Slot Milling Operation Research Articles

Numerical investigation on machining of additively manufactured CFRP composite with different build orientations and layer widths

Additive manufacturing (AM) is now a widely researched manufacturing technology in the past two decades to adopt in industry for its added advantage of customization and adopting complex geometries with comparatively low buy-to-fly ratio. Carbon fiber reinforced polymer (CFRP) composite has found applications in different high-performance industries for its greatest benefit of high strength-to-weight ratio. Additive manufacturing of CFRP composite (AM-CFRP) opens up the possibility of enhancing mechanical strength using different printing orientations and enables producing complex shapes maintaining sustainable manufacturing perspective. However, Limitation of AM parts of having surface irregularities and questionable dimensional accuracies. To use AM-CFRP parts in high precision assembly or industrial applications, post processing machining is often required to meet the customers’ specification of geometrical tolerances and acceptable surface finish. In this study, the influence of AM parameters on machinability of AM-CFRP composite has been evaluated using finite element analysis (FEA) based numerical simulation. The slot milling operation was simulated with a tungsten carbide end milling tool and AM-CFRP workpiece with four different printing directions, i.e., 0°-90°, 45°-135°, 0°-90°-45°-135°, two different layer widths, i.e., 50 µm and 100 µm, and two in-fill patterns, i.e., solid and perforated structures. The machinability of the 3D printed CFRP has been analyzed based on cutting forces, stress at first contact and maximum stress generation, and temperature increases at the interface during slot milling of AM-CFRP under different AM parameters. Evolution of failure mechanisms of AM-CFRPs under various machining conditions, such as, delamination, matrix rupture etc., have been discussed and chip and burr formation mechanisms have been analyzed. Finite Element analysis (FEA) package ABAQUS/Explicit was used to model 3D micro slot milling operation of AM-CFRP workpiece with appropriate damage and constitutive models, such as, damage initiation, progression and cohesion in adjacent passes and layers.

Wear Mechanism of an AlCrN-Coated Solid Carbide Endmill Cutter and Machined Surface Quality under Eco-Friendly Settings during Open Slot Milling of Tempered JIS SKD11 Steel

In the die and mold industry, tempered JIS SKD11 steel is selected to manufacture cold-forming dies that require an optimum balance of toughness, strength, and wear resistance. Therefore, the machinability of tempered JIS SKD11 in the milling machining process is challenging. The use of eco-friendly machining settings is intended to diminish tool wear and enhance the quality of the machined surface as well as the accuracy of the machined components. Adapting to the aforementioned factors for cold-forming dies is a pivotal issue. In this study, the machinability of tempered JIS SKD11 steel was analyzed under dry, MQL, cryogenic cooling with liquid nitrogen (LN2), and liquid carbon dioxide (LCO2) machining settings during open slot milling operations with varying input parameters, including cutting speeds and cutting feeds. An in-depth evaluation of output responses, including tool wear, surface roughness, cutting temperature in the cutting zone, and microhardness of the machined surface, was also conducted. The findings unveiled that the flank wear of the cutters and surface roughness of the machined surfaces obtained minimum values of 0.22 mm and 0.197 µm, respectively, during open slot milling operations at a cutting speed of 100 m/min and a cutting feed of 204 mm/min under cryogenic cooling with liquid carbon dioxide (LCO2). The findings from this study suggest that employing cryogenic cooling with LCO2 could serve as a viable substitute for dry, MQL, and cryogenic cooling with LN2 methods to enhance the machinability of hardened JIS SKD11 steel.

Enhancing machining efficiency of Ti-6Al-4V through multi-axial ultrasonic vibration-assisted machining and hybrid nanofluid minimum quantity lubrication

Ti-6Al-4V offers a balance of good strength with lightweight properties. Yet, Ti-6Al-4V poses machining challenges, including low thermal conductivity, chemical adhesion to cutting tools, and chip removal difficulties. To improve machining efficiency, Ultrasonic Vibration-Assisted Machining (UVAM) has emerged as a promising approach. UVAM has demonstrated reduced tool wear, cutting forces, and improved surface quality compared to Conventional Machining (CM). Additionally, Minimum Quantity Lubrication (MQL) methods offer sustainable coolant alternatives, with recent research focusing on Nanofluid-MQL (NMQL) and Hybrid Nanofluid-MQL (HNMQL) for enhanced performance. Although there exists a body of literature showcasing the promising effects of UVAM and MQL methods individually, comprehensive investigations into the synergistic effects of these methodologies remain limited. This study addresses these critical research gaps by conducting a systematic examination of combined application of multi-axial UVAM and HNMQL. Specifically, it delves into the comparison of different vibration directions within UVAM, evaluates the effectiveness of UVAM when combined with cutting fluids incorporating Al2O3 and CuO nanoparticles in NMQLs and HNMQLs, and contrasts these novel approaches with conventional machining methods. The study unfolds in three distinct stages. The first stage examines the ultrasonic cutting mechanism and its combined application with the MQL technique. In the second stage, the study investigates the physical properties of the cutting fluids, including contact angle and surface tension. The final stage encompasses slot milling operations, where an array of parameters such as cutting forces, surface roughness, surface topography, surface texture, and the occurrence of burr formations are rigorously analyzed. The results demonstrate that the combination of multi-axial UVAM with HNMQL yields substantial advantages over traditional machining methods. Notably, it leads to a remarkable reduction in cutting forces (up to 37.6 %) and surface roughness (up to 37.4 %). Additionally, this combination engenders the production of highly homogeneous and uniform surface textures, characterized by minimal surface defects and a significantly diminished occurrence of burr formations. These findings underscore the potential of multi-axial UVAM combined with HNMQL as a promising approach in enhancing the machining of Ti-6Al-4V, thus offering a pathway to enhance the efficiency and precision of aerospace component manufacturing processes.

Optimization of Fixture Layout and Clamping Force in a Concurrent Environment to Improve the Part Quality in Milling Operations

Fixture layout design (FLD) determines the specific position of locators and clamps to position and support the workpiece with respect to a machine tool. The FLD approaches that use Finite Element Analysis (FEA) are widely used in previous works, and it becomes computationally expensive and specific to a particular problem. Further, the FLD and clamping force optimization were often performed separately, ignoring their interdependence. In the present work, to maximize the dimensional and form quality of the part, the reaction forces of the locators are made uniformly distributed by suitably varying the fixture layout and clamping force. The parametric rigid body model is used to depict the behaviour of the workpiece-fixture system, and it is incorporated with the genetic algorithm to optimize the design variables. A prismatic workpiece with slot milling operation is considered to validate the proposed methodology. Stability criterion and tool-fixture interference are considered constraints. Subsequently, FEA is used to verify the integrity of the proposed approach. The results infer that the uniformity in distribution of maximum elastic deformation of the workpiece is achieved due to the uniform distribution of reaction forces. Further, the effects of cutting forces on fixture layout and clamping forces are studied.

Підвищення продуктивності фрезерування профільних пазів за рахунок удосконалення системи видалення стружки

Among the effective, but insufficiently used at this time, reserves for improving the system of forced chip removal include the significant energy potential of the lubricating and cooling technological agent, which is fed into the cutting zone to lubricate and cool the cutting tool. A reason for this situation is the lack of a coherent concept for improving the chip removal system, as well as the practical lack of knowledge of the laws of their working processes when exercising a forced effect on the separated chips precisely when processing profile grooves. The foregoing testifies to the relevance and importance for the mechanical engineering of Ukraine of the task of creating high-performance forced chip removal systems for profile slot milling operations based on the development of a theory of their functioning. Because of the research performed, an important task has been solved, which is to increase the productivity of milling profile slots by using a forced chip removal system with rational parameters. Developed technical solutions for the chip removal system, which provides an increase in the productivity of profile slot milling. A systematic representation of the process of forced chip removal during profile slot milling has been developed, which made it possible to identify the required number of mathematical models. Particular and integral mathematical models of the functioning of the main subsystems and modules of the forced chip removal system have been developed. A simulation of the process of forced removal of chips is carried out. Based on modeling, a technique has been developed for determining the rational parameters of the forced chip removal system when milling profile slots. Experimental studies have been conducted aimed at determining the effectiveness of the proposed technical solutions and confirming the adequacy of the developed mathematical models. The created chip removal system provides an increase in the productivity of milling profile slots by approximately 2 times while maintaining the quality of surfaces and increasing the durability of the cutting tool by at least 3 times due to the use of a forced chip removal system with rational parameters.

Comparative studies of variation in cutting conditions and cutter nomenclature on the surface morphology and the integrity of slot milled nimonic 263 alloy

Cutter nomenclature and machining conditions has invoke critical impact on the machining behavior and surface integrity of machined samples. In this investigation, the slot milling operation has been performed under various cutter terminology or nomenclature (cutter with the RRA of −7°, 0° and 7°) and cutting conditions (spindle speed, table feed and MQL flow rate) to analyze its resulting outcome on the surface morphological features such as surface roughness (Sa), skewness (S sk ) and kurtosis (S ku ), etc Because the examination of these characteristics are important and significant to analyze the behavioral changes of asperities such as decohesion, wear resistance and adhesion, etc during in its relative motion. Additionally, the plasticity index and surface morphology of machined samples are helps to predict the variation in surface morphology under various machining behavior and through this study, it is found that the interactive effect of MQL flow rate and table feed offer higher and significant impact over the surface characteristics followed by the MQL flow rate during slot milling process.

Characterization of Inconel 718® superalloy fabricated by wire Arc Additive Manufacturing: effect on mechanical properties and machinability

Wire and Arc Additive Manufacturing has the potential to become an appropriate technique to produce large complex-shaped metallic parts. However, a post-processing machining operation is necessary to reach the final geometry. In this work, Inconel 718 walls were manufactured in a monitored environment and their microstructure and mechanical properties were characterised. Then, slot milling operations were performed to investigate the influence of cutting speed and machining direction. The conclusions drawn from this article can be used as a guide for a correct definition of strategies and milling parameters. It was observed that at higher cutting speeds a better surface quality and lower torques are obtained. Moreover, the main novelty of this work is that is shows the influence of the anisotropy of WAAM-Inconel 718 on its machinability. Milling along the torch's travel direction offers better dimensional tolerance values with lower cutting torques, being more favourable than machining in the building direction.

Investigating surface finish, burr formation, and tool wear during machining of 3D printed carbon fiber reinforced polymer composite

Abstract Carbon fiber reinforced polymer (CFRP) composites are taking place as the most commonly used material in automotive and aerospace applications due to their superior strength-to- weight ratio, corrosion resistant exterior, and high performance under extreme conditions. Additive manufacturing or three-dimensional (3D) printing of CFRP composites is rising in popularity due to the ability to manufacture complex shapes and alter the fiber orientation of the material. However, difficult-to predict-microstructures along with non-uniform fiber dimensions plague researchers from predicting the response of the material. The objective of this research aims to investigate the machinability of 3D printed CFRP composites with different matrix arrangements, while varying machining process parameters and lubricating conditions. When testing the machinability of each material sample, one edge and slot milling operation was performed at the same feed rate, followed by an additional slot milling operation with an increased feed rate. These tests were run on varying fiber orientations, to observe how the machining response changes with differing matrix layout. After experimenting with different machining parameters and microstructural compositions, post-process machining was found to improve the quality of the surface finish when machining 3D printed CFRP composites. In all three samples, light microscope images showed a surface with less imperfections and protrusions, signifying a more even and applicable surface finish. In addition to the improved surface finish, machining results in burr formation, that requires additional efforts to clean the surface allowing use in end application. To reduce the degree of burr formation and improve machining results from dry machining, experiments were re-run using minimum quantity lubrication (MQL) techniques. Both the surface finish and tool wear were found to improve under MQL conditions. The burr formation was also significantly reduced, when MQL were used in the machining of CFRP composites.

Investigation of effect on energy consumption of surface roughness in X-axis and spindle servo motors in slot milling operation

The energy cost is a significant expense in the machining companies, and the reduction of energy consumption has a critical prescription in the industry. To increase energy efficiency, machine producers have contributed by developing advanced functions for machines. Besides these, one of the main purposes of machining is to bring the desired surface roughness to the best level. In this study, it is aimed to optimize cutting parameters to minimize the surface roughness and the energy consumption in the process of the 7075-aluminium material, which is commonly used in manufacturing industry, in CNC milling machine under dry cutting conditions. Therefore, a test list was created with Taguchi L9 experiment design the surface roughness and the power consumption of the machining centre were measured by processing in the CNC milling machine according to the tool diameter, cutting depth, cutting speed and feed rate parameters. The measured values were analyzed in the Minitab 17 program for the Taguchi method. According to the results of the analysis, X axis servo motor’s Pcutting value is affected by the amount of depth of 82%. However, the spindle servo motor’s Pcutting value was determined to be affected by the highest 34% cutting speed. The SEC (Specific Energy Consumption) value of both servo motors is affected by the maximum amount of depth. It is the amount of SCEC (Specific Cutting Energy Consumption) allows us to characterize machinability of the materials according to results from energy consumption. SCEC value is affected by the cutting speed 53% rate in the axis servo motor. In addition, it is affected by the feed rate of 43% in the spindle servo motor.

Sustainable selection of optimum toolpath orientation in milling AISI 1018 steel alloy

Toolpath orientations and axes weights have been identified as some of the parameters that could influence the electrical energy consumption and sustainable machining objectives. However, power evaluations of the machine tool axes when carrying different weights and in different toolpath trajectories have not been fully implemented for energy management in machining processes. This work proposes a framework for determining optimum toolpath orientations by conducting a comparative study and individualization analysis of axes weights for electrical power consumption management in slot milling operations of AISI 1018 steel alloy. Results show that performing slot milling at an angle aligned in the direction of the axis with the minimum weights tend to lower the feed axes power consumption.. Therefore, sustainable slot milling operations could be achieved by aligning the toolpaths at an angle oriented in the direction of the lighter axis for minimum feed axes power consumption. This work could further enhance the modeling of power consumption, and hence electrical energy demand in mechanical machining for resource efficiency and green manufacturing.

Effect of Tool Path Complexity on Top Burrs in Micromilling

Abstract Burr generation during micro milling operation is one of the major problem that poses challenge before engineers. The deburring operations performed in macro milling cannot be utilized in micro domain as this can affect the dimensional accuracy and possibly, damage the machined surfaces. However, the burr dimensions could be reduced by selecting appropriate machining parameters. Most of the studies done so far are focused on straight slot milling operations, while the complex tool paths, which are more often used in the industrial domain, have not been studied adequately. Therefore, the present work involves a detailed experimental analysis of burr formation in micro milling considering the effect of curvature in the tool path. The experiments performed are of two types. The Type I experiments investigate the top burrs as a function of tool path and machined length. The Type II experiments investigate the effect of machining parameters on the formation of burrs in both straight and curved paths. The burr values are found to increase with the curvature for the top burrs because of the increased plowing region due to the curvature effect. It is also noticed that burr dimensions at lower feed values are more in straight slots whereas, at higher feed values, circular tool paths here resulted in more burrs. Minimum burrs are observed at a depth of cut of 20 μm .

Neural Network Based Modelling of Time Optimal Interpolation of Non-linear Trajectory

Non linear curve fitting for execution of milling operation on Computer Numerical Control machining is always challenging. This paper focuses on fitting nonlinear curve and generation of time optimal trajectory to perform slot milling operation using NX CAM. Virtual simulation of trajectory is tested with various experimentation conditions and executed using Siemens 828D controller. Simulation and actual experimentation result is then compared with Multilayered Perceptron based Neural Network and optimum cutting parameters for time optimal trajectory is calculated.

Effect of Variable Pitch on Cutting Temperature, Cutting Forces and Surface Roughness Using Nitico30 Cutting Tool when End Milling of Stainless Steel 316L

In this paper, a series of milling tests were carried out in order to identify the effects of variable pitch on cutting temperature, cutting force and surface roughness while end milling the stainless steel 316L using Nitico30 and conventional cutting tools. Slot-milling operations were conducted. The value of feed rate were choose between the range recommended by the manufactured for the both conventional and Nitico30 cutting tool. The effect of variable pitch on cutting temperature, cutting forces and surface roughness were discussed. Results showed that the cutting temperature increase with the increase of feed rate for both cutting tool. Further increasing the speed of feed rate, the cutting forces also gradually increase for both cutting tool. However, the comparison between both cutting tools, it was found that the cutting temperature, cutting force and surface roughness improve about 47.8%, 37.5% and 17.6% respectively for Nitico30 cutting tool.

To characterize and optimize the surface quality attributes in slot milling operation

Burr formation and surface roughness are crucial surface quality attributes that vary widely according to machining conditions used. Inappropriate selection of cutting parameters may lead to tremendous non-desirable expenses and poor product quality. This becomes more apparent in slot milling operation that has a complex burr formation mechanism, and it is associated with multiple burrs with non-uniform dimensions appearing in the machined part edges. Therefore, as the first objective of this study, experimental characterization of governing cutting parameters on surface quality attributes, including exit burr size as well average surface roughness (R a ), is presented. Based on experimental observations, each aforementioned surface quality attribute is affected by different cutting parameters, and in fact, no systematic relationship can be formulated between them and the cutting parameters used. Therefore, advanced strategies are demanded for adequate selection of cutting parameters and reduction in the needs of deburring and surface treatment operations. Except the works reported by the authors, very limited studies are available on advanced optimization approaches for simultaneous minimization of surface quality attributes in slot milling operations. This can be considered as the second objective of this work. To that end, desirability function, D i (x), was used as the proposed approach to evaluate the possibility of simultaneous minimization of aforementioned surface quality attributes, despite the low control ability of each response. Using this approach, the optimum and near to optimum setting levels of cutting parameters were defined by means of surface quality improvement and the adequacy of the proposed optimum cutting conditions was reconfirmed through verification tests. The presented results in principle can be very useful in practice by local and international automotive industries dealing with similar family of materials.

Study of the Variability of the Machinability along the Cross Section of Ductile Iron Produced by Continuous Casting

In industry, the increase in the search for new materials is related to the cost and to the strength to weight ratio. In an effort to achieve these requirements new materials with low density and similar strength are employed or the resistance of traditional materials are increased by the addition of alloying elements or heat treatments. The choice usually depends on the mechanical and thermal properties and other aspects, such as manufacturing costs, recyclability, customer acceptance and machinability. Cast irons usually offer good machinability and low production cost, but long bars produced by continuous casting may present variability in their properties, including machinability along their cross sections. This is particularly true in bars with large cross sections. This work evaluates the behavior of the machining torque and surface roughness along the cross section of rectangular bars of nodular cast iron produced by continuous casting in slot-milling operation. It was found that the pearlite microstructure of the matrix and the mechanical strength contributed to the highest machining torque presented by the intermediate and core regions, but they did not affect the surface roughness significantly.

Modeling and experimental characterization of the friction effects on orthogonal milling exit burrs

Among conventional machining operations, milling burr formation has a very complex mechanism. According to the review of literature, exit up milling side burr is the longest and thickest milling burr that needs to be avoided or at least reduced through manipulating effective burr prevention strategies. Knowing that burr thickness Bt is the most delicate burr size attribute, a good knowledge on the effects of various cutting parameters (e.g., geometry and coating) as well as friction on the thickness of exit up milling side burr is therefore required to decrease the incidence of burr formation. Although friction angle λ has a direct proportion to negative shear angle ϕ as well as radial and tangential cutting forces (Fr, Ft), very limited information is still available on relationship between burr thickness Bt and friction angle λ in orthogonal milling operations. Therefore, the main aims of this work are then oriented to modeling and experimental characterization of the friction at the exit side of the slot milling operation followed by assessing the relationship between burr thickness Bt and friction angle λ at the exit side of slot milled parts of aluminum alloys (AAs). To this end, a computational algorithm was prepared to calculate the instantaneous chip thickness h(φ), tangential and radial cutting forces (Fr, Ft), friction angle λ, and friction coefficient μ. The experimental results exhibited direct relationships between friction angles, chip load, and burr thickness Bt. It was observed that lower friction angle λ is resulted when a larger chip load is applied. Consequently, primary and secondary burr formation is associated with larger and smaller friction angles λ, respectively.

Burr formation and correlation with cutting force and acoustic emission signals

The principle objective of this work is to present a methodology to evaluate the correlation between burr size attributes (thickness and height) and information computed from acoustic emission and cutting forces signals. In the proposed methodology, cutting force and acoustic emission signals were recorded in each cutting test, and each recorded original acoustic emission signal was segmented into two sections that correspond to steady-state cutting process (cutting signal) and cutting tool exit from the work part (exit signal). The dominant acoustic emission signal parameters including AEmax and AErms were computed from each segmented acoustic emission signal. The maximum values of directional cutting forces (FX, FY and FZ) were also measured in each trial. The experimental verification was conducted on slot milling operation which has relatively more complicated burr formation mechanism than that in many other traditional machining operations. Among slot milling burrs, the top-up milling side burrs and exit burrs along up milling side were largest and thickest burrs which were studied in this work. To evaluate the correlation between signal information and burr size, the computed signal information (5 parameters) and their interaction effects (10 parameters) were used to construct the input parameters of the multiple regression fitted models. Statistical methods were then used to assess the adequacy of individual input parameters and signal information. Using the acoustic emission and cutting force signals information in the input layer of multiple regression models, a high correlation was observed between the predicted and observed values of burr size. It was exhibited that due to complex burr formation mechanism in milling operation and strong interaction effects between cutting process parameters, no systematic relationship can be formulated between the milling burrs.

Prediction of Machining Fixture Layout through FEM and ANN and Comparison of Optimal Fixture Layouts of GA and ACA

In machine manufacturing, workholding plays a vital role in immobilizing the workpiece to provide maximum accuracy. The workpiece should be securely located and held against the cutting tool to reduce workpiece deformation thereby reducing dimensional and form errors. Fixtures are workholding devices used in machining and assembly for holding, supporting and locating a workpiece in a given orientation. Fixturing elements such as locators and clamps are used to deprive the workpiece of all degrees of freedom so that it is constrained at all times to prevent any movement. The optimal positioning of locators and clamps highly influences the workpiece deformation and thereby the machining errors. A two-dimensional workpiece geometry involving a slot milling operation has been considered for the research work for which the workpiece deformation for different fixture layouts is determined using finite element method (FEM). The different layouts and the corresponding workpiece deformations from the simulation results are made available as the database for artificial neural network (ANN) to develop a numerical model that recognizes a pattern between the position of fixturing elements and the workpiece deformations. Using the recognized pattern from ANN, genetic algorithm (GA) based continuous optimization method and ant colony algorithm (ACA) based continuous optimization method have been used to determine the optimal position of locators and clamps to minimize the workpiece deformation and thereby the dimensional errors

Optimization of Fixture Layout and Artificial Neural Network (ANN) Weights of ANN-Finite Element Analysis Based Fixture Layout Model Using Genetic Algorithm

Workpiece elastic deformation in machine manufacturing may cause dimensional errors, which in turn affects the accuracy of the machined parts. Fixturing elements like locators and clamps are used to locate a workpiece with respect to the cutting tool in a given orientation such that the errors caused by workpiece elastic deformation are reduced. The optimization of locator and clamp positions is crucial in minimizing the dimensional errors in machining. In this research paper, a slot milling operation on a rectangular workpiece is considered for which the fixture layout is optimized using a hybrid system of artificial neural network (ANN) and genetic algorithm (GA). The workpiece elastic deformation for different sets of fixture layouts is calculated using finite element method (FEM) and training of ANN is done with the FEM results to develop a numerical model. To enhance the accuracy of learning in lesser time, the weights are optimized for the network using GA before the training phase. The trained ANN recognizes a pattern between the position of fixturing elements and the workpiece elastic deformation. Using the recognized pattern, GA determines the optimal position of locators and clamps to minimize the workpiece elastic deformation and thereby the dimensional errors.

Cyclostationarity approach for monitoring chatter and tool wear in high speed milling

Detection of chatter and tool wear is crucial in the machining process and their monitoring is a key issue, for: (1) insuring better surface quality, (2) increasing productivity and (3) protecting both machines and safe workpiece. This paper presents an investigation of chatter and tool wear using the cyclostationary method to process the vibrations signals acquired from high speed milling. Experimental cutting tests were achieved on slot milling operation of aluminum alloy. The experimental set-up is designed for acquisition of accelerometer signals and encoding information picked up from an encoder. The encoder signal is used for re-sampling accelerometers signals in angular domain using a specific algorithm that was developed in LASPI laboratory. The use of cyclostationary on accelerometer signals has been applied for monitoring chatter and tool wear in high speed milling. The cyclostationarity appears on average properties (first order) of signals, on the energetic properties (second order) and it generates spectral lines at cyclic frequencies in spectral correlation. Angular power and kurtosis are used to analyze chatter phenomena. The formation of chatter is characterized by unstable, chaotic motion of the tool and strong anomalous fluctuations of cutting forces. Results show that stable machining generates only very few cyclostationary components of second order while chatter is strongly correlated to cyclostationary components of second order. By machining in the unstable region, chatter results in flat angular kurtosis and flat angular power, such as a pseudo (white) random signal with flat spectrum. Results reveal that spectral correlation and Wigner Ville spectrum or integrated Wigner Ville issued from second-order cyclostationary are an efficient parameter for the early diagnosis of faults in high speed machining, such as chatter, tool wear and bearings, compared to traditional stationary methods. Wigner Ville representation of the residual signal shows that the energy corresponding to the tooth passing decreases when chatter phenomenon occurs. The effect of the tool wear and the number of broken teeth on the excitation of structure resonances appears in Wigner Ville presentation.