Machine Tool Volumetric Error Research Articles

Modeling method of CNC tooling volumetric error under consideration of Abb\xe9 error

The Abbé error is a key factor for high-precision CNC machine tools. Unluckily, it is not taken into account in traditional machine tool volumetric error models. In this respect, based on the traditional machine tool volumetric error models, a new machine tool volumetric error model containing Abbé error is performed by analyzing the mechanism of Abbé error formation tool volumetric and based on 21-item geometric error measurement data, Abbé arm, and angle functional relationship. Moreover, integrated qualitative and quantitative simulation method for evaluation of machine tool space precision are correspondingly presented. Finally, an example was utilized to further verify the value of our model by means of analysis and comparison of the tooling precision prior to and after performance of compensation, and its validity and feasibility were proved. This study provides an important modeling method for high-precision machine tools and has very important theoretical significance and practical value.

Interpolation and Extrapolation of Optimally Fitted Kinematic Error Model for Five-Axis Machine Tools

Abstract Machine tool geometric errors are frequently corrected by populating compensation tables that contain position-dependent offsets to each commanded axis position. While each offset can be determined by directly measuring the individual geometric error at that location, it is often more efficient to compute the compensation using a volumetric error model derived from measurements across the entire axis space. However, interpolation and extrapolation of measurements, once explicit in direct measurement methods, become implicit and obfuscated in the curve-fitting process of volumetric error methods. The drive to maximize model accuracy while minimizing measurement sets can lead to significant model errors in workspace regions at or beyond the range of the metrology equipment. In this paper, a method of constructing machine tool volumetric error models is presented in which the characteristics of the interpolation and extrapolation errors are constrained. Using a typical five-axis machine tool compensation methodology, a constraint bounding the tool tip modeled error slope is added to the error model identification process. By including this constraint over the entire space, the geometric errors over the interpolation space are still well identified. Also, the model performance over the extrapolation space is consistent with the behavior of the geometric error model over the interpolation space. The methodology is applied to an industrial five-axis machine tool. In the experimental implementation, for measurements outside of the measured region, an unconstrained model increases the mean residual by 40% while the constrained model reduces the mean residual by 40%.

Model of geometric deviations in milling with three error sources

The milling process is widely used industrially and the quality of the obtained milled products should be controlled because it affects their performance in exercise. This work correlates the quality of the machined surfaces with the adopted locating system, the shape deviations of the workpiece datum and the machine tool. An analytical model was set up and implemented through Matlab® to simulate the quality effects of a milling process. It was applied to two face milling processes characterized by two different locator configurations. It was proved that machine tool volumetric error influences the flatness of the milled surface, while the locator configuration and the datum form deviation affect the orientation of the milled surface, as should be actually.

An integrated methodology of volumetric error modeling, validation, and compensation for horizontal machining centers

It is crucial to perform volumetric error forward analyses of horizontal machining centers, including modeling, validation, and compensation, so that workpiece machining accuracies can be improved. Aiming at solving three major problems so far emerged in the machine tool volumetric error forward analyses, an integrated methodology is proposed in this paper. Firstly, in order to formulate a kinematic model without uncertainties and inconsistencies, a principle to determine the correct product relations of nominal motions to motion errors is systematically developed. Secondly, a novel validation approach based on the concept of volumetric vector Euclidean norm is demonstrated in this paper, assuring that the constructed volumetric error model can be quantitatively assessed without engaging any compensation processes. Thirdly, an optimal compensation technology is also presented to achieve the objective that the compensation residual errors, which are likely generated from the existing inverse superposition compensation strategies, can be diminished or even eliminated. A commercial horizontal machining center is selected to apply and verify the proposed integrated methodology.

An improved machine tool volumetric error compensation method based on linear and squareness error correction method

Error compensation is one of effective and economical means to improve the machining accuracy of machine tools. The measurement accuracy of kinematic errors has great impact on the accuracy of machine tool error modeling. Some measurement errors are inevitably generated due to the distortion of the slide table and the limit of local measuring stroke. To solve these problems, an improved machine tool volumetric error compensation method is proposed in this paper, based on linear and squareness error correction method. The linear errors, including position errors and straightness errors, are corrected by considering the distance effect between optical mirror groups and the surface of worktable. The squareness errors are corrected through modifying local squareness errors measured with double ball bar to global squareness errors, with the aid of straightness errors measured with multi-laser calibrator. Then volumetric errors are obtained based on multi-body system theory, and volumetric diagonal errors are measured with laser interferometer. It is illustrated that the bidirectional systematic deviation of positioning of four volumetric diagonals reduced about 81.3%, 35.2%, 29.2%, and 4.5% respectively by using this improved machine tool volumetric error compensation method, and it is of obvious advantages in contrast with traditional compensation method with direct measurement data. The improved error compensation method proposed in this paper has universal applicability and has great significance on machine tool accuracy improvement.

A kinematic approach for error modelling in drilling

PurposeThe purpose of this paper is to model how geometric errors of a machined surface (or manufacturing errors) are related to locators’ error, workpiece form error and machine tool volumetric error. A kinematic model is presented that puts into relationship the locator error, the workpiece form deviations and the machine tool volumetric error.Design/methodology/approachThe paper presents a general and systematic approach for geometric error modelling in drilling because of the geometric errors of locators positioning, of workpiece datum surface and of machine tool. The model can be implemented in four steps: (1) calculation of the deviation in the workpiece reference frame because of deviations of locator positions; (2) evaluation of the deviation in the workpiece reference frame owing to form deviations in the datum surfaces of the workpiece; (3) formulation of the volumetric error of the machine tool; and (4) combination of those three models.FindingsThe advantage of this approach lies in that it enables the source errors affecting the drilling accuracy to be explicitly separated, thereby providing designers and/or field engineers with an informative guideline for accuracy improvement through suitable measures, i.e. component tolerancing in design, machining and so on. Two typical drilling operations are taken as examples to illustrate the generality and effectiveness of this approach.Research limitations/implicationsSome source errors, such as the dynamic behaviour of the machine tool, are not taken into consideration, which will be modelled in practical applications.Practical implicationsThe proposed kinematic model may be set by means of experimental tests, concerning the industrial specific application, to identify the values of the model parameters, such as standard deviation of the machine tool axes positioning and rotational errors. Then, it may be easily used to foresee the location deviation of a single or a pattern of holes.Originality/valueThe approaches present in the literature aim to model only one or at most two sources of machining error, such as fixturing, machine tool or workpiece datum. This paper goes beyond the state of the art because it considers the locator errors together with the form deviation on the datum surface into contact with the locators and, then, the volumetric error of the machine tool.

Five-axis machine tool fault monitoring using volumetric errors fractal analysis

Detecting machine tool condition deterioration affecting its accuracy is a constant challenge for industrial machine maintenance. Machine tool volumetric errors (VEs) exhibit complex variations due, for example, to normal thermal variations, wear or faults and defective components. A monitoring technique based on the fractal analysis of VEs, estimated with the scale and master ball artefact method, is studied. Different fractal parameters from the VE vectors are compared with magnitude based quantities for the detection of abnormal machine states. Results using both actual data with real and pseudofaults and synthetic data from simulated faults using ISO230-1 error parameters are presented.

Quantitative assessment of machine tools condition through fractal analysis of volumetric error vector similarity measures

The volumetric error state of machine tools is related to the quality of the machined parts and the machine tool condition. Volumetric error vectors (VEs) of machine tools can be estimated using methods such as R-test, laser trackers and the scale and master ball artefact (SAMBA) method. During one measurement, a series of volumetric error vectors can be acquired. Herein, volumetric error vector features extracted using vector similarity measures (VSMs), such as the Module, the Cosine, the Area and the Volume measures, are subsequently processed by fractal analysis for quantitative assessment of the machine tool volumetric error state. Although VEs have recently been processed directly using fractals, this paper documents the first attempt to process VEs, extracted by VSMs, using fractal analysis. The proposed method is validated using VEs measured from the machine tool in its normal state and faulty state with real and pseudo-faults. In addition, simulated faults caused by the change of ISO230-1 error parameters are also applied. The results reveal that the performance of the proposed method in machine tools state representation is related to VSMs. Fractal analysis of VEs features extracted by the Area and Volume measures performs better than fractal analysis of Modu and Cosine measure in VEs condition evaluation. However, for the same fault, the change revealed by fractal analysis of VE coordinates are clearer than the change revealed by the fractal analysis of VE features extracted by VSMs.

Machine Tool Volumetric Error Features Extraction and Classification Using Principal Component Analysis and K-Means

Volumetric errors (VE) are related to the machine tool accuracy state. Extracting features from the complex VE data provides with a means to characterize this data. VE feature classification can reveal the machine tool accuracy states. This paper presents a study on how to use principal component analysis (PCA) to extract the features of VE and how to use the K-means method for machine tool accuracy state classification. The proposed data processing methods have been tested with the VE data acquired from a five-axis machine tool with different states of malfunction. The results indicate that the PCA and K-means are capable of extracting the VE feature information and classifying the fault states including the C axis encoder fault, uncalibrated C axis encoder fault, and pallet location fault from the machine tool normal states. This research provides a new way for VE features extraction and classification.

Sculptured surface-oriented machining error synthesis modeling for five-axis machine tool accuracy design optimization

Customer-oriented design is very important for machine tool manufacturers to win competition in the market. Mechanical parts with complicated sculptured surface are widely utilized in mechanical systems such as automobiles, aircrafts and wind turbines, and they are often machined by five-axis machine tools with high precision requirements. However, traditional machine tool design has not accounted for the varied machining errors in producing complex sculptured surface, which leads to inferior performance. To address this challenge, a novel machining error synthesis model is proposed in this paper for accuracy optimization in designing general five-axis machine tools used for making various sculptured surfaces. The new synthesis model is constructed by integrating a generic machine tool volumetric error model and two new surface machining error production models, and it bridges between the surface machining profile error and the machine tool accuracy. The synthesis model is then applied as a constraint in machine tool accuracy design optimization. A cost-tolerance function is formulated to construct the objective function, and a heuristic algorithm is developed to implement the optimization. These modeling and optimization methods are validated by one case study.

Optimized volumetric error compensation for five-axis machine tools considering relevance and compensability

Compensation of a machine tool's volumetric errors can be achieved by adjustment of the axes original commands. Depending on the machine topology, the volumetric errors and the axes commands, a full compensation may not be achieved due to kinematic singularities. Furthermore, corrections of volumetric errors which do not affect part quality, by virtue of the machining process and machined feature, may lead to excessive corrections causing surface degradation. The paper addresses these problems through the introduction of two notions, error relevance and error compensability, leading to an optimized compensation in which minimal but effective command modifications are made. Mathematical definitions are presented together with application examples for different processes. A specially designed test part containing four common features, i.e. hole, curved slot on a spherical surface, cone frustum and flat surface is machined, using up to five-axis simultaneous machining, for the experimental validation. Three parts are machined using uncompensated G-code, compensated G-code and optimized compensated G-code, respectively, which are then measured on a coordinate measuring machine. Simulation results show a reduction (up to 75%) in the 1-norm of the linear and angular compensations while the relevant errors are effectively corrected by the proposed optimized strategy.

Five axis machine tool volumetric error prediction through an indirect estimation of intra- and inter-axis error parameters by probing facets on a scale enriched uncalibrated indigenous artefact

The volumetric accuracy of five-axis machine tools is affected by intra-axis geometric errors (error motions) and inter-axis geometric errors (axes relative position and orientation errors). Self-probing of uncalibrated facets on the existing machine tool table is proposed to provide the necessary data for the self-calibration of the machine error parameters and of the artefact geometry using an indirect approach. A set of 86 non-confounded coefficients are selected from the ordinary cubic polynomials used to model both the intra- and inter-axis errors. A scale bar is added to provide the isotropic scale factor. The estimated model is then used to predict the actual tool to workpiece position. Experimental trials are conducted on a five-axis horizontal machining centre using its original unmodified machine table as an artefact. For validation purposes only, the estimated artefact geometry is compared to accurate coordinate measuring machine (CMM) measurements. A study of the volumetric error predictive capability of the model for selected subsets of estimated error coefficients is also conducted.

Volumetric Verification of Multiaxis Machine Tool Using Laser Tracker

This paper aims to present a method of volumetric verification in machine tools with linear and rotary axes using a laser tracker. Beyond a method for a particular machine, it presents a methodology that can be used in any machine type. Along this paper, the schema and kinematic model of a machine with three axes of movement, two linear and one rotational axes, including the measurement system and the nominal rotation matrix of the rotational axis are presented. Using this, the machine tool volumetric error is obtained and nonlinear optimization techniques are employed to improve the accuracy of the machine tool. The verification provides a mathematical, not physical, compensation, in less time than other methods of verification by means of the indirect measurement of geometric errors of the machine from the linear and rotary axes. This paper presents an extensive study about the appropriateness and drawbacks of the regression function employed depending on the types of movement of the axes of any machine. In the same way, strengths and weaknesses of measurement methods and optimization techniques depending on the space available to place the measurement system are presented. These studies provide the most appropriate strategies to verify each machine tool taking into consideration its configuration and its available work space.

Robust Design of Fixture Configuration

The paper deals with robust design of fixture configuration. It aims to investigate how fixture element deviations and machine tool volumetric errors affect machining operations quality. The locator position configuration is then designed to minimize the deviation of machined features with respect to the applied geometric tolerances.The proposed approach represents a design step that goes further the deterministic positioning of the part based on the screw theory, and may be used to look for simple and general rules easily applicable in an industrial context.The methodology is illustrated and validated using simulation and simple industrial case studies.

C002 Estimation of Machine Tool Volumetric Error based on the Multi-lateration Principle using Machine Tool Rotary Axes : Two-dimensional case

C002 Estimation of Machine Tool Volumetric Error based on the Multi-lateration Principle using Machine Tool Rotary Axes : Two-dimensional case

Proposition for a Volumetric Error Model Considering Backlash in Machine Tools

This paper proposes a new scheme for evaluating the machine tool volumetric error model including the backlash error. The effects of backlash errors are assessed by experiments, conducted on a three-axis vertical-type machining centre. The assessment was taken for 18 error components out of the 21 geometric errors of a machine tool. It was shown that the backlash error of a machine tool is one of the systematic errors. Some important characteristics of the backlash error were identified; that is, the backlash error is a function of position, it decreases as the feedrate increases, and its size and shape vary according to the machine structure.