Precision Machine Tools Research Articles

Optimal Design Method for Static Precision of Heavy-Duty Vertical Machining Center Based on Gravity Deformation Error Modelling

Due to the large size and large span of heavy-duty machine tools, the structural deformation errors caused by gravity account for a large proportion of the static errors, and the influence of gravity deformation must thus be considered in the machine tool precision design. This paper proposes a precision design method for heavy-duty vertical machining centers based on gravity deformation error modelling. By abstracting the machine tool into a multibody system topology, the static error model of the machine tool is established based on the multibody system theory and a homogeneous coordinate transformation. Assuming that the static error of each motion axis is composed of two parts, i.e., the manufacturing-induced geometric error and the gravity deformation error, the machine tool stiffness model of the relationship between gravity and deformation error is developed using the spatial beam elements. In the modelling process, the stiffness coefficients and volume coefficients of the components are introduced to fully consider the influences of structural parameters on machine tool precision. Taking the machine tool static precision, the component stiffness coefficients and the volume coefficients as the design variables, based on the use of the worst condition method, error sensitivity analysis and global optimization algorithm, the optimal allocation of the static error budget of the machine tool and the structural design requirements of each component are determined, providing a valuable guide for the detailed structure design and manufacture processing of the machine tool components.

Sensor selection and tool wear prediction with data‐driven models for precision machining

AbstractEstimation of tool wear in precision machining is vital in the traditional subtractive machining industry to reduce processing cost, improve manufacturing efficiency and product quality. In this vein, fusion of time and frequency‐domain features of commonly sensed signals can provide an early indication of tool wear and improve its prediction accuracy for prognostics and health management. This paper presents a data‐driven methodology and a complete tool chain for the inference of precision machining tool wear from fused machine measurements, such as cutting force, power, audio and vibration signals, and quantify the usefulness of each measurement. Indicators of tool wear are extracted from time‐domain signal statistics, frequency‐domain analysis, and time‐frequency domain analysis. Correlation coefficients between the extracted features (indicators) and the tool wear are used to select the most informative features. Principal Component Analysis and Partial Least‐Squares are used to reduce the dimensionality of the feature space. Regression models, including linear regression, support vector regression, Decision tree regression, neural network regression and Gaussian process regression, are used to predict the tool wear using data from a Haas milling machine performing spiral boss face milling. The performance of the regression models based on subsets of sensors validates the preliminary estimates about the saliency of the sensors. The experimental results show that the proposed methods can predict the machine tool wear precisely, with readily available sensor measurements. Neural network and Gaussian process regression were able to achieve good estimates of tool wear at different machine operating conditions. The most informative signal in predicting tool wear was shown to be the vibration signal. Time‐frequency domain features were the most informative features among the combination of features of three domains. In addition, using partial least squares components extracted from the original features of signals led to higher prediction accuracy.

Mist-edge-fog-cloud computing system for geometric and thermal error prediction and compensation of worm gear machine tools based on ONT-GCN spatial–temporal model

The geometric precision of worm gears (WGs) determines the service performance and life of precision machine tools, indexing turntables and other equipment. The machining accuracy of worm gear machine tools (WGMTs) is the core to guarantee the geometric precision of WGs, and is greatly affected by the thermal and geometric errors. To improve the machining accuracy of WGMTs, the thermal and geometric errors should be controlled and compensated. But the control system has a poor real-time performance, and the synchronous control of the geometric and thermal errors cannot be currently achieved, and the thermal error model has a low prediction accuracy and low robustness. To make up for the above gap, a mist-edge-fog-cloud computing system is designed for the error prediction and compensation to relieve the bandwidth pressure of the industrial Internet. Moreover, a sensor network composed of multiple sensors is constructed to obtain the thermal information, and then the ordered neuron temporal-graph convolutional network (ONT-GCN) is proposed based on the ordered neuron-long short term memory network (ON-LSTMN) and graph convolutional network (GCN) for the first time to conduct the spatial and temporal modeling of the thermal error data. The interaction among multiple sensors is explicitly considered, and the dependence of the temporal information of the thermal error data on and spatial information of sensors is taken into account. Besides, to realize the error control, the mapping relationship between the tooth surface error and geometric-thermal errors is established. The error mapping model converts 51 geometric errors and 4 thermal errors into the spatial errors of the hob. Moreover, the sensitivity of errors is analyzed, and then the key error items that affect the geometric precision of the tooth surface are identified and compensated. The results show that the ONT-GCN is superior to traditional time-series modeling methods and that the mist-edge-fog-cloud computing system can effectively shorten the executing time compared with other system frameworks, and can improve the machining accuracy of WGMTs.

Feedback control–based active cooling with pre-estimated reliability for stabilizing the thermal error of a precision mechanical spindle

The thermal error stability (STE) of the spindle determines the machining accuracy of a precision machine tool. The “active cooling-spindle” system is regarded as a feedback control system, and the data-driven thermal error model is utilized to output feedback. In this way, the spindle thermal error can be stabilized by the homeostasis ability of the feedback control system under disturbance. Structural temperature measurements are considerably interfered by the active cooling, so the regression models trained with experimental data might output inaccurate feedback in unseen work conditions. Such inaccurate feedbacks are the primary cause for excessive fluctuations and failures of the thermal error control processes. The independence of the thermal data is analyzed, and a V-C (Vapnik–Chervonenkis) dimension–based approach is presented to estimate the generalization error bound of the regression models. Then, the model which is most likely to give acceptable performance can be selected, the reliability of the feedback can be pre-estimated, and the risk of unsatisfactory control effect will be largely reduced. Experiments under different work conditions are conducted to verify the proposed strategy. The thermal error is stabilized to be within a range smaller than 1.637 μm, and thermal equilibrium time is advanced by more than 78.3%.

Modelling and Analysis of CNC Milling Machine Bed with UHM CFRP composite Material

Abstract: Structural materials are used in a machine tool have a key role in defining the productivity, accuracy and Size proportions of the part manufactured by machine tool. The conventional structural materials like cast iron and Stainless or carbon steel at high operating speeds but used in precision machine tools grow positional errors due to the vibrations transferred into the Machine tool structure. Faster cutting speeds can be achieve only by structure which has good damping characteristics and high stiffness. Clearly the life of a machine tool is proportional to the levels of vibration Produce by machine. The further Work is carried out to Study the deformation and natural frequency using Static analysis and Modal analysis respectively. The bed in machine tool Took Major role in the precision in components. It is one of the greatest vital tool structures which is absorb the vibrations resultant from the cutting operation. To analyse the bed for possible material changes and Structure changes that could increase stiffness, decrease weight, expand damping characteristics and segregate natural frequency at the operating range. So main enthusiasm behind the impression to go for a composite Material in model involving ultra-High Modulus Carbon Fibre Reinforced Polymer Composite Material (UHM CFRP). In a carbon has good stiffness and strength properties but its absences in damping requirements. On the other hand, polymers, though its deficiencies in strength but, good damping in characteristics and it is easily holding the carbon fibres. So, this is makes greatest combination of materials in an appropriate manner. In this work, a machine tool’s bed is selected for the analysis static loads. Then study is carried out to decrease the weight of the machine tool’s bed without affecting its structural rigidity. The 3D CAD model of the bed has been created by using commercial 3D modelling software and analyses were carried out using ANSYS 2021 R2. Keywords: Composite material, hybrid structures, Milling machine bed, UHM CFRP.

Coaxiality error analysis and optimization of cylindrical parts of CNC turning process

High precision rotary shafts with precise geometrical tolerances are generally mounted with a micron level clearance between the gears and casing during operation in industrial applications. Dynamics cyclic loads are inevitable in most of these applications which has an adverse effect on the fatigue life of the critical parts. Ensuring close dimensional tolerances and coaxiality during machining is highly desirable, as it affects the rotary characteristics in many applications. Thus, control of coaxiality error plays a vital role in rotating shafts and high precision machine tools. However, use of high precision machining would drastically increase the cost of manufacturing. Thus, a cost-effective machining process that could potentially reduce the coaxiality error is of high industrial importance. The present research efforts made an attempt to achieve minimum coaxiality error on cylindrical machined parts by optimizing parameters (cutting speed, feed rate, depth of cut and cutting tool nose radius). Experiments are planned, viz. central composite design matrix and statistical analysis determine the influence of machine parameters on coaxiality error of high-strength Al 7075 alloy by applying response surface methodology. Feed rate and depth of cut factors showed significant effect on coaxiality error. All machining parameters showed a non-linear effect on coaxiality error, which defines the strong interaction factor effects. The empirical equations derived were used to minimize coaxiality error by determining a set of machining parameters, viz. applying Big-Bang and Big Crunch and Rao (Rao-1, Rao-2 and Rao-3) algorithms. Rao algorithms outperform the Big-Bang and Big Crunch algorithm both in computation effort and solution accuracy. The results of Rao algorithms are experimentally verified, which resulted in reduced coaxiality error equal to 1.013 µm and resulted in 72.6% improvement compared to CCD experiments.

A PRIORI METHOD FOR EVALUATING THE KINEMATIC ACCURACY OF BALL SCREW GEARS

Helical gears are the most common type of drive that converts rotational motion into translational motion. Ball screw gears are the most widely used in precision instruments and machine tools. Currently, the issue of improving the reliability of the drive containing a ball screw transmission, according to the parameter “kinematic accuracy”, is relevant. The method of probabilistic estimation of the aftereffect of screw gears is considered. The method is based on the results of the analysis of the functioning of the transmission parts, followed by the synthesis of a model of the accuracy of screw gears. A comparative analysis of the magnitude of the aftereffect of some screw gear designs is performed. The prospect of using planetary mechanisms with threaded rollers and nonrack mechanisms with threaded rollers in three-dimensional hingerod structures such as: mobile reconfigurable robotic stations, robotic systems, collaborative and exoskeletal robots is shown.

A study on accuracy of linear ball guide

The accuracy of linear motion guide greatly affects the form accuracy of the processed parts in precision machine tools. For the linear ball guide, it is an important issue that how to improve accuracy by optimizing structure parameters based on the geometric errors. Due to the diversity of geometric errors and structure parameters, it requires a quantitative indicator of error averaging ability to judge whether a linear ball guide has higher accuracy. In this article, based on the newly built accuracy model and the newly defined averaging coefficient, the influence of rail profile errors and deformation errors on the error motions in five degrees of freedom can be quantitatively studied for the guides with one row of balls, one block and four blocks. It finds that, both the straightness and angular accuracies increase as the number of contact balls increases. For the guides with one and four blocks, the profile errors with integer wave numbers have main influence on the straightness and primary angular (around the moving direction) error motions, while those near both sides of integer wave numbers have main influence on the supporting angular error motions. The influence of deformation errors on accuracy coincides with that of profile errors. The accuracy model discussed can be conveniently used to predict error motions, select optimized number of contact balls and select optimized spacing of adjacent mounting holes in the design process of linear ball guide.

Analysis of thermal error model of ball screw feed system based on experimental data

In order to investigate the effect of thermal expansion on the ball screw feed system (BSFS) of a precision machine tool, theoretical modeling of and experimental study on thermally induced error are focused in this paper. A series of thermal experiments are conducted on the machine tool to measure the temperature of the main heat source and measuring points of BSFS. This study is to classify the main heat sources and discuss the impact on the ball screw feed system separately. By the experimental data of ball screw system, the thermal model of screw shaft in the axial direction is analyzed and verified. Based on the heat generation and transfer analysis of ball screw system, thermal expansion of screw shaft in the axial direction is modeled mathematically. In addition, by analyzing the effects of machining parameters such as rotational speed, preloads, and lead, we get the parameter influence of BSFS’s temperature rising and thermal deformation. This work can help us reduce thermal deformation effectively and improve the precision of CNC machining.

Active coolant control onto thermal behaviors of precision ball screw unit

Being a critical factor affecting the motion accuracy of precision machine tools, structural thermal elongation of precision ball screw unit is generally caused by the comprehensive influence from heat generations of screw-nut pair/bearings and time-varying ambient temperature. To resist 2 thermal disturbances above to guarantee precisely the original length of screw shaft, an active coolant control strategy is proposed in this paper. This strategy is based on a premise hypothesis: For the slender and long tubular structure of screw shaft, the screw shaft temperature is approximately equal to its recirculating coolant temperature. The reason is that the intensive forced coolant convection is capable of eliminating screw shaft temperature rises caused by friction heat generations and ambient air convections. Based on this premise, screw coolant temperature can be consistently controlled by an active strategy, further to correct the thermal elongation of screw shaft. It can be experimentally verified that the thermal variations of machine positioning accuracy caused by the active coolant control strategy are not more than 10 μm, which are lower than traditional strategy. Besides, based on detected structural temperatures of precision ball screw unit, the theoretical model above is further proved to be reliable by FE simulation method.

Research on the peak prediction and intelligent computing of reversal error for the tilt feed system installed on the precision machine tools

To effectively predict the peak of reversal error of tilt feed system and reduce reversal error caused by friction and gravity components, a peak prediction method of reversal error for tilt feed system on the precision NC machine tool is proposed. According to the load, tilt angle, motion trajectory, maximum static friction torque and relevant dynamic characteristic information, the peak prediction formula of the reversal error for the tilt feed system is established by mathematical derivation based on the kinematics, dynamics and torque balance during the process of reversal. Thus, the peak of reversal error for the tilt feed system can be obtained. The experimental results show that this method can achieve a good prediction effect, and can predict the peak of reversal error before the machining. It provides a theoretical basis for the reversal error suppression.

Cascaded sliding mode position control (SMC-PI) for an improved dynamic behavior of elastic feed drives

The precision of machine tools is essentially determined by the feed drive control. To improve the dynamic behavior of elastic feed drives, this paper presents a novel position control concept, substituting the conventional P position controller of the industrial cascade control with a continuous sliding mode controller (SMC) together with a Kalman Filter for state estimation. The novelty of this approach lies in the focus on practical applicability: The underlying PI-cascade structure leads to low commissioning effort and the SMC controller’s parameterization is simplified to a single tuning parameter. A general compliant feed drive model is used as plant, whose parameters usually are already known from commissioning of the velocity controller. The SMC position controller is derived analytically and its stability and damping properties are investigated for the dominating mechanical mode for uncertainties of the model parameters and a wide range of controller gains. The effectiveness of the SMC-PI controller is validated for an industrial ball screw feed drive. Extensive experimental results show a considerable decrease of tracking errors in command tracking, disturbance rejection and for a high speed cutting (HSC) milling experiment compared to P-PI cascade control, while stability margins remain almost independent of the controller gains. The parameterization is discussed on the basis of a theoretical analysis and measuring results. Furthermore, excellent robustness properties regarding model errors are demonstrated.

Self learning-empowered thermal error control method of precision machine tools based on digital twin

Self learning-empowered thermal error control method of precision machine tools based on digital twin

A passive compensated method with hydraulic transmission for static infinite stiffness of thrust bearing

Hydrostatic bearings are a core component of the worktable in heavy duty high-precision machine tools and a non-touch sliding pair composed of oil pads and guideway surfaces. The stiffness of an oil film produced by an oil pad is a key indicator that restricts the manufacturing precision and efficiency of machine tools. This paper presents a novel oil pad. It can withstand the impact of any step load in the designed range and always maintain the load position to only change in the submicron level. Therefore, the pad has the advantages of infinite stiffness and submicron precision stability. The pad performances were verified by the tests, and the theoretical, simulation and experimental results were highly consistent with one another.

Thermal-mechanical coupling calculation method for deformation error of motorized spindle of machine tool

Motorized spindle is one of the core components of precision machine tool. The precision of the motorized spindle will be subjected to thermal load and force load during its operation. These two kinds of loads will be coupled with the machining process, leading to the deformation error of a motorized spindle. So, a method of thermal- mechanical coupling calculation for deformation error of motorized spindle is proposed. Firstly, the thermal load and force load during operation of the motorized spindle are calculated, and the effect of force load on thermal load is also analyzed. On this basis, the changes of thermal load, force load and thermal boundary condition of motorized spindle are analyzed. With the increase of temperature, the heat generation and thermal boundary conditions of the bearing will change. Through iterative updating of heat generation and thermal boundary conditions, the deformation of the motorized spindle can be calculated in a thermal steady state. Finally, the thermal-mechanical coupling calculation method is verified by finite element simulation and experiment.

A novel transient infrared-thermography based experimental method for the inverse estimation of heat transfer coefficients in rotating bearings

Heat Transfer at moving bearing interfaces is a key parameter for the thermal characterization and design of high precision machine tools and electrical engine systems for e-mobility application. Yet, the majority of experimental approaches use tactile sensors to obtain the required temperature information for the calculation of heat transfer coefficients. However, only a limited amount of sensors can be placed in the investigated system, also including significant measurement uncertainties, long investigation times, and providing only access to local temperature information. To overcome these shortcomings, a novel method is presented, using infrared thermography to obtain transient and spatially resolved temperature information of bearing front surfaces. The recorded temperature data is used in an inverse evaluation algorithm, to determine the heat transfer coefficient, considering for modeling heat conduction as well as convective fluxes due to rotating components. Finally, experimental temperature data and calculated heat transfer coefficients are presented, discussing further the effect of low angular velocities on the heat transfer. It is shown, that this method is capable to detect changes in heat transfer coefficient due to variations in rotational speed which was not possible with existing methods. Concluding, this approach can be used in future work to focus in detail on the influence of different rolling elements, geometry and interstitial media.

Design and optimized analysis of high speed precise machine tool spindles

Upcoming machine tools need to be extremely efficient systems to maintain the needed intellectual performance and stability. The spindle tool system is necessary to optimize which enhances the rigidity of the spindle and in turn produces the cutting stability with higher productivity. Prediction of the dynamic behavior at spindle tool tip is therefore an important criterion for assessing the machining stability of a machine tool at design stage. In this work, a realistic dynamic high-speed spindle /milling tool holder/ tool system model is elaborated on the basis of rotor dynamics predictions. The integrated spindle tool system in analyzed with the Timoshenko beam theory by including the effects of shear and rotary deformation effects. Using the frequency response at the tool tip the corresponding stability lobe diagrams are plotted for the vertical end mill system. Furthermore an optimization study is carried out at design stage for the bearing system and the rotor positions for maximizing the chatter vibration free cutting operation at the desired depth of cuts with precise rotational speeds.It is markedly found that the first mode of vibration had a large impact on the dynamic stability of the system. The parametric studies are conducted such as tool overhang and bearing span and the influence of these on the system dynamics are identified and the corresponding stability lobe diagrams are plotted. It is evidently found that the second mode of the frequency response has critically affected the bearing span and competing lobes are identified. These results are assisted to design a spindle bearing system at the desired machining conditions. A neural network based observer is designed based on the simulation resultsto predict optimum design parameter values.

Design, Development and Installation of Polygon Profile Cutting Attachment for CNC Turning Centre

A polygon cutting attachment has been designed, developed and installed in the existing computer numerical control (CNC) turning center using conceptual design. The working of polygon cutting attachment is checked by performing some machining operation. Thus the CNC turning center becomes multifunctional and flexible for performing turning operations as well as milling operations like polygon profile cutting with presently developed attachment. The attachment is compact, detachable, portable unit and is capable of doing many operations that requires special purpose machines. This powered, variable speed precision tool attachment can be mounted in any position on the turret, table, ram of CNC turning center. Thus with two directional feed table, the attachment becomes complete precision machine tool for CNC turning center.

Design, Development and Installation of Polygon Profile Cutting Attachment for CNC Turning Centre

A polygon cutting attachment has been designed, developed and installed in the existing computer numerical control (CNC) turning center using conceptual design. The working of polygon cutting attachment is checked by performing some machining operation. Thus the CNC turning center becomes multifunctional and flexible for performing turning operations as well as milling operations like polygon profile cutting with presently developed attachment. The attachment is compact, detachable, portable unit and is capable of doing many operations that requires special purpose machines. This powered, variable speed precision tool attachment can be mounted in any position on the turret, table, ram of CNC turning center. Thus with two directional feed table, the attachment becomes complete precision machine tool for CNC turning center.

Profile Measurement Using Confocal Chromatic Probe on Ultrahigh Precision Machine Tool

An on-machine measurement (OMM) system is an effective apparatus for achieving an efficient profile compensation and improving machining conditions in ultrahigh precision machining. Herein, we report a new OMM system with a confocal chromatic probe on a five-axis ultrahigh precision machine tool constructed using a real-time position capturing method. The probe and machine tool positions are captured synchronously using a personal computer to generate profile measurement data. Long- and short-term stability, micro step response, and repeatability tests using an optical flat indicates that the system has a precision of approximately ±10 nm. The profile measurement test using a reference sphere indicates that the precision of the OMM system deteriorated at a large slope angle of ±45°. However, the overall accuracy is estimated to be within ±100 nm at a slope angle within ±15°. The linearity test at various slope angles indicates that the decrease in reflected light from a mirror-like surface deteriorates the performance of the probe.