Three-axis Machine Tool Research Articles

An unconstrained and non-redundant identification method of geometric errors and compensation of machine tools by X-AX Laserbar

Efficient and accurate measurement and identification of geometric errors are crucial for improving the precision of CNC machine tools. The X-AX Laserbar, as a novel tool for indirect measurement, has not been extensively studied for the identification of geometric errors in machine tools. In this paper, the geometric error model for a three-axis machine tool is established to illustrate the multilateration measurement principle of the laserbar, and a non-redundant and unconstrained identification method is proposed to identify these geometric errors. This method avoids the use of redundant parameters and additional constraints by employing pose error twists to describe the geometric errors. These pose error twists are identified in a transitional coordinate system, and then the geometric errors will be identified in the machine coordinate system by deriving the relationship between the pose errors and geometric errors. The proposed method is validated with the VMC-850E three-axis machine tool. The geometric error measurement using a laserbar is completed in about 40 min, showing great efficiency. The experimental results indicate that the proposed method is capable of accurately identifying the 17 geometric errors required for error compensation. The identified geometric errors are then applied to the machine tool’s accuracy improvement through error compensation. The results show that the actual geometric errors are controlled to a low level. The proposed method can efficiently measure the geometric errors of three-axis machine tools and contribute significantly to improving their geometric accuracy.

Geometric error identification for three-axis machine tools based on on-machine measurement of a calibrated artefact

Geometric error identification for three-axis machine tools based on on-machine measurement of a calibrated artefact

Machine tool thermal error measurement and prediction via wireless microscope

A novel method is proposed to measure the thermal errors of a three-axis machine tool by taking images of unique custom-designed fiducials attached to a worktable using a wireless microscope mounted to the spindle. Multiple fiducials are applied for the measurement of different thermal errors at various worktable locations. In addition, a least-squares thermal error model within the work volume is proposed in which the model parameters are determined from various fiducial measurements, and the use of various fiducials for the thermal error model is analyzed. The results show the method can measure thermal errors within four times the positioning resolution of the machine tool, with most of the errors being smaller in magnitude than twice the positioning resolution. Further, the results show the thermal error model depends on the location of the fiducials used to construct the model. The unique numbering system for the fiducial patterns also allows for the measurement of large planar thermal errors, which is advantageous for machine tools that undergo significant thermal drift.

Analysis of models of measurement and correction of volumetric error of three-axis metal-cutting machine tool

The paper considers the improvement of the quality of products of machined production in connection with the quality of machining of various products and, accordingly, with the accuracy of the equipment used. It is noted that geometrical errors, which account for up to 40 % of the total error of a multi-axis, especially three-axis, metal-cutting machine tool, have the greatest influence on the accuracy of product machining. In order to improve the quality of product machining, it is necessary to correct its parameters according to the measurement information received during machine tool operation, for which the methods of mathematical modelling are used. Models of the volumetric error of a three-coordinate metal-cutting machine tool are developed, taking into account the summands of the first (linear) and second (quadratic) order of smallness. A comparative analysis of the developed models is carried out. The results of experiments on measurement of volumetric errors of the STAN S500 complex and their correction on the basis of the nonlinear theoretical model are given. It is found that in the range of angular errors 0–2.5′ the consideration of quadratic terms of the model in addition to linear ones does not lead to a significant reduction of the volumetric error. It is shown that when processing measurement information of multi-axis metal-cutting machines it is sufficient to limit the consideration of components of the volumetric error not higher than the first order of smallness. The research results are useful for the acceptance and periodic control of the volumetric error of metal-cutting machines, as well as for the programme reduction of the volumetric error.

A unified geometric error model applicable to all configurations of three-axis machine tools

A unified geometric error model applicable to all configurations of three-axis machine tools

Geometric Error Identification of Gantry-Type CNC Machine Tool Based on Multi-Station Synchronization Laser Tracers

Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial measurement. We propose a geometric error identification method based on multi-station synchronization laser tracers to enable the rapid and high-precision measurement of geometric errors for gantry-type computer numerical control (CNC) machine tools. This method also improves on the existing measurement efficiency issues in the single-base station measurement method and multi-base station time-sharing measurement method. We consider a three-axis gantry-type CNC machine tool, and the geometric error mathematical model is derived and established based on the combination of screw theory and a topological analysis of the machine kinematic chain. The four-station laser tracers position and measurement points are realized based on the multi-point positioning principle. A self-calibration algorithm is proposed for the coordinate calibration process of a laser tracer using the Levenberg–Marquardt nonlinear least squares method, and the geometric error is solved using Taylor’s first-order linearization iteration. The experimental results show that the geometric error calculated based on this modeling method is comparable to the results from the Etalon laser tracer. For a volume of 800 mm × 1000 mm × 350 mm, the maximum differences of the linear, angular, and spatial position errors were 2.0 μm, 2.7 μrad, and 12.0 μm, respectively, which verifies the accuracy of the proposed algorithm. This research proposes a modeling method for the precise measurement of errors in machine tools, and the applied nature of this study also makes it relevant both to researchers and those in the industrial sector.

Machining accuracy reliability optimization of three-axis CNC machine tools using doubly-weighted vector projection response surface method

Machining accuracy reliability optimization of three-axis CNC machine tools using doubly-weighted vector projection response surface method

An optimization method of acceleration and deceleration time of feed system based on load inertia

The acceleration and deceleration time is usually a constant value in the process of computer numerical control (CNC) machine tool processing, which cannot adapt to the change of external load and greatly affects processing efficiency. This paper proposes an optimization method for the acceleration and deceleration time of the feed system based on load inertia, which provides the basis for the adaptive adjustment of the acceleration and deceleration time of the feed system. Firstly, by establishing the dynamic model of the servo system, the acceleration and deceleration method is used to identify the external load inertia under different working conditions. The prediction model of the current variance based on load inertia and acceleration and deceleration time parameters is established by using the response surface method, and then the multi-objective particle swarm optimization algorithm is used to build the acceleration and deceleration time optimization model based on the load inertia. At the same time, the inertia identification part is compared with the model reference adaptive system method and the empirical formula estimation method based on current and velocity, the simulation and cutting experiment results show that the inertia identification method based on acceleration and deceleration optimizes the other method. Finally, the machining experiments are carried out on three-axis and five-axis machine tools with the same machine tool type, and by adding different counterweight blocks to change the external load. The test proves that the acceleration and deceleration adaptive adjustment strategy based on load inertia can effectively improve processing efficiency and reduce the fluctuation of the processing load.

Fast detection of geometric errors for three-axis machine tools with combined double-ball bars based on spatial circle detection

The geometric accuracy of the CNC machine tools determines the quality of the sculptured mechanical parts. Measuring and compensating the geometric errors of machine tools can effectively improve the machining accuracy. However, traditional measurement methods using a double-ball bar (DBB) can only detect the error along the rod length direction and thus require multiple measurements in three orthogonal planes of the machine tool. This work proposes a fast error detection method for the three-axis machine tools using combined double-ball bars (C-DBBs) based on the spatially circular detection (SCD) path. The test path of this method requires the simultaneous linkage of three linear axes of the machine tools and thus could identify 21 geometric errors of three-axis machine tool. Firstly, the measuring principle of the SCD method is introduced, and the mathematical model for detecting 21 geometric errors of the machine tool based on the SCD method is established. Then, the detection experiment based on the SCD method is carried out, and it is shown that 21 geometric errors of the three-axis machine tool are obtained. Finally, the verification experiment using a traditional DBB is conducted to validate the effectiveness of the proposed SCD method. The radial errors in three orthogonal planes measured by traditional DBB exhibit a good agreement with those predicted using 21 geometric errors obtained by the SCD method. Compared with the traditional DBB method, the proposed SCD method could detect 21 geometric errors of three-axis machine tools in a single measurement. This work provides an effective and efficient methodology for detecting all geometric errors of the three-axis machine tool.

Workshop-suited identification of thermo-elastic errors of three-axis machine tools using on-machine measurement

This paper presents a method for workshop-suited identification of thermo-elastic errors of three-axis machine tools (MTs) using on-machine measurement. For this purpose, a new design for a three dimensional artifact is presented. Using the artifact, it is possible to identify all relevant geometric errors of three-axis portal milling machines in table design. The method presented is therefore suitable for the one-time identification of geometric errors caused by manufacturing inaccuracies, assembly-related deviations and wear, and for the identification of thermally induced geometry errors over a long-term period. Since the artifact is scalable in size, it can be easily adapted to different machine sizes. The presented method thus represents a universal and inexpensive possibility to measure geometric and especially thermo-elastic errors.Within the scope of this paper, an error model was established for the investigated machine type and an artifact design was derived on the basis of this model. The suitability of the artifact for identifying thermo-elastic errors has also been investigated experimentally. For this purpose, an artifact made of thermo-invariant material (Invar) was produced. This artifact was measured cyclically on a MT with three linear axes, which was exposed to a controlled thermal load in a temperature chamber. The positions of the geometric features were collected using a 3D touch trigger probe. In addition, the ambient temperatures were recorded. The results of this measurement are discussed in this paper.

On-machine measurement of thermal influence of the long-span crossbeam of gantry machine tools using a 3D laser profiler

For gantry machine tools, the large-span beam is an important structural component, and its deformation is significantly affected by temperature. It is still a crucial problem to identify the thermal error of the motion axis continuously and in real-time. This paper proposed an on-machine measurement (OMM) method to evaluate the thermal influence on long-span crossbeam of the gantry machine tools, using a high-precision 3D laser profiler and a set of artifacts. Firstly, kinematic model to compute the deformation of the crossbeam is established considering the position calibration of the laser profiler. As the Y-axis relies on the crossbeam, thermal errors of the Y-axis are identified to evaluate the thermal influence on long-span crossbeam. Secondly, algorithms for the position calibration and the point cloud registration are proposed to solve the calibration matrix and the relative transformation matrix of the 3D laser profiler in the kinematic model. The thermal error of the Y-axis can then be identified by utilizing the developed kinematic model. Finally, a continuous warm-up experiment was carried out on a three-axis gantry machine tool, and the six thermal errors of the Y-axes during the warm-up process were calculated. The results verify the effectiveness of the proposed method. In addition, uncertainty analysis is conducted to evaluate the effect of the 3D laser profiler calibration error on thermal error identification based on the experimental results. It is proved that the proposed thermal error identification method is insensitive to position calibration errors.

Influence of lateral dynamic error on the trajectory error in machine tools

In machine tools, the trajectory error of the tool center point (TCP) is caused due to the dynamic positioning error of feed drive systems according to the relationship in spatial structure and motion. The dynamic positioning error of the feed drive system includes axial dynamic error and lateral dynamic error. To analyze the influence of the lateral dynamic error on the trajectory error of the TCP of multi-axis machine tools, in this study, circular and butterfly trajectories were designed as the set trajectories of a machine tool with three linear axes. In addition, the tracking error models were constructed both considering the lateral dynamic error and without considering the lateral dynamic error, and the difference between the two models was quantified. The Sobol method was then used to analyze the sensitivity of the lateral dynamic error of the feed drive system to the tracking error of the TCP. Finally, experiments were performed on a three-axis machine tool. The results show the maximum lateral dynamic error in the direction perpendicular to the motion direction is 0.026 mm. The lateral dynamic error detrimentally affects the tracking error and contour error of the TCP in multi-axis machine tools.

Condition monitoring of three-axis ultra-precision milling machine tool for anomaly detection

Accurately and continuously monitoring ultra-precision machining (UPM) process is the foundation forsubsequent diagnosis and optimization, then facilitating energy-saving, efficient production, and high-quality machining. However, comprehensive monitoring of UPM process has hardly been investigated systematically in previous studies. To cover the gap, this study examined the linkages among these parameters monitored in UPM process using a five-layers network for the first time. Subsequently, we proposed an advanced monitoring platform that integrates G-code command, installation sensors, and controller interface. This proposed platform incorporated with anomalies detection algorithm was finallyemployed and validated onathree-axis ultra-preciisiion miilllliing machiine tooll. Results showed that this proposed platform could successfully achieve anomaly identification using power consumption and X/Y/Z components force signals.

Development of a Novel Dynamic Modeling Approach for a Three-Axis Machine Tool in Mechatronic Integration

This paper proposes a novel, fast, and automatic modeling method to build a virtual model with minimum degrees of freedom (DOFs) without the need for FE models or human judgment. The proposed program uses the iterative closest point (ICP) algorithm to analyze the mode shape vector of structural dynamic characteristics to define the position and DOFs of the joints between structural components. After the multi-body dynamics model was developed in software, it was converted into an SSM to connect the servo loop model. Then, the mechatronic integration analysis was performed to verify the dynamic characteristics of the tool center point (TCP) and the workbench in the experiment and simulation. The model created by the proposed identification process has a small DOF and can accurately simulate the dynamic characteristics of a machine. This model can be used for dynamic testing and control strategy development in mechatronic integration.

Process Optimization Based on Analysis of Dynamic and Static Performance Requirements of Ion Beam Figuring Machine Tools for Sub-Nanometer Figuring

Extreme ultraviolet lithography objective lenses require surface figure accuracy of approximately sub-nanometer root mean square (RMS). As the key equipment for sub-nanometer accuracy figuring, the dynamic and static performance of ion beam figuring (IBF) machine tools are critical. However, the related research is not sufficient and comprehensive. To this end, a general model of dynamic and static performance requirements on three-axis IBF machine tools was established. The requirements on dynamic and static performance under different figuring process for different surface shape were comprehensively analyzed. Analysis results revealed that the three-axis IBF machine tools require typical motion accuracy better than 100 μm and certain dynamic performance for achieving sub-nanometer accuracy. According to the theoretical and simulation results, a process optimization based on analysis of dynamic and static performance requirements of IBF machine tools for sub-nanometer figuring is proposed. To verify the proposed method, a Φ90 mm mirror with 2.594 nm RMS was figured to 0.251 nm RMS by optimizing the processing parameters to ensure that the IBF machine tool with measured performance (positioning error of 52.74 μm, 53.04 μm, 37.71 μm, and maximum acceleration of 1.0 m/s2, 1.3 m/s2, and 1.5 m/s2 for axes x, y, and z, respectively) meets the performance requirements. The proposed method can promote the application of three-axis IBF machine tools in sub-nanometer accuracy figuring.

Analysis of Surface Profile Error of Ultra-Precision Diamond Planing Based on Power Spectral Density

Vibration in ultra-precision machining is an inherent physical phenomenon and a key factor affecting surface generation. However, the influence of the vibration characteristics of aerostatic guideways on the machining morphology has not been fully studied. In this article, a diamond micro-planing experiment was carried out on an oxygen-free copper workpiece using a homemade three-axis machine tool, and a white-light interferometer was used to measure the surface topography of the planing surface. The power spectral density of the surface topography was analyzed, and the spatial wavelength components of the surface topography were extracted. Then, the vibration characteristics of the aerostatic guideway were measured in both the space domain and the time domain. A comprehensive analysis of the main components of the workpiece surface error morphology and the vibration characteristics of the guideway shows that the time-domain vibration of the aerostatic guideway is the main factor causing the surface topography error of the workpiece.

Improvement in the efficiency of the five-axis machining of aerospace blisks.

Blisks are not easily machined because of their complex curved surfaces and the high-precision requirements of surface machining. Lightweight alloy materials with superior mechanical properties, such as titanium alloy and stainless steel, are popular material choices for manufacturing turbine blisks. However, these materials are difficult to cut and require advanced machine tools and processing technologies. Because aerospace-grade parts are complex and require precise dimensions and high surface quality, machining these parts by using three-axis machine tools is difficult. Using multi-axis machine tools for the machining of complex parts can cause the achievement of precise dimensions, high quality, and the required surface roughness. In the multi-axis machining of aerospace blisks, tool path planning is considered the most difficult task. In this study, we examined the implementation of five-axis machining technology for the manufacturing of an aerospace blisk. Processing modules from computer-aided manufacturing software (NX10) are used for five-axis tool path generating, and 5-axis machining numerical control code is generated through post-processing calculations. Solid cutting simulation software (VERICUT) is used to verify whether tools exhibited overcut or interference. A sensory tool holder (SPIKE) is used to analyze cutting force during the rough machining of a blisk. The sensory tool holder is also adopted to evaluate the spindle runout and tool holding status. In order to obtain a consistent cutting allowance and surface accuracy, the online measurement system is used to generate a measurement path for semi-finish and finish machining. The real cut is performed with SUS304 and demonstrates the practical application. Through improvements in process planning, the machining time was shortened by 16.5%.

Partition-based 3 + 2-axis tool path generation for freeform surface machining using a non-spherical tool

Abstract When machining a complex freeform part, using a non-spherical tool could significantly improve the machining efficiency, as one can adaptively adjust the tool posture to maximize its contact area with the part surface. However, since adjusting the tool posture requires changing the tool orientation, a five-axis machine tool is needed, which is extremely expensive as compared to a conventional three-axis machine tool. Moreover, for a complex freeform surface with high curvature variation, to match its curvature change, the tool axis has to drastically change accordingly, thus inducing high velocity and acceleration on the machine tool’s rotary axes. To address these issues, in this paper we propose a partition-based 3 + 2-axis strategy for machining a general complex freeform surface with a non-spherical tool. As only a finite small number of distinct tool orientations are needed for 3 + 2-axis machining, an indexed three-axis machine tool suffices, thus relieving the need of an expensive five-axis machine tool. In addition, the much-increased rigidity of the three linear axes of the machine tool will greatly improve the kinematics and dynamics of the machine tool and thus enhance the machining accuracy. Experiments in both computer simulation and physical machining are carried out, whose results confirm that, when compared to using a conventional spherical cutter, by using a non-spherical cutter and adaptively adjusting the contacting tool posture and the feed direction, significant improvement in machining efficiency could be achieved, e.g., more than 50% achieved in our experiments.

Energy consumption investigation of a three-axis machine tool and ball-end milling process

Energy consumption investigation of a three-axis machine tool and ball-end milling process

Design of a real-time three-axis controller for contour error reduction based on model predictive control

The machining accuracy is mainly indicated by the contour error especially in high-precision processing. Previously, scholars have proposed many controllers to reduce contour errors in real-time machining, such as the cross coupling controller and sliding mode controller. In this paper, we propose a controller based on model predictive control (MPC), and the contour error caused during path tracking can be effectively reduced by this controller. First of all, for two-dimensional (2D) and three-dimensional (3D) tool paths, their contour errors are deduced based on coordinate system transform. Second, the MPC-based controller is designed with the state-space discrete model of a machine tool. The contour error is regarded as a constraint during receding optimization. These are reasons why the presented control scheme is adapted with both bi-axis and three-axis machine tools. Furthermore, in order to improve the efficiency of receding optimization, the contour error of a 3D curve is simplified. Subsequently, the optimization problem is transformed into the standard form of quadratic programming. Finally, a 2D tool path and a 3D tool path are machined to test the proposed controller. Simulations and experiments show satisfactory results which indicate effectiveness of the proposed method.