Tool Spindle System Research Articles

An effective investigation of chatter prediction system on Al6061 alloy in an end milling process

Visual examination of the surface topography, in conjunction with the other sensors, may confirm the existence of chatter. Online chatter detection during real machining operations is possible with the use of sensors, and the presence of noise in their output and restricted bandwidth are the major drawbacks of these sensors. Productivity drops and manufacturing costs go up when there is a lot of chatter in the machining process. In the present paper, an integrated spindle tool system is modeled using finite element method with Timoshenko beam theory including rotational and shear deformation effects. To maximize the average stable depth of cut in an end milling process while simultaneously minimizing the chatter vibration levels, real time and offline strategies have been investigated. Machining experiments performed on Al6061-alloy specimens provide an empirical confirmation of the stability boundaries. The surface topography methods such as scanning electron microscope (SEM) and optical microscope images along with vibration levels are considered, to identify chatter marks under various machining conditions, which helps to assure cutting process stability. Stability lobe diagrams are plotted with these derived conditions and observed at an incremental level in the axial depths of the cut. The methodology shown in this paper improves the machining stability of the end milling with the reduction in the tool tip vibrations.

Development of a Digital Model for Predicting the Variation in Bearing Preload and Dynamic Characteristics of a Milling Spindle under Thermal Effects

The spindle tool is an important module of the machine tool. Its dynamic characteristics directly affect the machining performance, but it could also be affected by thermal deformation and bearing preload. However, it is difficult to detect the change in the bearing preload through sensory instruments. Therefore, this study aimed to establish a digital thermal–mechanical model to investigate the thermal-induced effects on the spindle tool system. The technologies involved include the following: Run-in experiments of the milling spindle at different speeds, the establishment of the thermal–mechanical model, identification of the thermal parameters, and prediction of the thermal-induced preload of bearings in the spindle. The speed-dependent thermal parameters were identified from thermal analysis through comparisons with transient temperature history, which were further used to model the thermal effects on the bearing preload and dynamic compliance of the milling spindle under different operating speeds. Current results of thermal–mechanical analysis also indicate that the internal temperature of the bearing can reach 40 °C, and the thermal elongation of the spindle tool is about 27 µm. At the steady state temperature of 15,000 rpm, the bearing preload is reduced by 40%, which yields a decrease in the bearing rigidity by approximately 16%. This, in turn, increases the dynamic compliance of the spindle tool by 22%. Comparisons of the experimental measurements and modeling data show that the variation in bearing preload substantially affects the modal frequency and stiffness of the spindle. These findings demonstrated that the proposed digital spindle model accurately mirrors real spindle characteristics, offering a foundation for monitoring performance changes and refining design, especially in bearing configuration and cooling systems.

Stability prediction for robotic milling based on tool tip frequency response prediction by considering the interface stiffness of spindle-tool system

The change of tool tip frequency response caused by the posture dependence of robot dynamic is one of the key problems that make it difficult to accurately predict the milling stability of robot. In this paper, a tool tip frequency response prediction method considering the interface stiffness characteristics of spindle-tool system is proposed for stability prediction of robotic milling under the condition of posture variation. Firstly, the interface stiffness models of spindle-toolholder, toolholder-spring clip and spring clip-tool are established based on Yoshimura's unit area method. Then, The dynamics model for the robot body and the interface stiffness models for spindle-tool system are imported into the finite element analysis model of the spindle system, so that the prediction of the tool tip frequency response is realized by harmonic response analysis. Compared with the experimental results, the maximum error of the natural frequency was not more than 2 %, and the maximum error of the amplitude was not more than 12 %. Finally, the 2 DOF robot milling stability prediction model is established. Then the robot milling chatter is predicted considering redundant degrees of freedom from the perspective of regenerative chatter prediction theory, and the accuracy of prediction results is verified by milling experiment.

Prediction of the Waviness Error in Ultra-Precision Fly Cutting Using the Direct Integration Method

Abstract Fly cutting is widely used in manufacturing of large-scale, high-precision optical components. However, the discontinuity of fly cutting machining leads to significant relative vibrations between the tool and the workpiece. The cutting process generates periodic waves along the cutting direction, which will deteriorate the wavefront characteristics of optical components. Based on the machining dynamics, this paper proposes a direct integration method to predict the waviness error of the machined surface. The cutting force model of fly cutting is established. The multi-mode characteristics of the spindle-tool system are measured by the experimental method. Then, the influence of uncertainties on the calculation results is analyzed by the variance-based sensitivity analysis method. Finally, the plane cutting experiment verifies that the direct integration method effectively predicts the waviness error and its variation trend, and the waviness prediction research is important for optimization of the machining parameters.

Active control of milling chatter considering the coupling effect of spindle-tool and workpiece systems

Chatter occurred in the machining process can seriously limit the processing efficiency and reduce the surface quality of the machined workpiece, which urgently needs to be controlled. Aiming at milling of flexible workpieces with similar characteristics to the spindle-tool system, two active chatter control strategies are proposed in this work. Firstly, considering the coupling effect of the spindle-tool system and the workpiece system, the milling force is developed based on the regenerative effect. And the 3D stability lobe diagram along the tool path is constructed. Then, an active chatter control structure is designed by integrating piezoelectric actuators and displacement sensors into the spindle-tool-workpiece (STW) system. Next, based on the developed milling force and active control structure, two chatter control strategies with different feedback signals are proposed using the model predictive control method. Finally, numerical simulations and milling experiments are carried out under different cutting conditions. The results show that milling chatter of the STW system can be effectively controlled by the proposed strategies. The maximum material removal rate is also significantly improved.

Mitigation of chatter in thin-wall milling by using double-side support device

This article develops a new method to mitigate chatter vibrations in the thin-wall milling of the structures with half-opened side walls through designing a supplementary device, which can provide double-side support to the weakly rigid positions between cutter and workpiece. It aims to improve the stiffness and damping responses of the side walls without the need to consider the limitation of the workpiece’s geometrical configuration. That is, it is suitable for both the flat and the curved shapes. The typical structural characteristic of the device lies in that as the cutting continues, the supporting positions can be easily adjusted up and down along the axial direction to meet the instantaneous chatter mitigation requirement. Dynamic models of both the curved thin-wall milling process and the workpiece with the supplementary support device are derived by integrating the milling mechanics with the receptance coupling substructure analysis. The in-process modal parameters of the workpiece with the support device, i.e., natural frequency and modal shape, are calculated by comprehensively considering the removal of material and the influence of the supporting position change. Finally, a method that combines the derived models with the dynamic response of the spindle-tool system is used to predict the stability lobe diagrams (SLDs), with which chatter vibrations can be well avoided by reasonably selecting the cutting parameters. A series of thin-wall milling experiments are carried out on typical curved plates to validate the effectiveness of the designed support device together with the proposed methods for mitigating chatter vibrations.

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.

Geodesic Distance Field-Based Process Planning for Five-Axis Machining of Complicated Parts

Abstract A critical task in multi-pass process planning for the five-axis machining of complicated parts is to determine the intermediate surfaces for rough machining. Traditionally, the intermediate surfaces are simply parallel Z-level planes, and the machining is of the simplest three-axis type. However, for complicated parts, this so-called Z-level method lacks flexibility and causes isolated islands on layers, which require extraneous air movements by the tool. Moreover, the in-process workpiece machined according to the Z-level method suffers from the staircase effect, which often induces unstable dynamic problems on the tool-spindle system. In this paper, we propose a new method of planning a five-axis machining process for a complicated freeform solid part. In our method, the intermediate surfaces are no longer planar but curved, and they are intrinsically influenced by the convex hull of the part. The powerful algebraic tool of geodesic distance field is utilized to generate the desired intermediate surfaces, for which collision-free five-axis machining tool paths are then planned. In addition, we propose a novel idea of alternating between the roughing and finishing machining operations, which helps improve the stiffness of the in-process workpiece. Ample physical cutting experiments are performed, and the experimental results convincingly confirm the advantages of our method.

Additively manufactured, particle-filled damping structures with magnetorheological fluids

To this day, undesired vibrations are a common problem in metal-cutting machine tools. Due to the development of lightweight structures and ever more rigid as well as low-friction machine elements, machine tools have increasingly fewer damping properties so that they are more susceptible to vibrations. The use of special particles and suspensions such as magnetorheological fluid leads to good damping properties. By integrating specially designed, additively manufactured structures in combination with such particles, it is possible to change the dynamic properties of a mechanical system. This paper presents the results of our study into the application of additively manufactured structures in combination with different particles, based on the example of a spindle-tool system. It showed that the structures and particles reduce the dynamic response and shift the natural frequencies.

Chatter Stability Prediction Method of the Spindle-Tool Holder-Tool System with Interface Contact Characteristics

To predict chatter stability and suppress chatter vibration, a chatter stability prediction method for the spindle-tool holder-tool system with interface contact characteristics is constructed. A five-DOF model is constructed to determine the spindle-bearing interface dynamic contact stiffness considering the coupling effect of spindle and bearing. A fractal multiscale tool holder-spindle interface dynamic stiffness model is proposed considering time-varying cutting force. The fractal dimensions and cutting force coefficient parameters are identified from the power spectrum experiments and cutting force tests. The cutting force is solved according to the milling stability model. Dynamic model of the spindle-tool holder-tool system is found by the finite element method. Based on extended Floquet theory, chatter stability of the spindle system is studied. Effect of interface parameters, radial cutting depth, and feed rate on milling stability is researched. Milling force tests and milling stability tests are performed in order to verify the reliability of the method. Results find that the increase of front bearing preload and spindle-tool holder’s interference fit are effective to improve the milling stability. The optimal feed rate and the critical radial cutting depth are found. The model proposed in this paper can be used as an instruction for predicting and suppressing the chatter vibration and optimizing cutting parameters and also is helpful for designing the spindle-tool holder-tool system.

Chatter analysis and mitigation of milling of the pocket-shaped thin-walled workpieces with viscous fluid

This article presents a theoretical method to analyze the dynamic behavior of the milling process of the pocket-shaped thin-walled workpieces, which are filled with viscous fluid to suppress the chatter vibrations. Dynamic models of both the spindle-tool system and the pocket-shaped thin-walled workpiece with the viscous fluid are derived by extending the principles of the fluid-structure interaction dynamics theory and structural mechanics. The in-process dynamical parameters of the tool and the workpiece, i.e. natural frequency and modal shape, are solved by comprehensively integrating the effects of the viscous fluid, material removals, and tool position changes. Based on the built models, a method for analyzing the machining stability of this kind of workpieces after using the viscous fluid in the milling process is carried out and the avoidance principle of chatter vibrations is established by reasonably selecting the cutting parameters. A series of simulation and experimental tests are conducted on a typical pocket-shaped thin-walled workpiece to verify the reliability and effectiveness of the proposed methods for the suppression of chatter during the whole milling process.

Identification of milling chatter based on a novel frequency-domain search algorithm

Chatter is a kind of self-excited vibration, which will result in very poor quality and dimensional accuracy on the machined surface, even a harmful effect on machining operation. A simple, reliable, and accurate chatter identification algorithm is crucial for taking control strategy before it is fully developed. This paper proposes a novel frequency-domain search (FDS) algorithm to identify the chatter during milling. An identification feature based on vibration base frequency is extracted according to the FDS algorithm, where the complicated signal processing algorithms are not needed before feature extraction. Compared with most of the existing identification features, the introduced feature does not need to set thresholds according to different machining conditions. Meanwhile, the feature extraction only needs a small amount of data to guarantee the timeliness of identification. Hammer test and milling experiments with various cutting parameters are carried out, and both force signal and vibration signal in the experiments are utilized to validate the effectiveness of the proposed algorithm. The results show that the proposed algorithm can identify the milling chatter accurately, whether using force signal or vibration signal, even slight chatter in the initial machining stage can be identified. Furthermore, the research reveals that dominant chatter frequencies appear around the natural frequency of the spindle-tool system but do not exactly equal to its natural frequency. The chatter frequencies are found to be determined by the combination of natural characteristics of the system and cutting conditions.

Optimal design of spindle-tool system for improving the dynamic stability in end-milling process

This paper presents an optimum design approach of a spindle-tool system to improvise the dynamic stability of end-milling. Initially, the tool-tip frequency response function is obtained by analyzing the spindle-tool assembly with the finite element model. The chatter-free regions are maximized using an optimization methodology by considering the spindle and tool parameters as design variables. A simulated experimental dynamic data consisting of the average stable depth of cut is obtained for different combinations of design variables by the method of design of experiments (DOE) and analysis of variance technique is applied to find the influence of design parameters on the outputs. Based on the obtained results, the data is generalized with the help of a neural network model that works as an estimator of the average stable depths for the optimization module. The average stable depth of cut over a range of operating speeds is maximized by selecting optimal tool and spindle parameters.

Stiffness modeling, identification, and measuring of a rotating spindle

The stiffness of a spindle at high speeds has a significant effect on the quality of the cutting surface and the machining accuracy. However, the spindle stiffness is difficult to be detected directly when the spindle is rotating, and the measured stiffness values are usually coupled with other parts of the spindle–tool system (such as toolholder, spindle–toolholder joint, tool). This paper presents a comprehensive method to deal with the stiffness modeling, identification, and measuring of a rotating spindle. Based on the deflection equation and the principle of superposition, the stiffness model is derived, for a spindle–tool system including a spindle, a specially manufactured toolholder, and a spindle–toolholder joint. A three-step identification algorithm is proposed to decouple and identify the actual spindle stiffness value. First, when the spindle is static, the stiffness values of the shaft, toolholder, and joint are obtained by using the least-squares method. Second, when the spindle is rotating, the stiffness values of the rear bearings and front bearings are identified based on the spindle error analysis method. Third, the stiffness values of the spindle under different rotating conditions are calculated based on the identification results from the previous two steps. Furthermore, the stiffness model and identification algorithm are verified experimentally on an instrumented spindle. The static stiffness value of the same spindle is also measured and compared with the stiffness value under rotating conditions subsequently. This work is useful and can be utilized as a guide for spindle stiffness testing and spindle performance evaluation to spindle manufacturers.

Chatter Stability of Micro-Milling by Considering the Centrifugal Force and Gyroscopic Effect of the Spindle

Abstract In the micro-milling process, the minimization of tool chatter is critical for good surface finish quality. The analysis of chatter requires an understanding of the milling tool as well as the dynamics of milling system structure. Frequency response function (FRF) at the micro-milling tool point reflects dynamic behavior of the whole micro-milling machine–spindle–tool system. However, the tool point FRF of micro-milling cannot be obtained directly through the hammering test. To solve the problem, the authors get the FRF of the spindle system based on the rotating Timoshenko beam theory and the receptance coupling substructure analysis (RCSA), and the bearing characteristics are added into the spindle model through structural modification. Then, the centrifugal force and gyroscopic effect caused by the high-speed rotation of the micro-milling spindle are considered to better simulate the real scenario and increase the accuracy of modal parameters. The method has general usage and can be applied to all the micro-milling tools under which only the spindle dimension, bearing characteristics, and contact parameters need to be changed.

Prediction of the Frequency Response Function of a Tool Holder-Tool Assembly Based on Receptance Coupling Method

Regenerative chatter has a fatal influence on machine performance in high-speed milling process. Basically, machine condition without chattering can be selected from the stability lobes diagram, which is estimated from the tool point frequency response function (FRF). However, measurements of the tool point FRF would be a complicated and time-consuming task with less efficiency. Therefore prediction of the tool point FRF is of importance for further calculation of the machining stability. This study employed the receptance coupling analysis method to predict the FRF of a tool holder-tool module, which is normally composed of substructures, tool holder and cutter with different length. In this study, the angular components of FRFs of the substructures required for coupling operation were predicted by finite element analysis, apart from the translational components measured by vibration experiments. Using this method, the effects of the overhang length of the cutter on the dynamic characteristics have been proven and successfully verified by the experimental measurements. The proposed method can be an effective way to accurately predict the dynamic behavior of the spindle tool system with different tool holder-tool modules.

Prediction of cutting force in milling process using vibration signals of machine tool

This paper presents a method based on the theory of Kalman filter (KF) to predict cutting force through vibration signals in milling process. The acceleration signal and displacement signal of the machine tool spindle vibration are acquired and used for the prediction of the cutting force. In actual machining process, different cutting parameters lead to different time and frequency domain characteristics of cutting force. As system output, the vibration of machine tool is influenced by the input signal of force and machine tool dynamic characteristics. The bandwidth of the transfer function between the cutting force and acceleration should be considered when adopting indirect cutting force measurement method by using vibration sensors. Because of the influence of structural modes of the spindle-tool system, the measurement bandwidth is limited and as a result, it leads to the distortion of measurements containing high frequencies. Consequently, it is necessary to compensate the disturbances caused by structural modes and the bandwidth of the system should be increased properly according to machining conditions. In order to implement the compensating strategy for the measurement, a Kalman filter is designed for the test system. Before the construction of the filter, the frequency response functions (FRFs) of the spindle-tool system are tested through experimental modal analysis (EMA). With the implementation of the compensation, the bandwidth of the testing system is increased significantly. Besides, a strong tracking filter (STF) is designed and applied to the system to improve filter performance. Application of the proposed method has been demonstrated experimentally through cutting tests under different experimental conditions on a three-axis vertical machining center.

Bayesian Degradation Analysis With Inverse Gaussian Process Models Under Time-Varying Degradation Rates

Degradation observations of modern engineering systems, such as manufacturing systems, turbine engines, and high-speed trains, often demonstrate various patterns of time-varying degradation rates. General degradation process models are mainly introduced for constant degradation rates, which cannot be used for time-varying situations. Moreover, the issue of sparse degradation observations and the problem of evolving degradation observations both are practical challenges for the degradation analysis of modern engineering systems. In this paper, parametric inverse Gaussian process models are proposed to model degradation processes with constant, monotonic, and S-shaped degradation rates, where physical meaning of model parameters for time-varying degradation rates is highlighted. Random effects are incorporated into the degradation process models to model the unit-to-unit variability within product population. A general Bayesian framework is extended to deal with the degradation analysis of sparse degradation observations and evolving observations. An illustrative example derived from the reliability analysis of a heavy-duty machine tool's spindle system is presented, which is characterized as the degradation analysis of sparse degradation observations and evolving observations under time-varying degradation rates.

Stability-based selection of cutting parameters to increase material removal rate in high-speed machining process

The reasonable selection of cutting parameters is of great significance to improve the productivity in high-speed machining process. In this article, a stability-based selection method of cutting parameters is proposed to increase material removal rate in high-speed machining process. First, the coupled dynamics of the high-speed spindle system and machining process is modeled. Then, the interaction mechanism between the spindle-tool system and the cutting process is investigated. Based on the process stability and surface quality of workpiece, a cutting parameter selection method is proposed from the perspective of machining stability. In order to select reasonable spindle speed and depth of cut, the lower bound of chatter stability lobe diagram and surface finish are taken as constraints, and the maximum material removal rate is set as the target. The proposed method is applied to the machining of the front face of a gearbox cover, which is made of Aluminum-7050. The axial depth of cut and spindle speed are chosen reasonably with the increase in machining efficiency by about 133%.

Leveraging Degradation Testing and Condition Monitoring for Field Reliability Analysis With Time-Varying Operating Missions

Traditionally, degradation testing and condition monitoring are used separately to investigate field reliability. Barriers are naturally formed between these two types of methods due to condition-discrepancies between lab testing and field monitoring, as well as time-varying missions among product population groups. In this paper, a joint framework for field reliability analysis is presented by integrating degradation testing data as well as mission operating information with condition monitoring observations. A coherent modeling strategy is introduced for the information integration by gradually adopting random effects, dynamic covariates, and marker processes into a baseline stochastic degradation model. In detail, random effects are introduced to cope with the inherent unit-to-unit variation. Dynamic covariates are adopted to deal with the external condition heterogeneity. Marker processes are used to account for the time-varying missions. To facilitate information integration and reliability analysis, the Bayesian method is used to implement parameter estimation and degradation analysis. The reliability assessment of products' populations, degradation prediction, and residual life prediction of individual products are investigated. Finally, an illustrative example for field degradation analysis of oil debris in a lubrication system of a machine tool's spindle system is presented. The effectiveness of information integration and the capability of degradation inference are demonstrated through this example.