Computer Numerical Control Machine Tools Research Articles

Effect of detector installation error on the measurement accuracy of multi-degree-of-freedom geometric errors of a linear axis

A linear axis is the key component of several mechanical machines, especially of computer numerical control machine tools. The simultaneous measurement of the geometric motion errors of a linear axis is indispensable to compensate the machine errors, which improves the accuracy of machine tools. The principle of laser collimation is widely used for measuring the multi-degree-of-freedom (MDOF) geometric motion errors of a linear axis. However, installation errors of the detectors affect the measurement accuracy. In this study, we have proposed, for the first time, a measurement model for investigating the influence of all detector installation errors on the accuracy of the simultaneous measurement of MDOF geometric motion errors in a linear axis. The effect of detector installation errors on the horizontal straightness, vertical straightness, pitch, and yaw are analyzed using the homogeneous transformation method, which indicates that angular installation errors of detectors along the X0-axis direction can cause a crosstalk between the two straightness errors and between pitch and yaw errors. In addition, translational installation errors of position-sensitive detectors in the X0-axis direction, which is often called the defocusing amount, has a significant effect on the pitch and yaw measurements. To elucidiate the effect of defocusing, a measurement model was verified by both Zemax simulation and experiments. The experimental results indicate that the maximum deviation of the measured results obtained using the proposed model from that obtained using a Renishaw XL-80 interferometer can be greatly reduced by compensating the measurement errors induced by defocusing.

Consistency retention method for CNC machine tool digital twin model

Computer Numerical Control Machine Tool (CNCMT) Digital Twin (DT) model is a carrier for complex, time-varying, coupled data of CNCMT, which can theoretically provide a time-varying high-fidelity model. However, there are still many difficulties in its implementation process. And the key issue is how to realize the updated DT model with performance attenuation and validate it. In order to solve this problem, a model consistency retention method for CNCMT DT model is studied and proposed in this paper. Firstly, the framework of consistency retention method for DT model is designed including both digital space and physical space. The principles of data management and performance attenuation update in digital space are elaborated. Then, the implementation method for consistency retention of CNCMT DT model is studied in terms of performance attenuation update workflow for wear and other damage separately. Finally, a case study for the establishment and application of high-fidelity test bench DT model that focusing on rolling guide-rail is carried out to show the implementation flow of the proposed method and verify its operability and effectiveness.

A nominal radial stiffness prediction model for HSK tool holder-spindle flange interface

The connection characteristics of HSK tool holder-spindle system have great influences on machining precision and security of computer numerical control machine tools. In order to predict dynamic behaviors and avoid connection failure of HSK tool holder-spindle system, a nominal radial stiffness prediction model for HSK tool holder-spindle flange interface is constructed. Contact stress of spindle and HSK tool holder can be obtained by considering actual interference and actual clamping force. Considering elastic contact deformation, the plastic contact deformation, and two different regimes of elastoplastic contact deformation, a fractal model of nominal contact stiffness of HSK tool holder-spindle flange interface is proposed. In order to prove the rationality of the model, the tests are validated by a self-designed equipment. The effects of different parameters to the maximal permissible rotational speed, critical bending moment, and nominal radial stiffness of HSK tool holder-spindle connection system are researched. The results can be used as an instruction for the application of HSK tool holder and optimization of geometry parameters.

Machine monitoring system: a decade in review

In recent years, significant advancements have been achieved in the domain of machine monitoring as witnessed from the beginning of the new industrial revolution (IR) known as IR 4.0. This new revolution is characterized by complete automation, and an increase in the technological deployments and advanced devices used by various systems. As a result, considerable advancement has been reported by researchers and academia around the world by adopting and adapting the new technology related to the machine condition monitoring problem. For these reasons, it is important to highlight new findings and approaches in machine condition monitoring based on the wireless sensor solution and machine learning signal processing methodology that are relevant to assist in advancing this new revolution. This article presents a comprehensive review on tool condition monitoring (TCM), tool wear, and chatter based on vibration, cutting force, temperature, surface image, and smart label monitoring parameters from signal acquisition, signal processing methodology, and decision-making, particularly for the milling process. The paper also provides a brief introduction to the manufacturing industries and computer numerical control (CNC) machine tool demand and a review of machine monitoring and countries involvement in machine monitoring, as well as the approaches and a survey of machine monitoring. The aim is to contribute to this rapidly growing field of machine condition monitoring research by exploring the latest research findings on the solution approach for milling machine process monitoring, to help expedite future research, and to give some future direction that needs to be considered as a path to produce a standardized CNC machine platform.

Research on Deterministic Figuring of Ultra-Precision Shaft Parts Based on Analysis and Control of Figuring Ability.

The application of ultra-precision shaft parts is widely used, such as the spindle core of the air bearing spindle in ultra-precision machine tools. The precision of the spindle core is extremely high, and it is very difficult to obtain directly by traditional Computer Numerical Control (CNC) machine tools but is mostly obtained by manual grinding, whose machining efficiency is greatly limited. Based on the deterministic figuring theory, this paper focuses on the ultra-precision roundness, optimizing the filtering parameters of the measurement error data and studying the generation mechanism of the removal function morphology; the shape of the removal function is adjusted by combining the analysis of the figuring ability and positioning error. Finally, the optimized removal function is used on an experimental steel shaft, the average roundness convergence ratio is 72% higher than that of the original removal function, and the roundness reaches a 0.1 μm level. The result shows that a reasonable filtering of measured data and the removal function adjusted for the surface feature can improve the efficiency and precision of deterministic figuring on shaft parts.

Reliability assessment of heavy-duty computer numerical control machine tools based on multi-performance multi-sequence hidden Markov model

Reliability assessment is vital to improve the efficiency and availability of heavy-duty computer numerical control machine tools (HCNCMT). Traditional reliability assessment methods based on time-to-failure data are difficult to achieve timely and accurate reliability estimation. In this paper, a new multi-performance multi-sequence hidden Markov model is proposed for the reliability assessment of the HCNCMT by building the relationship model between machine running states and multiple key performance parameters. It significantly improves assessment accuracy by fully mining a large number of performance degradation data and provides better support for its maintenance. Finally, four heavy-duty gantry computer numerical control boring and milling machines are taken as examples to validate the effectiveness of the proposed method.

Theoretical and experimental analysis of the preload degradation of double-nut ball screws

In most applications, preload is applied to double-nut ball screws to improve the positioning accuracy and rigidity. However, the applied preload degrades owing to wear, which lowers the positioning accuracy of the ball screws, and thus affects the accuracy of computer numerical control machine tools. In this study, to obtain the dynamic contact force and sliding velocities on the ball-raceway contact, we established a load distribution model and velocity variation model, respectively. Based on these models, we propose an accurate model for predicting the preload degradation of double-nut ball screws. The degraded preload of three ball screws was measured under high axial load-low speed, medium axial load-medium speed, and low axial load-high speed, with a running stroke of 7.2 million revolutions. The experimental results are in good agreement with the theoretical values calculated by the prediction model, which confirms the validity of the prediction model. Therefore, it was concluded that the proposed preload degradation model can accurately predict the performance and service life of double-nut ball screws.

A knowledge matching approach based on multi-classification radial basis function neural network for knowledge push system

We present an exploratory study to improve the performance of a knowledge push system in product design. We focus on the domain of knowledge matching, where traditional matching algorithms need repeated calculations that result in a long response time and where accuracy needs to be improved. The goal of our approach is to meet designers’ knowledge demands with a quick response and quality service in the knowledge push system. To improve the previous work, two methods are investigated to augment the limited training set in practical operations, namely, oscillating the feature weight and revising the case feature in the case feature vectors. In addition, we propose a multi-classification radial basis function neural network that can match the knowledge from the knowledge base once and ensure the accuracy of pushing results. We apply our approach using the training set in the design of guides by computer numerical control machine tools for training and testing, and the results demonstrate the benefit of the augmented training set. Moreover, experimental results reveal that our approach outperforms other matching approaches.

Performance Evaluation and Compensation Method of Trigger Probes in Measurement Based on the Abbé Principle.

Trigger probes are widely used in precision manufacturing industries such as coordinate measuring machines (CMM) and high-end computer numerical control(CNC) machine tools for quality control. Their performance and accuracy often determine the measurement results and the quality of the product manufacturing. However, because there is no accurate measurement of the trigger force in different directions of the probe, and no special measuring device to calibrate the characteristic parameters of the probe in traditional measurement methods, it is impossible to exactly compensate for the measurement error caused by the trigger force of the probe in the measurement process. The accuracy of the measurement of the equipment can be improved by abiding by the Abbé principle. Thus, in order to better evaluate the performance parameters of the probe and realize the accurate compensation for its errors, this paper presents a method which can directly measure the performance parameters of the trigger probe based on the Abbé measurement principle, expounds the measurement principle, the establishment of the mathematical model, and the calibration system, and finishes with an experimental verification and measurement uncertainty analysis. The experimental results show that this method can obtain the exact calibration errors of the performance parameters of the trigger probe intuitively, realize the compensation for the errors of the probe in the measurement process, and effectively improve the measurement accuracy.

Fabrication of Edge Rounded Polylactic Acid Biomedical Stents by the Multi-Axis Micro-Milling Process

This paper presents the first try to fabricate degradable polylactic acid (PLA) biomedical stents with round edges by the multi-axis micro-milling process. Conventionally biomedical stents are produced by laser processing. Post-processing operations are usually required to handle sharp edges and thermal defects of the stent due to laser processing. A computer graphics software package was used to design the strut structures with round corners of the PLA stent. A PLA tube was first created using injection molding, and a degradable biomedical stent was then fabricated through micro-milling by using a five-axis computer numerical control (CNC) machine tool. This study investigated the error in the rotation center that can occur during five-axis micro-milling. Data obtained from experiments on center-of-rotation errors were substituted into homogeneous coordinate conversion formulas. Center-of-rotation errors in the five-axis machine tool were compensated for improving the milling precision (A and C axes) to be within 5 μ m. Furthermore, milling parameter optimization experiments were conducted, which determined the optimal conditions for milling PLA to be a spindle speed of 60,000 rpm, feed per tooth of 0.005 mm, and feed rate of 600 mm/min, and achieved the minimum burr 0.01 mm and the average surface roughness (Ra) 0.4 μ m. These optimal cutting parameters will be used in the following actual stent processing experiments. Finally, the error compensation and optimal parameters were combined in a CAM software package and layered spiral micromilling to machine the actual stent. The experimental results revealed that the combination of five-axis micro-milling led to the successful fabrication of a degradable biomedical stent (stent diameter = 6 mm, strut width = 0.3 mm, and radius at round corners = 0.1 mm). The machined actual stent had cross-section height and width errors within 0.01 mm, and arc depth of cut variation within 6 μ m. In addition, the PLA stent machining results indicated a rebound of approximately 33% at the strut round edge machining. This work may also open up future possibilities for complex three-dimensionally structured biomedical stents for better performance and special functionality.

Modular design research of computer numerical control machine tools oriented to customer requirements

In order to study the modular design of computer numerical control machine tools oriented to customer demands, the customer demand information model was established based on rough analytic hierarchy process and information entropy by analyzing and transforming customer demands. Based on the domain mapping method of axiomatic design and quality function deployment integration, the product function model and structure model of computer numerical control machine tools are established. Based on fuzzy clustering analysis, the module division of computer numerical control machine tools is studied, and the dynamic clustering diagram of computer numerical control machine tools is formed with MATLAB as the operating environment. Based on Technique for Order Preference by Similarity to Ideal Solution method, the scheme of computer numerical control machine tools module division is evaluated. Taking the horizontal computer numerical control machine tool products of Shenyang Machine Tool Group as an example, the module division is carried out. The example design and the result analysis prove that the module division system is very effective and fast.

Contour Tracking Control Based on Extended State Observer for Multiaxis Motion System

In the contouring process, the trajectory generated by the computer numerical control (CNC) machine tool is a result of the multiaxis coordinated motion. The contour error has a direct impact on the accuracy of the machined product. To obtain higher contouring accuracy of the multiaxis motion control system, this paper presents a cross-coupled control approach based on the extended state observer sliding mode control. First, a single-axis sliding mode controller is designed, and an extended state observer is used to estimate system disturbances and improve the system robustness. Then, the cross-coupled control approach handles the coordinated motion of multiple axes to improve the contour control accuracy. Next, a simulation study is conducted on the three-axis motion platform. Its result shows that the control algorithm is effective in reducing tracking errors and contour errors.

Active vibration suppression in robotic milling using optimal control

Six degree-of-freedom (6-dof) industrial robots are attractive alternatives to Computer Numerical Control (CNC) machine tools for milling of large parts because of their low-cost, greater versatility, and larger work volume. However, 6-dof industrial robots are significantly more compliant than CNC machine tools, which makes them prone to vibrations during milling. An additional complexity of industrial robots is their pose-dependent vibration characteristics. This paper presents a pose-dependent optimal control methodology to actively suppress tool tip vibrations generated by the periodic milling forces in robotic milling. Discretely sampled robot structural modal parameters as a function of robot configuration (pose) are used to develop a data-driven Gaussian Process Regression (GPR) model. The model is then utilized to solve the Linear Quadratic Regulator (LQR) optimal control problem to obtain pose-dependent controller gains necessary for vibration suppression. The pose-dependent controller is implemented on a 6-dof industrial robot and its performance evaluated through process-independent offset mass experiments and through milling experiments. The methodology is shown to be effective in decreasing the tool tip vibrations and improving the machining accuracy in robotic milling.

Research and application on rapid recognition of CNC machine tools’ running state

A rapid recognition of CNC (Computer Numerical Control) machine tools’ running state based on time domain characteristic parameters and frequency domain correlation coefficient was proposed. The experiment proved the accuracy and efficiency of the mentioned method, which made the states recognition rate reach 93.33% and the identification efficiency improve 66.67%. In this scenario, a theoretical foundation is established for the condition-based maintenance of CNC machine tools.

Research and development of monitoring system and data monitoring system and data acquisition of CNC machine tool in intelligent manufacturing

Intelligent manufacturing as the development direction of the new generation manufacturing system has become a hot research topic. Computer numerical control (CNC) machine tools are the core manufacturing equipment in discrete manufacturing enterprises, collecting and monitoring the data is an important part of intelligent manufacturing workshops. It has a great significance to improve the production efficiency of enterprises and eliminate information islands. The purpose of this article is to solve the problems of data acquisition and monitoring of CNC machine tools in the manufacturing workshop of enterprises. This article uses FOCAS data acquisition method to research and develop the data acquisition and monitoring system of CNC machine tools in intelligent manufacturing workshop. The research results show that the equipment information model based on MTConnect protocol and FOCAS can solve the data acquisition and storage functions of CNC machine tools well. Using the object-oriented Petri net model, it can solve various uncertain factors in numerical control (NC) machining tasks and realize the monitoring function of CNC machining tasks in the workshop. Based on the NC program analysis, the calculation method of machining time in the NC program can determine the preventive maintenance cycle of the machine based on the machine fault information. Based on VS2013 development environment, Qt application framework and SQL Server 2012 database, the numerical control machine tool data acquisition and monitoring prototype system was developed, and the system was verified in the workshop to prove the effectiveness of the system.

A review on vibration analysis and control of machine tool feed drive systems

With the development of the modern manufacturing industry, especially that of high-speed and high-precision machining, higher performances of computer numerical control (CNC) machine tools are necessary than ever. For high-precision CNC machine tools, vibration in high-speed machining is an important factor to affect the machining accuracy. As a significant part of CNC machine tools, the dynamic characteristics of the feed drive system have a great impact on the machining performance. Ball screw drive systems are widely applied in the majority of CNC machine tools for the time being. In the process of high-speed machining, the vibration of the ball-screw drive system will affect the stability of the control system and the machining accuracy of CNC machine tools. Thus, further investigation of dynamic characteristics and vibration control methods of the ball-screw drive system will be of great importance to improve the machining performance. A comprehensive review is carried out here to research statuses of vibration analysis and control methods for feed drive systems. Related studies on system modeling, parameter identification, and vibration control technologies are classified and summarized. The advantages and disadvantages of different methods are discussed and compared. Moreover, the linear parameter-varying (LPV) modeling method of ball-screw drive systems and corresponding control technologies are introduced in detail. Finally, related research prospects are systematically presented based on the existing studies, and these research directions which are rarely studied will be of great significance to develop vibration control technologies for CNC machine tool feed drive systems.

Hazards That Can Affect CNC Machine Tools during Operation—An AHP Approach

CNC (computer numerically controlled) machine tools are highly advanced technological systems, used to machine parts by means of metal cutting processes. Their structure and kinematics are very complex, involving accurate coordinated motions on three to five axes. Operating CNC machine tools is a complicated process, which can easily be affected by errors. Nowadays, safety systems and devices are developed in order to make this process safer and more user friendly. Modern CNC controllers are designed to deal with obvious sources of hazards, such as overloads (by means of various sensor systems) and collisions (by checking the NC code syntax and simulating it on the machine). However, despite of these safety systems, various unwanted events still occur during machining operations on CNC machine tools. These means that there are still certain hazards, not so obvious, which can severely affect the operation of CNC machine tools. This work tries to identify and hierarchize the above-mentioned hazards by using an AHP (analytic hierarchy process) approach. The results of the AHP emphasize which hazard has the biggest influence upon the CNC machine tools operation and consequently should be avoided. The results of this work could be used by the machine tools designers to develop new safety features for the existing CNC controllers. Also, the users of the machine tools could focus some of the safety measures during the machining process upon the most significant hazards pointed by the results of the research.

An early fault elimination method of computerized numerical control machine tools

Early faults of product have plagued many machine tool companies, especially middle-small enterprises limited by capital. To eliminate the early faults and improve the reliability of computerized numerical control (CNC) machine tools, we propose a systematic early fault elimination method based on the after-sale data (customer field data) of CNC machine tools. The proposed method includes four steps: fault data collection; a four-parameter non-homogenous Poisson process (NHPP) model; a mixed fault analysis method that is the combination of fault tree analysis (FTA) method and fault mode, effects, and criticality analysis (FMECA) method; and early fault elimination measures. The first step is the basis of the analysis. The second step is used to determine the early faults from the fault data. The third step is to analyze the early faults determined. Risk priority number (RPN) is calculated to assess the criticality of the fault causes determined by the FTA. The elimination measures are taken in the end. We apply our method to a machine tool company in China, and the results prove the practicality and effectiveness of the proposed method.

Experimental analysis of the wear coefficient of double-nut ball screws

The wear coefficient is an important parameter that directly determines the wear rate of ball–raceway contact in ball screws and thus affects the degradation of the accuracy of ball screws and computer numerical control machine tools. However, few studies have experimentally studied the wear coefficient of ball screws. The present paper proposes a model for calculating the wear coefficient by considering the wear mechanism at the ball–raceway contact in ball screws. More importantly, a novel test method is implemented to measure the wear coefficient of seven double-nut ball screws, with total running of 48 million revolutions. Experimental results show two obvious wear stages and give wear coefficients that are several orders of magnitude lower than the empirical wear coefficient for continuous sliding friction between steel and steel, mainly owing to the special motion and wear mechanism of ball screws. The findings are important to the study of the degradation of the performance of ball screws due to wear.

Research on processing technology of grinding aspheric workpiece in the five-axis machine tool

Aspheric optical components have been widely used recently because of their unique advantages. Thus, it is necessary to investigate processing technology of such aspheric parts. In this paper, an aspherical mirror is ground with cup wheel in five-axis computer numerical control (CNC) machine tool and corresponding processes were investigated. To improve machining efficiency and reduce tool wear, the workpiece is firstly ground to be a spherical mirror, and then it is ground to be the aspheric contour. The best fitting spherical mathematical equation is derived by the axisymmetric quadratic aspheric generatrix equation. A ∅90 mm aspheric mirror was ground with cup wheel with five-axis computer numerical control (CNC) machine tool. The aspheric curve is processed into a paraboloid shape. The experimental results show that the surface profile of the aspherical lens is consistent with the designed profile, and the peak value (PV) value of the error is 4.77μm. Such results can be accepted in consideration of working allowance for polishing. According to the experimental results, the cause of the error was analysed and methods for improving precision were proposed.