Efficient uncertainty estimation of indirectly measured geometric errors of five-axis machine tools via Monte-Carlo validated GUM framework

2021 ◽  
Vol 67 ◽  
pp. 160-171
Author(s):  
Saeid Sepahi-Boroujeni ◽  
J.R.R. Mayer ◽  
Farbod Khameneifar
Keyword(s):  
Monte Carlo ◽  
Machine Tools ◽  
Uncertainty Estimation ◽  
Geometric Errors ◽  
Five Axis

Identification and compensation of 11 position-independent geometric errors on five-axis machine tools with a tilting head

2017 ◽  
Vol 94 (1-4) ◽  
pp. 533-544 ◽  
Author(s):  
Hui Yang ◽  
Xiaodiao Huang ◽  
Shuang Ding ◽  
Chunjian Yu ◽  
Yameng Yang
Keyword(s):  
Machine Tools ◽  
Geometric Errors ◽  
Five Axis

Table-Based Volumetric Error Compensation of Large Five-Axis Machine Tools

2016 ◽  
Vol 139 (2) ◽  
Author(s):  
Jennifer Creamer ◽  
Patrick M. Sammons ◽  
Douglas A. Bristow ◽  
Robert G. Landers ◽  
Philip L. Freeman ◽  
...  
Keyword(s):  
Machine Tool ◽  
Error Compensation ◽  
Machine Tools ◽  
Data Gathering ◽  
Measurement Data ◽  
Geometric Error ◽  
Compensation Method ◽  
Geometric Errors ◽  
Simultaneous Generation ◽  
Five Axis

This paper presents a geometric error compensation method for large five-axis machine tools. Compared to smaller machine tools, the longer axis travels and bigger structures of a large machine tool make them more susceptible to complicated, position-dependent geometric errors. The compensation method presented in this paper uses tool tip measurements recorded throughout the axis space to construct an explicit model of a machine tool's geometric errors from which a corresponding set of compensation tables are constructed. The measurements are taken using a laser tracker, permitting rapid error data gathering at most locations in the axis space. Two position-dependent geometric error models are considered in this paper. The first model utilizes a six degree-of-freedom kinematic error description at each axis. The second model is motivated by the structure of table compensation solutions and describes geometric errors as small perturbations to the axis commands. The parameters of both models are identified from the measurement data using a maximum likelihood estimator. Compensation tables are generated by projecting the error model onto the compensation space created by the compensation tables available in the machine tool controller. The first model provides a more intuitive accounting of simple geometric errors than the second; however, it also increases the complexity of projecting the errors onto compensation tables. Experimental results on a commercial five-axis machine tool are presented and analyzed. Despite significant differences in the machine tool error descriptions, both methods produce similar results, within the repeatability of the machine tool. Reasons for this result are discussed. Analysis of the models and compensation tables reveals significant complicated, and unexpected kinematic behavior in the experimental machine tool. A particular strength of the proposed methodology is the simultaneous generation of a complete set of compensation tables that accurately captures complicated kinematic errors independent of whether they arise from expected and unexpected sources.

Measurement and identification of geometric errors for turntable-tilting head type five-axis machine tools

2018 ◽  
Vol 26 (11) ◽  
pp. 2684-2694 ◽  
Author(s):  
郭世杰 GUO Shi-jie ◽  
姜歌东 JIANG Ge-dong ◽  
梅雪松 MEI Xue-song ◽  
陶 涛 TAO Tao
Keyword(s):  
Machine Tools ◽  
Geometric Errors ◽  
Five Axis ◽  
Head Type

Sensitivity Analysis of Error Motions and Geometric Errors in the Case of Sphere-Shaped Workpiece

2020 ◽  
Author(s):  
Zongze Li ◽  
Ryuta Sato ◽  
Keiichi Shirase
Keyword(s):  
Sensitivity Analysis ◽  
Machine Tools ◽  
End Milling ◽  
Geometric Errors ◽  
Machined Surface ◽  
Error Sources ◽  
Motion Error ◽  
Machining Center ◽  
Machining Errors ◽  
Five Axis

Abstract Motion error of machine tool feed axes influences the machined workpiece accuracy. However, the influences of each error sources are not identical; some errors do not influence the machined surface although some error have significant influences. In addition, five-axis machine tools have more error source than conventional three-axis machine tools, and it is very tough to predict the geometric errors of the machined surface. This study proposes a method to analyze the relationships between the each error sources and the error of the machined surface. In this study, a kind of sphere-shaped workpiece is taken as a sample to explain how the sensitivity analysis makes sense in ball-end milling. The results show that the method can be applied for the axial errors, such as motion reversal errors, to make it clearer to obverse the extent of each errors. In addition, the results also show that the presented sensitivity analysis is useful to investigate that how the geometric errors influence the sphere surface accuracy. It can be proved that the presented method can help the five-axis machining center users to predict the machining errors on the designed surface of each axes error motions.

scholarly journals A geometric error tracing method based on the Monte Carlo theory of the five-axis gantry machining center

2017 ◽  
Vol 9 (7) ◽  
pp. 168781401770764 ◽  
Author(s):  
Jinwei Fan ◽  
Yuhang Tang ◽  
Dongju Chen ◽  
Changjun Wu
Keyword(s):  
Monte Carlo ◽  
Machine Tool ◽  
Test Piece ◽  
Great Influence ◽  
Numerical Control ◽  
Geometric Errors ◽  
Machining Center ◽  
Machining Errors ◽  
Five Axis ◽  
Tracing Method

This article proposes a tracing method to identify key geometric errors for a computer numerical control machine tool by cutting an S-shaped test piece. Adjacent part relationships and machine tool errors transform relationships are described by topology of the machining center. Global sensitivity analysis method based on quasi-Monte Carlo was used to analyze machining errors. Using this method, key geometric errors with significant influence on machining errors were obtained. Compensation of the key errors was used to experimentally improve machining errors for the S-shaped test piece. This method fundamentally determines the inherent connection and influence between geometric errors and machining errors. Key geometric errors that have great influence on machining errors can be determined quickly with this method. Thus, the proposed tracing method could provide effective guidance for the design and use of machine tools.

Observation of Thermal Influence on Error Motions of Rotary Axes on a Five-Axis Machine Tool by Static R-Test

2012 ◽  
Vol 6 (2) ◽  
pp. 196-204 ◽  
Author(s):  
Cefu Hong ◽  
◽  
Soichi Ibaraki
Keyword(s):  
Machine Tools ◽  
Single Point ◽  
Geometric Errors ◽  
Thermal Tests ◽  
Thermally Induced ◽  
Rotary Axis ◽  
Spindle Rotation ◽  
Thermal Changes ◽  
Thermal Influence ◽  
Five Axis

Thermal distortions are regarded as one of the major error factors in machine tools. ISO 230-3 and ISO 10791-10 describe tests to evaluate the influence of thermal distortions caused by linear motion and spindle rotation on the Tool Center Position (TCP). However, for five-axis machine tools, no thermal test is described for a rotary axis. Therefore, in this paper, a method for observing thermally induced geometric errors of a rotary axis with a static R-test is proposed. Unlike conventional thermal tests in ISO 230-3 and ISO 10791-10, where the thermal influence on the positioning error at a single point is tested, the present test measures the thermal influence on the error motions of a rotary axis. The R-test measurement clarifies how the error motions of a rotary table change with the rotation of a swiveling axis and how they are influenced by thermal changes. The thermal influence on the error motions of a rotary axis is quantitatively parameterized by geometric errors that vary with time.

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