Peripheral Milling Operations Research Articles

Machined surface prediction and reliability analysis in peripheral milling operations

The performance improvement of machine tools can be constrained by limited understanding of machined surfaces and machining quality reliability. In this paper, attentions are paid to the prediction of machined surface and the reliability analysis of machining quality for a three axis vertical machining center using peripheral milling operations. The prediction model of the machined surface in peripheral milling operations is developed considering the kinematic trajectories of all flutes, the run-out of tool, as well as the dynamic displacements of the cutter and workpiece. The dynamic displacements of the cutter and workpiece can be analytically calculated by the dynamics models of the tool and workpiece clamping systems of the machine tool. The location errors and roughness parameters are used to evaluate the quality of machined surfaces, and the reliability analysis method of machining quality is proposed considering the multiple failure modes. The proposed prediction method is verified during the peripheral milling of workpiece under different cutting conditions. The influences of some parameters on the machined surface are analyzed, and the machining quality reliability of the machine tool is also calculated and analyzed. This study can provide a theoretical basis for the design and optimization of machine tools and cutting tools, as well as the optimum design of processing conditions.

Multi-objective optimization of machining parameters in complete peripheral milling process with variable curvature workpieces

The mechanism of peripheral milling with variable curvature has yet to be revealed. There is an urgent need to develop a composite optimization approach for the full milling process, including rough and fine machining. The influence of curvature on the energy consumption mechanism in peripheral milling is investigated in this paper. Firstly, the geometric parameters of peripheral milling are analyzed, and the material removal rate calculation method with variable curvature is proposed. The effects of workpiece curvature, machining parameters, and tool wear on energy consumption and surface quality are revealed. Secondly, prediction models for machine tool specific energy and surface roughness are developed in accordance with the examined material removal mechanism. Then, the carbon emission calculation method for the complete peripheral milling process is put forward based on the developed energy consumption mechanism. Finally, a genetic algorithm with elite strategy is used to optimize the multi-dimensional and multi-objective machining parameters. The objective is to achieve the maximum machining efficiency, minimize carbon emissions, and attain excellent surface quality during the complete milling process. The research aims to concurrently optimize machining parameters for rough and fine machining processes, thereby enabling effective and environmentally friendly peripheral milling while maintaining machining quality. The determination coefficient R2 for the proposed model exceeds 0.97, while the average accuracy of predictions surpasses 96 %. The research holds particular importance in providing guidance for peripheral milling operations involving workpieces with variable curvature.

Surface location error prediction in 2.5-axis peripheral milling considering tool dynamic stiffness variation

In peripheral milling, surface accuracy is crucial for the quality of the machined components, and it is one of the reasons why milling is still essential in the manufacturing field. Nonetheless, both static phenomena, like tool deflections, and dynamic issues such as forced vibrations, impact on the accuracy of the components causing surface errors. In this context, the prediction of surface error is an important tool to guarantee surface accuracy and increase productivity at the same time. This paper presents a novel approach to predict surface location error in 2.5-axis peripheral milling operations considering the stiffness variation along the axial depth of cut. The proposed approach discretizes the endmill in small discs, and it evaluates analytically the cutting force along the cross-feed direction for each disc in the frequency domain. Then, tool dynamic stiffness, which is expressed in terms of frequency response function (FRF), is computed considering the stiffness variation along the tool axis. Finally, the presented approach couples the cutting forces with the tool stiffness, and it evaluates surface error along the tool axis. The method was experimentally tested in different conditions to verify its effectiveness and its limits. The results obtained show how static and dynamic aspects and stiffness variation contribute to surface errors in peripheral milling operations.

A frequency-based analysis of cutting force for depths of cut identification in peripheral end-milling

This paper presents a novel approach to identify both radial and axial depth of cut in 2.5-axis peripheral milling operations using cutting force signals analysed in the frequency domain (i.e., cutting force spectrum). In detail, the method exploits the normalized cutting force spectrum, which is directly obtained through dedicated analytical formulations, to estimate depths of cut. The proposed approach is promising and differs from previous works since it does require nor the cutting force coefficients or cutting force direction neither a dedicated instrumentation. The developed method was numerically and experimentally validated in different cutting conditions. The results obtained show that depths of cut are identifiable with a maximum absolute error less than 0.4 mm, proving that the proposed approach could be a solid foundation for a force based cutting condition monitoring system in peripheral milling.

On the relationship between cutting forces and anisotropy features in the milling of LPBF Inconel 718 for near net shape parts

The versatility and potential applications of additive manufacturing have accelerated the development of additive/subtractive hybrid manufacturing methods. LPBF processes are exceptionally efficient at producing complex-shaped, thin-walled, hollow, or slender parts; however, finishing machining operations are necessary to ensure part assembly and surface quality. Rapid solidification during LPBF processes generates columnar grain structures in alloys. This is associated with crystalline textures and anisotropy, and therefore, mechanical properties are highly dependent on space directions, thus affecting cutting force and its variability.In this study, theoretical and experimental analyses examined the effects of LPBF parameters on cutting forces and the anisotropy of alloys. Therefore, an oblique cutting Taylor based model was proposed to quantify the crystallographic effects on the shear strength. For this, the tool geometry, tool position, and laser scanning strategy were considered along with the microstructures, crystallographic textures and grain morphologies of two samples with different layer thicknesses (low-volumetric energy density (VED) and high-VED) using scanning electron microscopy and electron backscatter diffraction. Peripheral milling operations had been performed under 54 experimental conditions to evaluate the interactions between the machining parameters along with the layer thickness and the microstructural characteristics of printed alloys. The analysis revealed a significant interaction between the direction of the plane of the shear band and the grain orientation along the main axis. Three milling configurations were evaluated. The effects of the layer thickness on the evolution of the cutting force were elucidated. Additionally, the low-VED sample exhibited higher anisotropy in the cutting force compared to the high-VED one. The anisotropy in the latter corresponds to a high, dense <001> ring-like texture; however, the crystallographic effect is lower in the low-VED sample. A good correlation between the cutting force fluctuation and the predicted Taylor factor was obtained. Lastly, the grain boundary density was acceptably correlated with the level of cutting force for both the printed cases.

Modelling of machined surface topography and anisotropic texture direction considering stochastic tool grinding error and wear in peripheral milling

This paper establishes a new model for predicting machined surface topography and anisotropic texture direction in peripheral milling. Unlike previous models, this model takes into account the largest number of influential factors, i.e., tool setting error (radial offset and axial tilt), static tool deflection, forced vibration, chatter vibration, and stochastic tool grinding error and wear (STGEW). STGEW, quantified by the normal distribution (μ, σ2), is incorporated into the model for the first time. The model predictions for 3D surface topography, anisotropic texture direction, 2D surface profile or roughness agree remarkably well with experimental or published results, under both stable and unstable milling conditions. It is found that static deflection slightly attenuates the effect of tool setting error on roughness. Even machining with fresh tools or tools with very small cutting length (<15 mm) and wear (VB∼5 μm), inherent STGEW creates random scratches with different geometries parallel to feed direction on the milled surface. STGEW expands the difference of roughness in axial direction. STGEW induces an additional surface texture in feed direction, which co-exist with axial texture contributed by feed marks when standard deviation σ to feed rate ft ratio is small. As σ increases, (1) feed marks are gradually obliterated by scratches, and surface texture is only oriented in feed direction; (2) the mean and variance of roughness in both directions increase, and axial roughness prevails transverse toughness at high σ. The study discovers that, STGEW, even with small σ (e.g., σ=[0.01 μm, 0.1 μm]), is an important factor affecting surface topography, anisotropic surface texture direction and roughness that cannot be ignored, especially in the case of low-feed machining, e.g., ft = 0.05 mm, which is commonly adopted in finish-milling of difficult-to-cut materials. The proposed model can be used to reliably and accurately predict surface topography, surface roughness and surface texture direction in peripheral milling operation.

Modelling and simulation of surface topography machined by peripheral milling considering tool radial runout and axial drift

Based on the Z-map model of a workpiece and the dynamic cutting forces model of peripheral milling in which the regenerative effect of tool radial runout and axial drift are considered, a model for the prediction of surface topography in peripheral milling operations is presented. According to the stability lobe diagram obtained by the zero-order analytical method, the relationship between spindle speed and surface topography, the tool radial runout, and the axial drift following the chatter are studied. The results show that a stable cutting status but a poor surface finish is obtained at the spindle speeds at which the dominant frequency of the milling system is integral multiples of the selected machining frequency, and a stable cutting status with a good surface finish can be obtained near and on the left side of the resonant spindle speeds determined by the predicted stability lobe diagram. The motion equations of any tooth end mill for peripheral milling are established, and these equations are based on the transformation matrix and the vector operation principle of motion-homogeneous coordinates. In addition, the simulation algorithm and the system of surface topography generated in peripheral milling are given based on the Z-map model. Cutting tests are carried out, and good agreement between the measured surface topographies and the topographies predicted by the model in this study is found in terms of their shape, magnitude, feed mark, profile height of cross-section, and surface roughness. The simulation results show that the milling surface roughness increases with the increase in feed per tooth, which further shows that this simulation system has high credibility. Thus, the simulation and experimental results can provide some practical instructions for the actual peripheral milling in determining the optimal machining conditions.

Dependence of the passive force Fp from the revolutions, back engagement of cutting edge ae, working engagement of the cutting edge ap during milling

In this contribution is analysed the force component of final force (passive force) by peripheral milling operation. Therefore, the main parameters that had influence to independent variable were revolutions, back engagement of a cutting edge ae, working engagement of the cutting edge ap. The article deals with the issue of milling in material AlMgSi0.5 (aluminium alloy). Specifically evaluates the force component with respect to change of revolutions (4000/min., 5000/min., 6000/min.), working engagement of the cutting edge ap (1 mm, 2 mm, 3 mm) and back engagement of a cutting edge ae (5 mm, 10 mm, 15 mm). The Alfaflex process fluid with 7% concentration was supplied in an amount of about cca 10 l/min.

The Prediction of Surface Error Characteristics in the Peripheral Milling of Thin-Walled Structures

Lightweight design is gaining in importance throughout the engineering sector, and with it, workpieces are becoming increasingly complex. Particularly, thin-walled parts require highly accurate and efficient machining strategies. Such low-rigidity structures usually undergo significant deformations during peripheral milling operations, thus suffering surface errors and a violation of tolerance specifications. This article introduces a general approach to mitigating surface errors during the peripheral milling of thin-walled aluminum workpieces. It incorporates an analytical approach to predicting surface-error characteristics based on geometrical quantities and process parameters, which is presented in detail. Milling experiments, including geometrical measurements of the samples, have been performed to verify the approach. The approach allows for a pre-selection of parameter sets that result in surface errors that can be compensated with minimal effort. Additionally, the introduced model offers a simple criterion to assess potential error mitigation by applying the respective tool-path adjustments. In doing so, the amount of costly numerical simulations or experiments is significantly reduced.

Improved tooth trajectory model for prediction of milled surface geometry

ABSTRACTThe prediction on surface roughness and surface geometry in peripheral milling operation is a crucial but tedious task. The current researches concerned are almost based on circular tooth trajectory assumption to simplify analysis and modeling, and some models derived from true tooth trajectory are not concise enough or have certain limitation when put into practice. A novel idea on account of the principle of curvature circle approximation to true tooth path curve in cutting contact point nearby is presented, and the relevant mathematical theory is established. Then by means of specific curvature circles, mathematical models and analysis methods of surface roughness are discussed systematically, which cover two situations—cutting with and without runout effect. The validity and superiority of the models are demonstrated by experimental studies and numerical simulations. Finally, based on the suggested models and analytical methods, the effects of runout, feed rate, and cutter geometry on surface roughness and geometry are studied in depth, and several significant mathematical formulas and quantitative conclusions are reached, which would contribute to the theory of milled surface studies.

Dynamic modeling of spindle-rolling bearings systems in peripheral milling operations

In High-Speed Milling Process (HSM) the machining precision is directly affected by spindle bearing system which has a crucial role and it impacts directly the dynamic performance of the machining system. This study is about an accurate simulation of such system response. In fact, the Timoshenko beam theory with different circular sections is used to propose a finite element model of the spindle system. The effect of the rolling bearings and the gyroscopic moment at high speeds as well as the centrifugal forces and the cutting forces are considered in the formulation. The rigid and flexible movements of the spindle are taken into account. The dynamic responses of tool-tip under the dynamic cutting forces are numerically investigated.

エンドミル外周刃加工における数値制御工作機械駆動系の消費エネルギ

エンドミル外周刃加工における数値制御工作機械駆動系の消費エネルギ

Precision prediction of surface roughness in high speed peripheral milling Ti6Al4V alloy

Surface quality is important in engineering manufacture and a vital aspect of it is surface roughness, since it plays an important role in wear resistance, ductility, tensile, and fatigue strength for machined parts. In this paper, the influences of plastic deformation of work piece material in cutting process and tool vibration on the surface profile generation are analysed, and then illustration experiments are carried out under a range of high cutting speed (150-250 m/min). The experimental data are collected by a non-contact optical GFM MicroCAD system, and based on the results a regression model, termed as DRP model in this paper, is proposed for predicting surface roughness of peripheral milling. The prediction precision of DRP has been validated with a series of milling experiments, and the validation results show that the developed model achieves a good performance. This developed DRP model has a good prediction precision and can be used for predicting surface roughness in peripheral milling operation for industrial manufacturers.

On cutter deflection surface errors in peripheral milling

Cutter deflections induce significant amount of surface error on machined components and it is one of the major obstacles towards achieving higher productivity in peripheral milling operation. These surface errors do not take one particular form and their shape and profile measured along axial direction, varies significantly with cutting conditions. The understanding and characterization of all possible surface error types is of immense value to process planners as it forms a basis for controlling and compensating them. This paper presents a methodology to classify surface error profiles and to relate the same with cutting conditions in terms of axial and radial engagement between cutter and workpiece. The proposed characterization scheme has been validated using computational studies and machining experiments. The importance of proposed characterization is further demonstrated in understanding peripheral milling of curved geometries where workpiece curvature influences radial engagement of the cutter that often changes surface error shape both qualitatively and quantitatively. Computational and experimental studies undertaken to study machining of curved geometries underline the importance of proposed characterization scheme in identifying correct cutting conditions for a given machining situation.

Stability of Peripheral Milling Operations with Long End Mills

This paper presents dynamic modelling of peripheral milling systems with axially varying dynamics. The end mill is divided into differential elements along the cutter axis, and discrete nodes are assigned along the axial depth of cut. The cutting forces, which include regenerative and process damping components, are distributed to nodes. The equation of motion is transformed into modal space as periodic, delayed differential equations which cover one tooth period for regular, and one spindle period for variable pitch cutters. The directional coefficients are averaged and the stability is solved in frequency domain using Nyquist criterion. The presented model is experimentally verified in peripheral milling tests with low radial and high axial depth of cut.

Peripheral milling of thin titanium plates: modelling, analysis, and process planning

This paper presents research conducted to model and analyse the peripheral milling of thin titanium plates. Impact tests are performed and the vibration characteristics of a thin titanium plate modelled empirically. The force process is described by a mechanistic model and experimental data are used to determine the model parameters. The particle swarm optimization technique is used to determine the parameters of the plate vibration and force process models, which are combined to create a complete model of the thin titanium plate peripheral milling operation. The models are validated experimentally and excellent agreement is shown between the simulation and experimental results. A process planning scheme for peripheral milling of thin titanium plates is developed and applied. In this scheme integer numbers of widths-of-cut and depths-of-cut are used and the optimal helix angle and feed are computed for each combination of width-of-cut and depth-of-cut. The process planning test case revealed that the optimal material removal rate decreases as the width-of-cut decreases, the optimal helix angle is independent of the width-of-cut, and the optimal feed increases as the width-of-cut decreases. The test case also revealed that the optimal material removal rate is independent of depth-of-cut, the optimal helix angle increases as the depth-of-cut decreases, and the optimal feed increases as the depth-of-cut decreases.

Model for surface topography prediction in peripheral milling considering tool vibration

This paper presents a model for the prediction of surface topography in peripheral milling operations taking into account that the tool vibrates during the cutting process. The model includes the effect of tool vibrations in the equations of the cutting edge paths, which are transformed into equivalent polynomial equations and solved for discrete positions along the feed direction by applying a standard root finder. Through this procedure, surface topography generation is simplified with respect to other models in literature. The model allows the topography, the roughness values and the form errors of the milled surface to be predicted. Cutting test results show good agreement with model predictions.

Effect of tool setting error on the topography of surfaces machined by peripheral milling

In peripheral milling operations, errors in the tool setting on the spindle create roughness heterogeneity bands on the milled surfaces. This represents a defect in the appearance of the surfaces that cannot be ignored when surfaces have to meet high aesthetic requirements. Although the existence of these bands has been reported long ago, a quantitative evaluation has not been made so far. This paper presents a new model that allows the prediction of bands generated on surfaces machined by peripheral milling. This model accounts for tool setting errors: cutter parallel axis offset and cutter axis tilt. Through the proposed model, the effects of tool setting error, cutter geometry and feed, on band position, width and roughness are evaluated. Cutting tests were carried out to validate the model predictions and it was found that model predictions on band position and width agreed reasonably well with experimental results.

Mesure indirecte de la puissance de coupe pour une opération de contournage

The aim of this study is to present an indirect method to measure cutting power for a peripheral milling. Milling tests have been performed on 5-axis Ganibin 120CR machine fitted out with the electro-spindle with active magnetic bearings (AMB) SMB30, developped by S2M society. These bearings are not affected by friction and wear. An experimental approach lias been developed to determine the cutting power in function of the measured control voltages of the milling spindle's magnetic bearings. The validity of the cutting power calculation method was firstly established for slotting and extend to the case of peripheral milling operation. this indirect method of cutting force determination provides a, useful way to estimate tool wear and monitor on-line product quality in high-speed milling.

Stability Prediction for Low Radial Immersion Milling

Traditional regenerative stability theory predicts a set of optimally stable spindle speeds at integer fractions of the natural frequency of the most flexible mode of the system. The assumptions of this theory become invalid for highly interrupted machining, where the ratio of time spent cutting to not cutting (denoted ρ) is small. This paper proposes a new stability theory for interrupted machining that predicts a doubling in the number of optimally stable speeds as the value of ρ becomes small. The results of the theory are supported by numerical simulation and experiment. It is anticipated that the theory will be relevant for choosing optimal machining parameters in high-speed peripheral milling operations where the radial depth of cut is only a small fraction of the tool diameter.