Accuracy Of CNC Machine Tools Research Articles

Pre-compensation of Friction for CNC Machine Tools through Constructing a Nonlinear Model Predictive Scheme

Nonlinear friction is a dominant factor affecting the control accuracy of CNC machine tools. This paper proposes a friction pre-compensation method for CNC machine tools through constructing a nonlinear model predictive scheme. The nonlinear friction-induced tracking error is firstly modeled and then utilized to establish the nonlinear model predictive scheme, which is subsequently used to optimize the compensation signal by treating the friction-induced tracking error as the optimization objective. During the optimization procedure, the derivative of compensation signal is constrained to avoid vibration of machine tools. In contrast to other existing approaches, the proposed method only needs the parameters of Stribeck friction model and an additional tuning parameter, while finely identifying the parameters related to the pre-sliding phenomenon is not required. As a result, it greatly facilitates the practical applicability. Both air cutting and real cutting experiments conducted on an in-house developed open-architecture CNC machine tool prove that the proposed method can reduce the tracking errors by more than 56%, and reduce the contour errors by more than 50%.

Research on optimal multivariate thermal error modeling based on finite-element analysis

To improve the nonlinear fitting ability of multiple linear regression model in thermal error prediction of machine tools, an optimized thermal error modeling method based on test and simulation is proposed in this paper. Firstly, the finite-element analysis is used to complete the thermal-structure coupling analysis of the CNC machine tool. Based on the simulation results of temperature and deformation field of the machine tool, temperature-sensitive points (TSPs) are selected with fuzzy cluster analysis and correlation analysis. According to the simulation results, TSPs of the machine tool are fitted by quadratic polynomial from temperature to deformation. Finally, taking the deformation value of TSPs as the intermediate variable, the multiple linear regression model is established, and the optimized quadratic multiple regression thermal error model is obtained. The results show that the prediction curve of the optimized thermal error model based on on test and simulation is closer to the test curve, and the fitting index is better than that obtained from the traditional model. This method can effectively improve the nonlinear fitting ability of the thermal error model of CNC machine tools. Based on the thermal error model established in this paper, the compensation value of thermal error can be obtained by inputting the real-time measured temperature data of TSPs, which can effectively improve the machining accuracy of CNC machine tools.

Influence of material selection on fixture accuracy of CNC machine tools

Fixtures are commonly used tools for CNC machine tools to clamp workpieces. Due to the high requirements for its own position and motion accuracy during the operation of a CNC machine tool, in addition to its own motion accuracy, the positioning accuracy of the fixture is also an important factor affecting the overall accuracy. In the experiment, two fixture materials of 45# and 65Mn were selected, and the two fixtures with wedge-shaped positioning surface and circular positioning surface were compared. The data showed that: 1. The accuracy of fixtures with symmetrical structures of the same material is better than fixtures with asymmetrical structures; 2. The repeated positioning accuracy of 65Mn material fixture is better than that of 45 # material fixture. Therefore, the higher the positioning accuracy of the fixture made of high hardness and good rigidity materials.

Research Status and Development of Precision Analysis of CNC Machine Tools

Accuracy is a key quality characteristic of CNC machine tools, reflecting the pros and cons of machine tool performance. Accuracy is affected by performance failures of CNC machine tools, such as vibration, friction, and heat transfer. Therefore, it is difficult to accurately model and comprehensively analyse the accuracy of the machine tool by studying the influence of certain factors on the accuracy of the CNC machine tool in isolation, which makes it difficult to find out the problems in the design or manufacturing process. The article analyses the current status and research significance of domestic CNC machine tool accuracy, expounds the domestic and foreign research status of CNC machine tool accuracy modelling method and CNC machine tool accuracy comprehensive analysis, summarizes the existing problems and development trends of CNC machine tool accuracy research, and compares it based on the meta-action. The theoretical systematic modelling of the accuracy of CNC machine tools and the key issues of comprehensive evaluation of the accuracy of CNC machine tools combined with the meta-action chain provide insights and provide analytical methods for the design and manufacture of CNC machine tools.

Influence of thermo-mechanical deformations on the positioning accuracy of CNC machine tools

This research aims at improving the machining accuracy of the CNC machine tools by decreasing the errors caused by the thermo-mechanical deformations and increasing the positioning accuracy of the mobile element. This work analyses and researches the effects of the thermo-mechanical deformation on the positioning accuracy of the feed kinematical linkages of the CNC machine tools that are using the indirect measuring system of the position. The analysis is focused on feed kinematical linkages having rapid speed rates, of 40 m/min, that use a preloaded bearing system of the ball screw, supported at both ends. Constructive methods are also presented for decreasing the temperature at the heat generating sources by thermo-stating both the ball screw and its bearings. Through thermostats the temperature in the ball screw and its bearings is decreased, that leads to decreasing its influence on the positioning accuracy. The thermo-stating of the ball screw makes possible to keep a constant preloading force of the two ball screw nuts and, as far as the bearings are concerned, the coolant agent is the same as the lubrication agent that leads to a smooth running and, by default, to expanding the life of the feed kinematical linkage.

Development of real-time prediction module for precision and error of CNC system finishing

High speed and high precision are the important trends in the development of CNC machine tools. In order to improve the machining accuracy of CNC machine tools, the errors of CNC machine tools must be reduced as much as possible. Generally speaking, the errors of CNC machine tools include spatial errors, thermal errors, cutting force errors, tool wear errors, etc., in which spatial errors account for a large part of CNC machine tool errors, so reasonable control of reducing spatial errors is of great significance to improve the accuracy of CNC machine tools. Methods commonly used to reduce spatial errors include error prevention methods and error compensation methods. Error prevention is a method to eliminate and reduce error sources through design, manufacturing, assembly, etc. Although this method can reduce the original error, it is limited by improving manufacturing and assembly accuracy to reduce errors, and it is economically expensive. The error compensation method is to artificially create a new error to offset the current original error to achieve the purpose of improving machining accuracy. This method is easy to implement and has low cost. Therefore, the error compensation method is the most economical and effective method to improve the accuracy of the machine tool.

Bayesian neural network–based thermal error modeling of feed drive system of CNC machine tool

It is well known that thermal error has a significant impact on the accuracy of CNC machine tools. In order to decrease the thermally induced positioning error of machine tools, a novel thermal error modeling approach based on Bayesian neural network is proposed in this paper. The relationship between the temperature rise and positioning error of the feed drive system is investigated by simultaneously measuring the thermal characteristics that include the temperature field and positioning error of the CNC machine tool. Fuzzy c-means (FCM) clustering and correlation analysis are used to select temperature-sensitive points, and the Dunn index is introduced to determine the optimal number of clustering groups, which can inhibit the multicollinearity problem among temperature measuring points effectively. The least-square linear fitting is applied to explore the feature of the positioning error data. The results show that compared with the BP neural network and multiple linear regression model, the Bayesian neural network not only has higher prediction accuracy but also can guarantee excellent prediction performance under different working conditions. The prediction results obtained under different operating conditions indicate that the maximum thermal error can be reduced from around 18.2 to 5.14 μm by using the Bayesian neural network, which represents a 71% reduction in the thermally induced error of the feed drive system of machine tool.

Overview of Machine Tool Error Detection Technology

With the rapid development of modern mechanical manufacturing technology, precision and ultra-precision processing technology has become the main trend of the development of modern mechanical manufacturing industry. As a basic tool in mechanical manufacturing, the accuracy of CNC machine tools is an important index affecting the accuracy of workpiece processing. Therefore, the research on improving the accuracy of CNC machine tools has received great attention. In all kinds of high-speed and precision machine tools, the problem of the decline of machining accuracy caused by machine tool errors has become increasingly prominent. How to identify and eliminate machine tool errors quickly and efficiently has become an increasingly urgent task. In this paper, the research status of machine tool error detection technology at home and abroad is analyzed, in order to provide a reference for the development of machine tool error detection technology.

Full-scale measurement of CNC machine tools

Geometric error measurement is crucial for error compensation and machining accuracy of CNC machine tools. However, traditional double-ball bar (DBB) method cannot be used for full-scale measurement of geometric errors due to the constant length of bars. In this paper, a full-scale measurement of geometric errors for CNC machine tools with high efficiency is carried out based on the double ball bar with a ball joint (J-DBB) method. Firstly, the principle of J-DBB is introduced. The J-DBB can be used for a full-scale measurement thanks to its freely measuring radius. Then, the equations of geometric errors which include squareness error, straightness error, roll error, pitch error, and yaw error of the axes are theoretically analyzed. In the end, we compared the theoretical trajectories of circular interpolation with the actual ones. The geometric errors between theoretical trajectories and actual ones can be measured and shown by J-DBB method. The results revealed that the J-DBB can be applied to conduct the full-scale measurement of geometric errors in CNC machine tools. Besides, the measurement range of geometric errors is extended from a two-dimensional circle to a three-dimensional sphere with a radius of 0.259L to 2L.

Multivariate orthogonal polynomial-based positioning error modeling and active compensation of dual-driven feed system

The nonsynchronous error of the dual-driven feed system seriously affects the positioning and machining accuracy of CNC machine tools. Improving the positioning error is an extremely important task as it determines the geometric accuracy of the manufactured parts. In this paper, a Multivariate Orthogonal Polynomial Regression model has been developed to predict the positioning error in terms of motion parameters such as position and speed of the X1 and X2 axes of the dual-driven worktable. Orthogonal Experimental Design has been engaged in conducting experiments. The positioning errors are measured by a dual-frequency laser interferometer. In addition, a real-time error compensation system is developed based on the proposed active compensation control strategy in the dual-driven feed system controlled by Beckhoff motion control card. Experimental results show that the proposed positioning error model and error compensation strategy can be utilized as an effective manner to improve the accuracy of dual-driven CNC machine tools.

Rapid Measurement and Identification Method for the Geometric Errors of CNC Machine Tools

Error compensation technology offers a significant means for improving the geometric accuracy of CNC machine tools (MTs) as well as extending their service life. Measurement and identification are important prerequisites for error compensation. In this study, a measurement system, mainly composed of a self-developed micro-angle sensor and an L-shape standard piece, is proposed. Meanwhile, a stepwise identification method, based on an integrated error model, is established. In one measurement, four degrees-of-freedom errors, including two-dimensional displacement and two-dimensional angle of a linear guideway, can be obtained. Furthermore, in accordance with the stepwise identification method, the L-shape standard piece is placed in three different planes, so that the measurement and identification of all 21 geometric errors can be implemented. An experiment is carried out on a coordinate measuring machine (CMM) to verify the system. The residual error of the angle error, translation error and squareness error are 1.5″, 2 μm and 3.37″, respectively, and these are compared to the values detected by a Renishaw laser interferometer.

Research on Thermal Topology Design Method of Spindle Based on HCAM

Spindle thermal error is one of the key factors in the machining accuracy of CNC machine tool. In order to reduce the thermal error of the spindle and improve the machining precision of the CNC machine tool, the idea of the thermal topology design based on the hybrid cellular automaton method (HCAM) is proposed. In this paper, the existing research results of hybrid cellular automaton are summarized, and the main achievements of domestic and foreign research work are analysed and reviewed from the aspects of structural topology optimization. Finally, the realization and prospect of HCAM self-optimizing thermal topology design method for spindle are presented.

A two-stage friction model and its application in tracking error pre-compensation of CNC machine tools

Friction modelling and compensation is an important artifice to improve the tracking accuracy of CNC machine tools used for welding, 3D printing and milling, etc. This paper proposes a two-stage friction model to describe the characteristics of friction. First, a novel method is proposed to distinguish the boundary between the presliding and sliding regimes of non-linear friction by estimating the breakaway velocity of static friction based on its elastic characteristics. Then, a two-stage feedforward friction compensation model which only has relationship with the velocity is developed. The proposed friction model not only can describe the Stribeck phenomena of friction, but also represent the characteristics of the static friction. A tracking error pre-compensation model is developed thereafter based on the good performances of feedforward friction compensation, in order to further reduce the tracking error of CNC machine tools. Extensive experiments and analyses verify that the proposed friction model and tracking error pre-compensation method can significantly improve the tracking accuracy of CNC machine tools. Specifically, comparison with existing tracking-error based friction model shows that the proposed model can reduce maximum and average tracking errors more than 70% and 20%, respectively. Furthermore, contouring errors of multi-axis motion are also reduced to some extent.

A Method for Evaluating the Speed and Accuracy of CNC Machine Tools

A Method for Evaluating the Speed and Accuracy of CNC Machine Tools

Model of a CNC Feed Drive for On-Site Tuning of the Controllers for Single Axis Motion

The accuracy of CNC machine-tools is heavily influenced by the correct tuning of the feed drives controllers. While an initial tuning is performed by the machine-tool manufactures, in time the values have to be changed by the user in order to preserve positioning and contouring accuracy of the machine. This paper presents a model of a CNC feed drive, for a particular CNC machine-tool, but with a high degree of generality. The objective is to provide the user the necessary knowledge, together with a simple, yet accurate simulation tool, in order to assist him in the process of tuning the controllers.

Application of sliced inverse regression with fuzzy clustering for thermal error modeling of CNC machine tool

Thermal error significantly influences the accuracy of CNC machine tool. A high-performance compensation system depends upon the accuracy and robustness of the model and appropriate model inputs of temperatures. In this paper, fuzzy clustering is conducted in temperature classification. Based upon an evaluation model, an optimal temperature classification can be found. The representative temperatures from each group construct temperature candidates. Then, a sliced inverse regression (SIR) model is introduced in thermal error modeling, which can change the problem of high-dimensional forward regression into several one-dimensional regression and meanwhile further eliminate the coupling among temperatures candidates. To evaluate the performance of SIR model, measuring experiment was carried out on a horizontal machining center for temperature and thermal error information under two experimental conditions. The proposed classification method was used to classify 29 temperature variables into five groups. A SIR model was built upon the five temperature candidates. Meanwhile, stepwise regression (SR) theory is also conducted for temperature variable selection and thermal error modeling. Comparison shows that both of the two models have high fitting accuracy, while the SIR model is more excellent in robustness than the SR model. Finally, a compensation system was developed. Compensation experiment shows that the SIR model is practical and effective, which can reduce the axial thermal error from 43 to 7 μm.

Unified error model based spatial error compensation for four types of CNC machining center: Part I—Singular function based unified error model

To unify the error model for four types of CNC machining center, the comprehensive error model of each type of CNC machining center was established using the homogenous transformation matrix (HTM). The internal rules between the HTMs and the kinematic chains were analyzed in this research. The analysis results show that the HTM elements associated with the motion axes which are at the rear of the reference coordinate system are positive value. On the contrary, the HTM elements associated with the motion axes which are at the front of the reference coordinate system are negative value. To express these internal rules, the singular function was introduced to the HTMs. And a unified error model for four types of CNC machining center was established based on the HTM and the singular function. The unified error model includes 18 error elements which are the main factors affecting the machining accuracy of CNC machine tools. The practical results show that the unified error model is not only suitable for vertical machining center but also suitable for horizontal machining center.

Detection and Compensation of Positioning Accuracy Based on the Laser Interferometer

The positioning accuracy of CNC machine tool is the best moving position accuracy which the machine tool can reach under the control of CNC control system. The principles of frequency laser interferometer measurement are described in this paper, and pitch error is compensated by taking DAHE V1500 CNC machine with FANUC system as example. The result shows that the precision of CNC machine tool is effectively improved.

Research on Volumetric Error Measurement, Modeling and Compensation for NC Machine Tools

With the increasing requirements of the machining accuracy of CNC machine tools, the impact of thermal deformation is growing. Thermal error compensation technology can predict and compensate the thermal errors in real-time, and improve the machining accuracy of the machine tool. In this paper, the research objects of thermal error compensation is expanded to the volumetric error of the machine tool, the volumetric error modeling of a three-axis machine tool is fulfilled and a compensator is developed for the compensation experiment, which provides scientific basis for the improvement of the machining accuracy.

The Use of Response Surface Methodology to Optimize Parameter Adjustments in CNC Machine Tools

This paper mainly covers a research intended to improve the circular accuracy of CNC machine tools and the adjustment and analysis of the main controller parameters applied to improve accuracy. In this study, controller analysis software was used to detect the adjustment status of the servo parameters of the feed axis. According to the FANUC parameter manual, the parameter address, frequency, response measurements, and the one-fourth corner acceleration and deceleration measurements of the machine tools were adjusted. The experimental design (DOE) was adopted in this study for taking circular measurements and engaging in the planning and selection of important parameter data. The Minitab R15 software was adopted to predict the experimental data analysis, while the seminormal probability map, Plato, and analysis of variance (ANOVA) were adopted to determine the impacts of the significant parameter factors and the interactions among them. Additionally, based on the response surface map and contour plot, the optimal values were obtained. In addition, comparison and verification were conducted through the Taguchi method, regression analysis to improved machining accuracy and efficiency. The unadjusted error was 7.8 μm; through the regression analysis method, the error was 5.8 μm and through the Taguchi analysis method, the error was 6.4 μm.