified experimentally.
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A Study on the Estimation of Geometric Errors for Rotary Axes of a Five-Axis Machine Tool Using a Cross-Shaped Calibration Artifact Jeongmo Kang, Dayoung Kim, Sungchul Jee Journal of the Korean Society for Precision Engineering.2023; 40(1): 87. CrossRef
A TCP Calibration of a 6-Axis Manipulator and Geometric Errors Identification of a Tilting-Rotary Table Kwang-Il Lee, Do-Hun Kim, Hoon-Hee Lee, Seung-Han Yang Journal of the Korean Society for Precision Engineering.2022; 39(4): 253. CrossRef
In CNC machining, NC data created by CAM software is usually linearly interpolated. This linearly interpolated tool path, however, may degrade the dynamic motion performance of the machine tool and the geometric accuracy in comparison with the reference CAD data. Tool path smoothing can be an effective way to address these problems. In this paper, a five-axis tool path smoothing method is proposed based on dual cubic B-spline curves. The proposed smoothing method includes two steps. First, the tool orientation is adjusted to reduce drastic changes in tool orientation movement. Then, dual B-spline curves are generated for smooth interpolation of tool position and orientation, wherein their control points are created by using modified internal division points between the top and bottom points of the tool defined by given tool position and orientation vectors. The B-spline curves pass through the junctions of straight line segments comprising the top and bottom points, respectively. Smooth tool position and orientation vectors are finally obtained by simultaneous interpolation of the B-spline curves. The proposed method is implemented in a PC-based five-axis control system and experimentally demonstrated to show improvements in the dynamic motion performance and the geometric accuracy compared with the conventional linear interpolation.
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Research on three-section type tool path planning algorithm for tooth hot pressing model cutting Lijun Zhang, Shaowei Fang, Jiayi Xu, Ning Yang, Weijian Guo, Hang Wang, Changliang Li Computers & Industrial Engineering.2022; 163: 107817. CrossRef