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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]

Interest in natural fiber–reinforced composites (NFRCs) is increasing rapidly thanks to their numerous advantages such as low cost, biodegradability, eco-friendly nature, relatively good mechanical properties, and a growing emphasis on the environmental and sustainability aspects of engineering materials. However, large-scale use of NFRCs is still considered as challenging due to the difficulties in manufacturing, limited knowledge of its machinability and appropriate parameter settings, and being prone to machining-induced defects. This article presents a comprehensive review on various aspects of NFRCs, with a focus on the manufacturing and machinability. It covers some recent works related to NFRCs, including the manufacturing processes and parameters, characterization of mechanical properties, applications, and machinability and machining process monitoring, many for the first time. The main challenges associated with machining of NFRCs and the induced damages are outlined, with special attention paid to the effect of physical properties of the fibers and manufacturing process on the machinability, along with the essential machining parameters that affect the quality of the machined surface. The research perspectives and the current application status are also discussed. The article is intended to help readers attain a fundamental understanding of key technologies and the state of the arts in this research area. [ABSTRACT FROM AUTHOR]

Chatter detection in metal machining is important to ensure good surface quality and avoid damage to the machine tool and workpiece. This paper presents an intelligent chatter detection method in a multi-channel monitoring system comprising vibration signals in three orthogonal directions. The method comprises three main steps: signal processing, feature extraction and selection, and classification. The ensemble empirical mode decomposition (EEMD) is used to decompose the raw signals into a set of intrinsic mode functions (IMFs) that represent different frequency bands. Features extracted from IMFs are ranked using the Fisher discriminant ratio (FDR) to identify the informative IMFs, and those features with higher FDRs are selected and presented to a support vector machine for classification. Single-channel strategies and multi-channel strategies are compared in low immersion milling of titanium alloy Ti6Al4V. The results demonstrate that the two-channel ( Ay , Az ) strategies based on signal processing and feature ranking/selection give the best performance in classification of the stable and unstable tests. [ABSTRACT FROM AUTHOR]

A cutting force model, based on a predictive model for orthogonal cutting, is developed for force predictions in end milling of titanium alloy Ti6Al4V. The model assumes a semi-stationary process for the serrated chip formation. The Johnson–Cook material model that couples strain hardening, strain rate sensitivity and thermal softening effects is applied to represent the material strength. A thermal model considering the tool thermal properties is integrated to account for the high temperature rise due to the low thermal conductivity of Ti6Al4V. To extend the predictive model to milling, the end mill is discretised into several axial slices, and an equivalent cutting edge is used to include the end cutting edge effect caused by the first axial slice. The model is assessed by comparing its prediction with the experimental results and a mechanistic model for verification. The results show that the proposed model outperforms the mechanistic model with higher accuracy in force prediction. [ABSTRACT FROM AUTHOR]

This paper presents an experimental study of the effects of cutting parameters of micro-end-milling process on the machined surface roughness, in order to find the optimal operation conditions for improved surface finish. Three types of metals, namely 6160 aluminium alloy, brass, and AISI 1040 steel, are used as work materials. The effect of material property on the surface roughness is investigated. It is found that under the same machining condition, the machined surface quality of aluminium alloy is the worst, while that of brass is the best. A multiple regression model for the surface roughness is developed, which includes the effects of cutting speed, feedrate, and the interaction between them. Results based on analysis of variance (ANOVA) show that the cutting speed is the most significant factor on surface roughness. The residual analysis indicates that the multiple regression model is valid and agrees with the experimental results. [ABSTRACT FROM PUBLISHER]

Modelling of the cutting forces in micromilling is challenging due to the size effect and existence of a minimum chip thickness. This paper presents the development of a cutting force model for micromilling of brass. The prediction of cutting forces derives from a simplified orthogonal process. A finite element (FE) model is employed to simulate two-dimensional cutting forces in orthogonal microcutting, with the ploughing and tool edge effect taken into consideration. The flow stress of workpiece material is modelled by using the Johnson–Cook constitutive material law. The FE model is used to evaluate the critical chip thickness and to extract the cutting force coefficients. The cutting force coefficients are modelled as a function of instantaneous uncut chip thickness, which is independent of cutting speed but influenced by tool edge radius. To rectify the issue of sharp increase of the force coefficients under very small uncut chip thickness, a critical uncut chip thickness value is introduced and the coefficients are adjusted by using a tangent slope for uncut chip thickness smaller than the critical value. A generalized analytical force model based on numerical findings is developed to predict the micromilling force by considering the tool trajectory and tool runout. The simulation results of micromilling forces are compared against experimental measurement, where an agreement of force trends is shown along with the increasing feedrate and depth of cut. [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]