Milling Chatter Research Articles

Can mode coupling chatter happen in milling?

In milling, two different self-excited vibrations have been reported; regenerative and mode coupling chatter. The regenerative chatter mechanism has been extensively studied and validated with tests whereas mode coupling chatter mechanism was reported a long time ago for threading operations. The presented mode coupling chatter models were based only on current vibrations of the system but not on the delayed vibrations. With the increase in the research carried out on robotic milling operations, the low frequency severe self-excited vibrations at high spindle speeds were claimed to be mode coupling chatter by many researchers. However, the justification of mode coupling chatter mechanism is absent from predicted stability boundaries and a strong evidence distinguishing it from regenerative chatter mechanism is not present. Additionally, mode coupling chatter models applied to milling was based on threading operations and hence they were not capturing the characteristics of intermittent milling process. Therefore, this paper focuses on the diagnosis of mode coupling chatter in robotic milling. Mode coupling chatter principles are applied to milling process considering its intermittent characteristics. The zeroth order approximation for mode coupling chatter mechanism is adapted for milling and extended to multi frequency approximation. Mode coupling chatter stability boundaries are calculated, explored with tests and compared with regenerative chatter stability boundaries. Results show that mode coupling chatter stability boundaries are very low and vaguely dependent on the spindle speed. This contradicts the stability observed in the experimental tests. Hence, it is concluded that mode coupling chatter in milling is not possible, because the assumption of the chip thickness depending only on current vibrations does not apply to milling operations. The novelty of the presented paper is the theoretical and experimental justification that mode coupling chatter is not possible in milling operations.

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.

Feature extraction of milling chatter based on optimized variational mode decomposition and multi-scale permutation entropy

In the milling process, chatter is easy to occur and has a very adverse impact on the quality of the workpiece and the production efficiency. A chatter feature extraction method based on optimized variational mode decomposition (OVMD) and multi-scale permutation entropy (MPE) was proposed to solve the problem that it is difficult to detect the machining chatter state during milling. The methodology presented in this article allows the occurrence of machining chatter to be effectively identified through real-time digital signal processing and analysis. First, in order to solve the problem of variational mode decomposition (VMD) parameter selection, an automatic selection method based on particle swarm optimization (PSO) and the maximum crest factor of the envelope spectrum (CE) was proposed. Then, the decomposed signal was reconstructed based on the energy ratio. In order to solve the problem that the single-scale permutation entropy (PE) cannot detect milling chatter well, the MPE was introduced to detect milling chatter. Finally, experimental verification was carried out, and the MPE of the reconstructed signals at different scales was extracted and analyzed. The results show that using the OVMD algorithm to process the signals can significantly improve the discrimination of MPE. With the increase of the scale factor, the MPE of the milling signals tends to decrease. At the same time, MPE is better than single-scale PE in chatter detection, and the MPE at scale factor of 4 is more conducive to chatter detection.

Effect of minimum friction coefficient on vibration stability in cold rolling mill

Mill chatter is a major restriction in the high-speed rolling of high-strength and thin strips. To maintain mill stability, the friction coefficient must be kept within a certain range. Unfortunately, there is no model to calculate the lower limit of the friction. In this paper, a new model is developed to capture the minimum friction coefficient. This model is proposed based on mixed lubrication theory and monotonicity analysis in the friction curve. The verification results showed that the established model could accurately predict the minimum friction and the friction balance in tandem rolling mills. The model was utilized to design the optimal rolling conditions to expand the stability range of the friction and improve mill vibration stability.

Study the effect of anti-vibration edge length on process stability of milling thin-walled Ti-6Al-4V alloy

Owing to limited rigidity and wall thickness, the machining of thin-walled components leads to chatter, poor surface quality, and low productivity. It is well-acknowledged that end-mill geometry and cutting conditions have a significant influence on the process stability of thin-walled parts. In order to reduce the milling chatter, an anti-vibration milling tool with an anti-vibration edge (60, 90, 120μm) on the flank face is proposed based on the analysis of the process damping effect. The dynamic modeling, numerical computation, and confirmatory experimental analysis are carried out to investigate the effect of anti-vibration edge length on the milling stability of thin-walled titanium-alloy components. The computation results have shown a stable and gradual increase in stable depth-of-cut with the increase of anti-vibration edge length at constant spindle speed. The ultimate stable axial depth increases with the increase of the anti-vibration edge. Besides, the increase of spindle speed reduced the interference between the flank surface of the milling tool and the workpiece due to the decrease of curvature of the vibration mark on the workpiece surface. At higher cutting speed, the relationship between the stability axial depth and anti-vibration edge length reduced. The comparison of computational and experimental results indicate that the anti-vibration edge improved the process damping effect at low cutting speeds, and 120μm anti-vibration edge is optimum to manufacture the flank face of the tools.

The influence of flank lands of end mills on machined surface in milling in the context of chatter

Reliability and cost-effectiveness are the main requirements for aircraft materials and structure components used in manufacturing of aviation engines. This defines the requirements for them. The majority of components are thin-walled and made of hard-to-machine materials: nickel and titanium alloys, heat-resistant steels. The use of such materials places restrictions on the use of certain cutting modes. During rough milling and semi-finish milling with end-mill cutters chatter occur. The vibrations deteriorate the machined surface of engine parts, tool life decreases and machine units are worn out. Different process technologies and constructive features of tools are used to decrease the intensity of chatter. The use of end mills having lands has yielded mixed results. The influence of land usage on surface condition and decrease of chatter in up-milling and down milling has been studied. The mechanism of influence on machined surface and chatter in up-milling and down milling has been determined. At the experimental stand studies were carried out on its effect on changes in the laws of motion of detail during the cutting process. It has been shown that in up-milling and down milling, a land fl = 0.05 mm wide on the rear surface along the cutting tooth reduces the intensity of chatter has been shown. The results can be used to select the feed direction to reduce the intensity of chatter when milling thin-walled parts with end mills with a land on the rear surface along the cutting edges.

Chatter reliability prediction of side milling blisk

During the blisk side milling, the blade is thin and the tool suspension length is large, which is easy to occur milling system chatter. The wavy surface left by chatter has great effect on the surface roughness and service performance of the aero-engine blisk. To accurately predict the stability of the blisk side milling, the influence of random variables on the machining stability was considered. In this paper, the chatter reliability model of the blisk side milling system was established using the first-order second-moment method. The model takes structural parameters and spindle speed as random variables and chatter frequency as intermediate variables. The chatter reliability model was used to draw the reliability lobe diagram, which can be used to divide the machining reliability area. The effectiveness of this method was verified by experiments and compared with Monte Carlo method. The validation results showed that the reliability lobe diagram can be used to determine the stability probability prediction of blisk side milling and can replace the traditional stability lobe diagram.

A kMap optimized VMD-SVM model for milling chatter detection with an industrial robot

Industrial robots play an important role in the milling of large complex parts. However, the robot is less rigid and prone to vibration-related problems; chatter, which affects machining quality and efficiency, is more complex and difficult to monitor. In this paper, a variational mode decomposition-support vector machine (VMD-SVM) model based on information entropy (IE) is built to detect chatter in robotic milling. Significantly, the vibration signals are classified into four states for the first time: stable, transition, regular chatter, and irregular chatter. To improve the accuracy of the identification model based on VMD-SVM, a novel hyper-parameter optimization strategy—the kMap method—is proposed in this paper for optimizing three-dimensional hyper-parameters in the VMD-SVM model. The hyper-parameters of VMD-SVM are jointly optimized by the kMap method, with constant step sizes. As an improved grid search (GS), kMap reduces the operation time to the same order of magnitude as the heuristic algorithm (HA) [comprising particle swarm optimization (PSO) and genetic algorithm (GA)]. The VMD-SVM model with the hyper-parameters optimized by kMap exhibits higher accuracy and better stability than the hyper-parameters optimized by PSO and GA. The results of the validation experiments show that the kMap-optimized identification model is effective in industrial robotic milling.

Prediction and suppression of chatter in milling of structures with low-rigidity: A review

Milling is widely used to machine the structures with low-rigidity in astronautic and aeronautic industries, while chatter vibration, which is a great limitation and a serious problem, is easy to occur in this kind of process due to the weak stiffness of the structures. To solve the machining problems caused by chatter, prediction and suppression are two important methods that are commonly used by researchers and industry engineers. This article reviews the study progresses on the prediction and suppression of the chatter occurring in milling process of the low-rigidity structure. The dynamic model, acquisition of dynamic parameters, and suppression techniques are introduced. Besides, the problems and the outlooks of the future coming research are also given in the conclusions.

A short review on milling dynamics in low-stiffness cutting conditions: Modeling and analysis

The dynamic responses of milling system change the ideal trajectories of cutting teeth and therefore plays a critical role in determining the machining accuracy. The amplitude of cutting vibrations could reach tens of or even hundreds of micrometers in low-stiffness cutting conditions, for example, when milling thin-walled parts and/or using slender tools. Usually, moderate cutting parameters are utilized to avoid excessive cutting loads, strong milling chatter or large dynamic deflections, which however, significantly lowers the productivity. In spite of decades of study, it is still a challenge to accurately model, efficiently analyze, reliably monitor and precisely control the dynamic milling process in low-stiffness cutting conditions. In this paper, the recent advances and research challenges on dynamics modeling and response analysis are briefly reviewed.

Research on Fuzzy Control for High Speed Milling Chatter of Intelligent Spindle

Research on Fuzzy Control for High Speed Milling Chatter of Intelligent Spindle

Verification of pattern formation mechanism using voxel model and estimation accuracy for inverse analysis of vibration phenomenon using two-dimensional discrete Fourier transform of end mill chatter mark

Verification of pattern formation mechanism using voxel model and estimation accuracy for inverse analysis of vibration phenomenon using two-dimensional discrete Fourier transform of end mill chatter mark

Active suppression of milling chatter based on LQR-ANFIS

Chatter is a typical self-excited and undesired vibration in the milling process, leading to poor surface finishes and limiting the machining efficiency, and hence needs to be suppressed. In this paper, an active chatter suppression method based on linear-quadratic regulator (LQR) and adaptive network-based fuzzy inference system (ANFIS) is presented to mitigate the milling chatter. Firstly, the dynamics of milling process with two-degree-of-freedom considering the active control force is discretized to facilitate the design of the LQR-based controller. In addition, the particle swarm optimization (PSO) algorithm is used to determine the weighting matrix preferentially to ensure the optimal performance of designed controller. Then, considering the time-varying cutting parameters in the practical milling process, the ANFIS is introduced to obtain the gain matrix of the controller directly, with which the online chatter suppression can be achieved. Simulation results show that the LQR-ANFIS-based controller can significantly improve the stability boundary of milling process.

Correction to: EEMD-based online milling chatter detection by fractal dimension and power spectral entropy

Correction to: EEMD-based online milling chatter detection by fractal dimension and power spectral entropy

Robust Chatter Stability Prediction of the Milling Process considering Uncertain Machining Positions

Milling stability is a function of the tool point frequency response functions (FRFs), which vary with the movements of the moving parts within the whole machine tool work volume. The position-dependent tool point FRFs result in uncertain prediction of the stability lobe diagram (SLD) for chatter-free machining parameter selection. Taking the variations of modal parameters to represent the variations of tool point FRFs, this paper introduces the edge theorem to predict the robust milling chatter stability. The application of the edge theorem requires the minimum and maximum modal parameters within the machining space defined by the machining position and machining allowance information. Then, radial basis function artificial neural networks (RBFANNs) are used to predict the position-dependent modal parameters in X and Y directions based on the sample information of machining positions and related modal parameters at the tool point. Moreover, sample machining spaces are determined based on the aforementioned sample positions, and the trained RBFANNs are used to obtain corresponding sample extreme modal parameters. On this basis, RBFANNs for predicting the position and machining allowance-dependent extreme modal parameters can also be trained, and they are combined with the edge theorem and zero exclusion condition to calculate robust pairs of the spindle speed (n) and limiting axial cutting depth (aplim) and then plot the robust SLD (RSLD). A case study was performed on a real three-axial vertical machining center, and the plotted RSLD considering position variations was compared with the traditional SLD. Results of the chatter tests show that the RSLD can provide more reliable (ap, n) pairs to guarantee the milling stability, validating the feasibility of the proposed robust milling chatter stability prediction method.

Prediction and analysis of cold rolling mill vibration based on a data-driven method

Mill chatter is one of the most common problems in cold rolling. Thus, it is important to investigate the mill chatter phenomenon to ensure a high-speed and stable rolling process. The traditional mill chatter mechanism model cannot meet the monitoring and rapid diagnosis needs of the rolling process in the field. In this paper, a data-driven mill vibration analysis method is proposed. The main objective of this study was to develop a mill vibration monitoring method and an intelligent algorithm for mill chatter early warning. Rolling experiments showed that the proposed monitoring method could be a promising and effective technique for assessing the chatter phenomenon. The mill vibration acceleration amplitude prediction performance of a support vector regression, neural-network-based method, and extreme gradient boosting method were evaluated. The results proved that the prediction performances of the proposed extreme gradient boosting method were highly reliable with the highest determination coefficient value of 0.779, lowest mean absolute percentage error of 9.7%, and better forecast robustness under all of the dataset ratios. Meanwhile, the contribution rates of the variables on the mill vibrations were investigated, and results showed that an effective way to eliminate the mill chatter was to control the rolling speed, cumulative rolling strip length, tension and roll radius.

Effect of controllable magnetic field-induced MRF solidification on chatter suppression of thin-walled parts

Aiming at solving the chattering problem of thin-walled parts, magnetorheological fluid (MRF) was used as phase-change clamping material to study the influence of MRF excitation clamping on the modal parameters of thin-walled parts. In this paper, to clamp the cantilever thin-walled parts firmly and stably, a strong and uniform magnetic field was achieved by designing a yoke-type configuration first. Next, to quantify the clamping effect of MRF, its squeeze stress-strain curves were tested and corresponding elastic squeeze parameters in pre-yield stage were applied on the on thin-walled parts. Then, the influence of MRF clamping on the workpiece mode was researched from simulating results and experimental results. After that, to validate the clamping effect of MRF fixture, reasonable cutting parameters on the thin-walled part were chosen according to the milling chatter stability lobes. By comparing surface roughness, surface topography, and chip type, the clamping effect of MRF fixture is validated. The results indicate that MRF flexible fixture can obviously restrain the machining vibration in milling process and contribute to suppress the machining vibration of thin-walled parts.

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.

MaxEnt feature-based reliability model method for real-time detection of early chatter in high-speed milling

Real-time detection of early chatter is a vital strategy to improve machining quality and material removal rate in the high-speed milling processes. This paper proposes a maximum entropy (MaxEnt) feature-based reliability model method for real-time detection of early chatter based on multiple sampling per revolution (MSPR) technique and second-order reliability method (SORM). To enhance the detection reliability, the MSPR is used to acquire multiple sets of once-per-revolution sampled data (i.e., MSPR data) and to overcome the shortcoming of the once-per-revolution sampling. The proposed MaxEnt feature-based reliability model method solves the issue of the real-time detection of early chatter while ensuring its reliability. The failure hazard function (FHF) is estimated as a chatter indicator by using the SORM with the MaxEnt feature. The proposed method consists of five steps. First, set the prior parameters. Then collect data by using the MSPR technique. Next, calculate a set of the standard deviation of the data collected as a chatter feature and estimate the chatter indicator FHF by applying the SORM with the MaxEnt feature. Finally, implement the real-time detection of early chatter based on the estimated chatter indicator FHF and the threshold FHF0. The proposed method is applied to the high-speed milling process. Two examples prove that the proposed method can detect two kinds of early chatter: the early-stage of a severe chatter and the slightly intolerable chatter.

Five-axis flank milling stability prediction by considering the tool-workpiece interactions and speed effect

Chatter is one of the challenging topics in the field of metal cutting. The dynamic characteristics of five-axis milling system are complex and variable. Especially in high-speed milling process, the influence of the tool-workpiece interactions and speed effect on milling stability is more obvious. It is necessary to investigate the influence of various interaction effects on milling stability. In this paper, the dynamical model of spindle system was established, and then the model was applied to investigate the influence of gyroscopic effect and centrifugal force on the dynamical characteristics of the tool tip. In order to solve the chatter problem of five-axis flank milling, the extended dynamical model of five-axis flank milling which considers the tool-workpiece interactions and speed effect was established. Based on the established milling dynamical model, the influence mechanism of the spindle system-tool-workpiece interaction effects on five-axis flank milling stability was investigated. The stability lobe diagrams of five-axis flank milling which contains the tool-workpiece interactions and speed effect can be obtained. Experimental results show that the proposed five-axis flank milling dynamical model can predict the milling state more reliable than the traditional ones. The research results are of great significance in preventing five-axis flank milling chatter.