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Chatter has always been a detrimental problem restricting the improvement of surface quality and processing efficiency in machining processes. Chatter detection is an essential approach to prevent these harmful effects, which aims to identify chatter occurrence at the early stage. Energy entropic methods explain chatter from randomness perspective of energy distribution and are often applied to detect chatter in machining processes. However, the energy of the milling system at the chatter frequency increase slowly at the onset of chatter, which lead to that energy entropy is sometimes challenging to identify weak chatter. In this paper, a new method based on combination of wavelet packet energy entropy and energy ratio is proposed to monitor chatter. By detecting the energy ratio of chatter frequency band, it is feasible to set a threshold to represent the different milling states and can accurately detect weak chatter. The proposed approach is assessed by using preliminary numerical simulation and several milling experiments, and the results demonstrate that the proposed method can effectively detect chatter. [ABSTRACT FROM AUTHOR]

In this paper, a novel, separable two-degrees-of-freedom stage with high-precision motion and resolution is proposed for the application of vibration-assisted micromilling. A separable design was realized on the basis of the detachable structure of the platform. Flexible stages with different dimensions and types can be utilized in the devices. A circular-fillet hinge is selected as the flexible unit with a parallel structure to realize output decoupling and reduce the coupling error between the two vibration directions. Analytical modeling is conducted to explore the static and dynamic characteristics of the stage. Results reveal a good agreement with the finite element simulation result. A series of experiments were conducted to assess the static and dynamic performances of the flexible stage, encompassing tests such as amplitude response, motion trajectory, and coupling trajectory. The results of these tests revealed that the designed vibration-assisted system exhibits precise movement capabilities.Highlights: A novel separable vibration-assisted stage with high-precision motion and resolution is proposed, in which flexible stages with different dimensions and sizes can be utilized. The test results show that the coupling error of the 1D stage is much lower than the 2D stage in one-direction vibration. The test results show that the coupling error of the 1D stage is much lower than the 2D stage in one-direction vibration. [ABSTRACT FROM AUTHOR]

An efficient stability analysis contributes to the improvement of machining stability and chatter suppression. First, this paper presents three chatter detection approaches that were developed on the application of wavelet transforms. Second, the feasibility of the methods for chatter detection is verified by combining numerical simulations and experimental research. Finally, the recognition performance of the three methods is compared. The analysis results indicate that the proposed three methods can distinguish different machining states. The p-leader multifractal method (PLMM) provides the best recognition performance but takes the longest time, the wavelet leader multifractal method (WLMM) comes second, and the wavelet packet method (WPM) is the worst but takes the shortest amount of time. Therefore, the PLMM can be used for identifying signals with high accuracy requirements, whereas the WLMM or WPM can be used otherwise.Highlights: Three methods for judging the stability of micro milling process are proposed by using wavelet packet method (WPM), wavelet leaders multifractal method (WLMM) and p-leader multifractal method (PLMM). The feasibility of WPD, WLMM, and PLMM in stability analysis was preliminarily verified through numerical simulation. The recognition performance of WPD, WLMM, and PLMM for chatter detection is compared. [ABSTRACT FROM AUTHOR]

Among the diverse challenges in machining processes, chatter has a significant detrimental effect on surface quality and tool life, and it is a major limitation factor in achieving higher material removal rate. Early detection of chatter occurrence is considered a key element in the milling process automation. Online detection of chatter onset has been continually investigated over several decades, along with the development of new signal processing and machining condition classification approaches. This paper presents a review of the literature on chatter detection in milling, providing a comprehensive analysis of the reported methods for sensing and testing parameter design, signal processing and various features proposed as chatter indicators. It discusses data-driven approaches, including the use of different techniques in the time–frequency domain, feature extraction, and machining condition classification. The review outlines the potential of using multiple sensors and information fusion with machine learning. To conclude, research trends, challenges and future perspectives are presented, with the recommendation to study the tool wear effects, and chatter detection at dissimilar milling conditions, while utilization of considerable large datasets—Big Data—under the Industry 4.0 framework and the development of machining Digital Twin capable of real-time chatter detection are considered as key enabling technologies for intelligent manufacturing. [ABSTRACT FROM AUTHOR]

Chatter in machining results in poor workpiece surface quality and short tool life. An accurate and reliable chatter detection method is needed before its complete development. This paper applies a novel p-leader multifractal formalism for chatter detection in milling processes. This novel formalism can discover internal singularities rising on unstable signals due to chatter without prior knowledge of the natural frequencies of the machining system. The p-leader multifractal features are selected by using a multivariate filter method for feature selection, and verified by both numerical simulations and experimental studies with detailed parameter selection discussions when applying this formalism. The proposed method is assessed in terms of their dynamic monitoring abilities and classification accuracies under wide cutting conditions. The results show that the multifractal features can successfully detect chatter with high accuracies and short computation time. For further verification, the proposed method is compared with two commonly-used methods, which indicates that the proposed method gives better classification accuracies, especially when identifying unstable tests. [ABSTRACT FROM AUTHOR]

Understanding the influences of drilling parameters on machinability characteristics of NFRCs is of value to both academia and manufacturing industries. The present work investigates drilling-induced delamination and hole quality of fully biodegradable flax/poly(lactic acid) composites in response to cutting speed, feed rate, drill diameter, and drill material. Among various types of drilling-induced damages, exit-ply delamination is found to be the most destructive damage and cutting thrust force is identified as the main reason. The experimental results revealed that thrust force is highly dependent on drilling parameters where feed rate and drill material were found to be the most influential parameter on it. The choice of drill bit in terms of diameter and material has a considerable effect on the machinability. Drilling with HSS drills resulted in nearly 60% lower thrust force and better hole quality compared to that with carbide drills. While the size of delamination damage in the samples drilled at the lowest feed (0.02 mm/rev) sounds to be unrelated to cutting forces, the overall trend confirms that decreasing the value of thrust force leads to lowering delamination damages. Hence, an effective strategy in avoiding such undesirable defects is calculating the critical thrust force below which delamination is negligible. An analytical model is developed based on the theory of virtual work to determine the critical thrust force at delamination onset. Through validating with experimental data, the proposed model agrees better with a more accurate prediction than existing models. [ABSTRACT FROM AUTHOR]

This paper presents an experimental study on abrasive waterjet (AWJ) drilling of Inconel 718 and AISI 1040 steel, with an aim to understand the AWJ hole drilling performance and to investigate the process monitoring strategy by using acoustic emission (AE). In the experiments, pressure levels were set from 200 to 350 MPa at intervals of 50 MPa, and drilling time between 5 and 30 s at intervals of 5 s. It is found that the hole depth increases along with the drilling time at a slowing down penetration rate. A higher pressure results in a higher penetration rate. While there exists a direct influence of the material property on the drilling efficiency, it has limited significance with regard to the diameter of the hole produced. AE-RMS signal is demonstrated to be able to reflect the decreasing trend of the penetration rate and the influence of the pressure. A strong correlation between the penetration rate and AE-RMS values in AWJ hole drilling is shown through correlation analysis. The AE-RMS is also substantially affected by the material properties. A discrepancy of the AE-RMS under similar condition may suggest an anomaly in this cutting run. [ABSTRACT FROM AUTHOR]

Chatter is a self-excited vibration that affects the part quality and tool life in the machining process. This paper introduces an intelligent chatter detection method based on image features and the support vector machine. In order to reduce the background noise and highlight chatter characteristics, the average FFT is applied to identify the dominant frequency bands that divide the time-frequency image of the short-time Fourier transform into several sub-images. The non-stationary properties of the machining conditions are quantified using sub-images features. The area under the receiver operating characteristics curve ranks the extracted image features according to their separability capabilities. The support vector machine is designed to automatically classify the machining conditions and select the best feature subset based on the ranked features. The proposed method is verified by using dry micro-milling tests of steel 1040 and high classification accuracies for both the stable and unstable tests are obtained. In addition, the proposed method is compared with two additional methods using either image features from the continuous wavelet transform or time-domain features. The results present a better classification performance than the two additional methods, indicating the efficiency of the proposed method for chatter detection. [ABSTRACT FROM AUTHOR]

This paper presents an experimental study on abrasive waterjet (AWJ) machining of the most commonly used titanium alloy, Ti-6Al-4V. Two types of machining operations, i.e. drilling (or piercing) and slotting, were conducted. For the drilling experiments, the influences of water pressure and drilling time were investigated. It was found that both the hole depth and diameter increased as drilling time increased but in a decreasing rate. An increase in the water pressure increased both the hole depth and the hole diameter. For the slot cutting, the influence of water pressure and the traverse speed were investigated. A slower traverse speed resulted in a deeper depth of cut. The kerf showed a taper shape with a wider entry on top, and the width decreased as jet cut into the material. At the bottom of the kerf, a pocket was generated. The variation of the depth of cut became insignificant when the traverse speed was increased. [ABSTRACT FROM AUTHOR]

This paper presents the development of a cutting force model for the micro-end-milling processes under various cutting conditions using a hybrid approach. Firstly, a finite element (FE) model of orthogonal micro-cutting with a round cutting edge is developed for medium-carbon steel. A number of finite element analyses (FEA) are performed at different uncut chip thicknesses and velocities. Based on the FEA results, the cutting force coefficients are extracted through a nonlinear algorithm to establish a relationship with the uncut chip thickness and cutting speed. Then, the cutting force coefficients are integrated into a mechanistic cutting force model, which can predict cutting forces under different cutting conditions. In order to account for the cutting edge effect, an effective rake angle is employed for the determination of the cutting force. A comparison of the prediction and experimental measured cutting forces has shown that the developed method provides accurate results. [ABSTRACT FROM AUTHOR]

The relationship between the self-similar propagation region for single pulse and oscillation region for a pair of self-similar pulses are first investigated in our paper. By introducing self-similar coefficient F and RMS width ratio K, we find that self-similar propagation region starts from z = 1.8LD to z = 18LD while F ≤ 10%. The optimum output of self-similar pulse is also achieved when F and K reach a minimum value simultaneously at z = 3.5LD. The sinusoidal fit oscillation region of self-similar pulse pair ranges from 5/8LD to 2LD while F varies from 40.27 to 7.99%, and the dark soliton fit oscillation region ranges from 2LD to 6LD while F varies from 7.99 to 5.32%, indicating that the sinusoidal fit oscillation region almost occurs before the pulses enter the self-similar propagation region and the dark soliton fit oscillation region occurs within the self-similar pulse propagation region. Furthermore, the oscillation characteristics of interacting pulses are also studied numerically by using split-step Fourier method. The results are beneficial in Dense Wavelength Division Multiplexing transmission system which is in heavy demands of light source in wide-range wavelength. [ABSTRACT FROM AUTHOR]

Abstract: The influence of different dispersion-distribution in dispersion-decreasing optical fiber with normal group-velocity dispersion (ND-DDF) on the generation and compression of self-similar optical beam is investigated in this paper. The split-step Fourier numerical method is adopted and the amplitude of the pulses' envelope under different distributed dispersion is determined numerically. The generation and compression of the self-similar optical beam are simulated and analyzed based on the perspective of chirp feature. The result shows that chirp nonlinear region and chirp linearity level in different dispersion distribution fiber affect the generation and compression of the self-similar optical beam significantly. The quality of obtained self-similar and compressed optical beam in different tapered fiber increases in order of: cosinoidally tapered DDF, linearly tapered DDF, exponentially tapered DDF and hyperbolically tapered DDF, from the lowest to the highest. Graphical abstract: [ABSTRACT FROM AUTHOR]