Sustainability analyses of cutting edge radius on specific cutting energy and surface finish in side milling processes

The aim of this work is to determine the influence of cutting edge radius on the specific cutting energy and surface finish in a mechanical machining process. This was achieved by assessing the direct electrical energy demand during side milling of aluminium AW6082-T6 alloy and AISI 1018 steel in a dry cutting environment using three different cutting tool inserts. The specific energy coefficient was evaluated as an index of the sustainable milling process. The surface finish of the machined parts was also investigated after machining. It was observed that machining with the 48.50-μm cutting edge radius insert resulted in lower specific cutting energy requirements when compared with the 68.50 and 98.72-μm cutting edge radii inserts, respectively. However, as the ratio of the undeformed chip thickness to cutting edge radius is less than 1, the surface roughness increases. The surface roughness values gradually decrease as the ratio of undeformed chip thickness to cutting edge radius (h/r _e) tends to be 1 and at minimum surface roughness values when the ratio of h/r _e equalled to 1. However, the surface roughness values increased as h/r _e becomes higher than 1. This machining strategy further elucidates the black box and trade-offs of ploughing and rubbing characteristics of micro machining and optimization strategy for minimum energy and sustainable manufacture.     

Experimental investigations on effects of tool flank wear on surface integrity during orthogonal dry cutting of Ti-6Al-4V

Machining titanium alloy Ti-6Al-4V is a challenging task since tool flank wear adversely affects surface integrity. Quantitative effects of predetermined tool flank wear values (VB) on the surface integrity were investigated through the orthogonal dry cutting of Ti-6Al-4V. Experimental results indicated that three-dimensional (3D) average surface roughness increased with the VB ranging from 0 to 0.2 mm but decreased at VB = 0.3 mm. Given the effects of rubbing and ironing enhanced, surface material burning and plastic flows emerged on the machined surface at VB = 0.3 mm. Not only the plastic deformation layer became deeper but also the grains were greatly distorted with the increase of tool flank wear. When machined by using the tool at VB = 0.3 mm, the β phase of Ti-6Al-4V decreased near the machined surface layer than that of using the fresh tool. Besides, the depth of work-harden layer increased from 20 to 60 μm with the VB increasing from 0 to 0.3 mm. The softened layer was generated near the machined surface by using the tool at VB = 0.3 mm. In addition, the residual compressive stresses of the machined surface had the trend of decreasing. Experimental results indicated that the VB less than 0.2 mm was the most suitable condition for better surface integrity during orthogonal dry cutting of Ti-6Al-4V. This study aims at providing experimental data for optimizing the processing parameters and improving the surface integrity of Ti-6Al-4V.     

Cutting performance of nano-crystalline diamond (NCD) coating in micro-milling of Ti6Al4V alloy

Hard coatings are an important factor affecting the cutting performance of tools. In particular, they directly affect tool life, cutting forces, surface quality and burr formation in the micro-milling process. In this study, the performance of nano-crystalline diamond (NCD) coated tools was evaluated by comparing it with TiN-coated, AlCrN-coated and uncoated carbide tools in micro-milling of Ti₆Al₄V alloy. A series of micro-milling tests was carried out to determine the effects of coating type and machining conditions on tool wear, cutting force, surface roughness and burr size. Flat end-mill tools with two flutes and a diameter of 0.5 mm were used in the micro-milling process. The minimum chip thickness depending on both the cutting force and the surface roughness were determined. The results showed that the minimum chip thickness is about 0.3 times that of the cutter corner radius for Ti₆Al₄V alloy and changes very little with coating type. It was observed from wear tests that the dominant wear mechanism was abrasion. Maximum wear occurred on NCD-coated and uncoated tools. In addition, maximum burr size was obtained in the cutting process with the uncoated tool.     

Taguchi-based grey relational analysis for modeling and optimizing machining parameters through dry turning of Incoloy 800H

The present research focused on the optimization of machining parameters and their effects by dry-turning an incoloy 800H on the basis of Taguchi-based grey relational analysis. Surface roughness (Ra, Rq and Rz), cutting force (Fz), and cutting power (P) were minimized, whereas Material removal rate (MRR) was maximized. An L ₂₇ orthogonal array was used in the experiments, which were conducted in a computerized and numerical-controlled turning machine. Cutting speed, feed rate, and cut depth were set as controllable machining variables, and analysis of variance was performed to determine the contribution of each variable. We then developed regression models, which ultimately conformed to investigational and predicted values. The combinational parameters for the multiperformance optimization were V = 35 m/min, f = 0.06 mm/rev and a = 1 mm, which altogether correspond to approximately 48.98 % of the improvement. The chip morphology of the incoloy 800H was also studied and reported.     

Development of a capacity analysis and planning simulation model for semiconductor fabrication

Micro-machining has gained increased application to produce miniaturized parts in various industries. However, the uncut chip thickness in micro-machining is comparable to cutting edge radius. The relationship between the cutting edge radius and uncut chip thickness has been a subject matter of increasing interest. The acoustic emission (AE) signal can reflect the stress wave caused by the sudden release of the energy of the deformed materials. To improve the precision of machining system, determination of the minimum uncut chip thickness was investigated in this paper. The AE signal generated during micro-cutting experiments was used to analyze the chip formation in micro-end milling of Inconel 718. The finite element method (FEM) simulation was used to analyze the results of the experiments. The results showed that the cutting tool geometry and material properties affected the minimum uncut chip thickness. The estimation of the minimum uncut chip thickness based on AE signals can produce quite satisfactory results. The research on the minimum uncut chip thickness can provide theoretical basis for analysis of surface quality and optimal choice of cutting parameters.     

Calculation of negative-pressure chip in suction-type internal chip removal system and analysis of influencing factors

Compacted graphite iron (CGI) is considered as the ideal material to make modern fuel-efficient diesel engine. Due to the vermicular or worm-like graphite distributed among the ferrite/pearlite matrix, CGI behaves better physical and mechanical properties in comparison with gray cast iron (GCI) and spherical graphite spheroidal cast iron (SGI). However, these good properties bring about the machining challenges. So it is important to appropriately select cutting parameters to machine this material with economy and efficiency. The present study investigated the influence of cutting parameters, such as cutting speed V, feed rate f, and exit angle Ψ, on workpiece material removal volume Q and cutting burr height on the entrance side H₁ and on the exit side H₂ during high-speed milling of CGI by the coated carbide tools_. On this basis, the relatively optimum high-speed cutting parameters were selected under the research condition. Cutting tool failure mechanism was also investigated with the aid of scanning electronic microscope (SEM) and energy-dispersive system (EDS) (SUPRA55, Germany) analysis. The results showed that Q, H₁, H₂, and the type of cutting burr on the exit side of the machined surface could be influenced by the cutting parameters. And the relatively optimum cutting parameters are V = 800 m/min, f = 0.25 mm/rev, and Ψ = 60°. Adhesive wear and thermal cracks which were perpendicular to the cutting edge were common wear mechanisms during the cutting process. However, with an increase in feed rate, mechanical cracks which were parallel to the cutting edge could be found on the flank face of the cutting tool.     

Integrated ANN-LWPA for cutting parameter optimization in WEDM

In this paper, we present a new approach to determinate cutting parameters in wire electrical discharge machining (WEDM), integrated artificial neuron network (ANN), and wolf pack algorithm based on the strategy of the leader (LWPA). The cutting parameters considered in this paper are pulse-on, current, water pressure, and cutting feed rate. Models of the effects of the four parameters on machining time (T_p), machining cost (C_p), and surface roughness (Ra) are mathematically constructed. An ANN-LWPA integration system with multiple fitness functions is proposed to solve the modelling problem. By using the proposed approach, this study demonstrates that T_p, C_p, and Ra can be estimated at 164.1852 min, 239.5442 RMB, and 1.0223 μm in single objective optimization, respectively. For example, as for Ra, integrated ANN-LWPA has optimized the Ra value by the reduction of 0.1337 μm (11.6 %), 0.3377 μm (24.8 %), and 0.105 μm (10.3 %) compared to experimental data, regression model, and ANN model, respectively. Consequently, the ANN-LWPA integration system boasts some advantages over decreasing the value of fitness functions by comparison with the experimental regression model, ANN model, and conventional LWPA result. Moreover, the proposed integration system can be also utilized to obtain multiple solutions by uniform design-based exploration. Therefore, in order to solve complex machining optimization problems, an intelligent process scheme could be integrated into the numeric control system of WEDM.     

AN EXPERIMENTAL STUDY OF ORTHOGONAL MACHINING OF GLASS

Abstract

An experimental study of machining glass with a geometrically defined cutting tool is presented. Orthogonal cutting conditions are employed to permit a focus on the fundamental modes of chip and surface formation. Analysis of the machined surfaces under an optical microscope identifies four regimes that are distinctly different with respect to either chip formation or surface formation. For a very small target uncut chip thickness, one on the order of the cutting edge radius, pure rubbing of the edge with no chip formation is observed. Edge rubbing imparts light scuffmarks on the machined surface giving it a frosted appearance. At a larger uncut chip thickness, ductile-mode chip formation occurs ahead of the cutting edge and a scuffed surface remains after the subsequent rubbing of the edge across the freshly machined surface. A further increase in uncut chip thickness maintains a ductile-mode of chip formation, but surface damage initiates in the form of surface cracks that grow down into the machined surface and ahead of the tool. The transition to this machining mode is highly dependent on rake angle. Increasing the uncut chip thickness further causes brittle spalling of chips leaving half-clamshell shaped divots on the surface. This experimental identification of the machining modes and their dependence on uncut chip thickness and rake angle supports the use of geometrically defined cutting tools to machine glass in a rough-semi-finish-finish machining strategy as is traditionally employed for machining metals.     

Research on specific cutting energy and parameter optimization in micro-milling of heat-resistant stainless steel

In present research, micro-milling of heat-resistant stainless steel (12Cr18Ni9) is conducted with the purpose of revealing influence mechanism of cutting tool edge radius and cutting parameters on specific cutting energy. In order to clarify the relationship between specific cutting energy and the geometrical characteristics of the cutting tools as well as cutting parameters, a newly designed experimental method is put forward, thereafter, the evolution rules of specific cutting energy along with cutting parameters is researched in detail. Furthermore, a prediction model of the minimum chip thickness is built by using fuzzy logic method based on experimental data, objective to optimize cutting parameters during micro-milling of 12Cr18Ni9, good agreements are achieved between predicted results and experimental results in verification tests, which means the specific cutting energy can be well controlled with the parameter recommended by the constructed model. The above research has great significance in improving tool life and machining quality.     

Parametric optimization of CNC turning process for hybrid metal matrix composite

Machining of hybrid metal matrix composite is difficult as the particulates are abrasive in nature and they behave like a cutting edge during machining resulting in quick tool wear and induces vibration. An attempt was made in this experimental study to evaluate the machining characteristics of hybrid metal matrix composite, and a mathematical model was developed to predict the responses, namely surface finish, intensity of vibration and work-tool interface temperature for known cutting condition while machining was performed in computer numerical control lathe. Design of experiments approach was used to conduct the trials; response surface methodology was employed to formulate a mathematical model. The experimental study inferred that the vibration in V _x, V _y, and V _z were 41.59, 45.17, and 26.45 m/s², respectively, and surface finish R _a, R _q, and R _z were 1.76, 3.01, and 11.94 μm, respectively, with work-tool interface temperature ‘T’ of 51.74 °C for optimal machining parameters, say, cutting speed at 175 m/min, depth of cut at 0.25 mm and feed rate at 0.1 mm/rev during machining. Experimental results were in close conformity with response surface method overlay plot for responses.     

Investigate on milling force of cryogenic cooling processing aluminum honeycomb treated by ice fixation

Aerospace metal honeycomb materials with low stiffness had often the deformation, burr, collapse, and other defects in the mechanical processing. They were attributed to poor fixation method and inapposite cutting force. This paper presented the improvement of fixation way. The hexagonal aluminum honeycomb core material was treated by ice fixation, and the NC milling machine was used for a series of cryogenic machining. Considering the similar structure of fiber-reinforced composite materials, the milling force prediction model of ice fixation aluminum honeycomb was established, considering tool geometry parameters and cutting parameters. Meanwhile, the influence rule on milling force was deduced. The results show that compared with the conventional fixation milling method, the honeycomb processing effect is improved greatly. The machining parameters affect order on milling forces: the cutting depth is the most important, followed by the cutting width, then the spindle speed and the feed. Moreover, too small cutting depth (a_p?=?0.5 mm) will cause insufficient cutting force, while a_p?>?2 mm with higher force will reduce the processing quality of honeycomb. Simultaneously, the honeycomb orientation (θ) has a great influence on processing quality. Using the model, the predicted and measured error values of the feed and main cutting force are all small in θ?<?90°. But, the rate is 33 and 26% for the main cutting force and feed force error in θ?>?90°, respectively, while they all exhibit the smallest error in θ?=?60°. This bigger error mainly is due to unstable cutting force with obtuse angle. In addition, the tool rake angle has little influence on cutting quality in θ?<?90°, but bigger on that in θ?>?90°. Furthermore, the calculation model successfully conforms to the main deformation mechanism and influences parameters of the cutting force in the milling process, and it can accurately predict the cutting force in θ?<?90° and guide the milling process.     

Soft computing models and intelligent optimization system in electro-discharge machining of SiC/Al composites

In this paper, a multi-variable regression model, a back propagation neural network (BPNN) and a radial basis neural network (RBNN) have been utilized to correlate the cutting parameters and the performance while electro-discharge machining (EDM) of SiC/Al composites. The four cutting parameters are peak current (I_p), pulse-on time (T_on), pulse-off time (T_off), and servo voltage (S_v); the performance measures are material remove rate (MRR) and surface roughness (Ra). By testing a large number of BPNN architectures, 4-5-1 and 4-7-1 have been found to be the optimal one for MRR and Ra, respectively; and it can predict them with 10.61 % overall mean prediction error. As for RBNN architectures, it can predict them with 12.77 % overall mean prediction error. The multivariable regression model yields an overall mean prediction error of 13.93 %. All of these three models have been used to study the effect of input parameters on the material remove rate and surface roughness, and finally to optimize them with genetic algorithm (GA) and desirability function. Then, an intelligent optimization system with graphical user interface (GUI) has been built based on these multi-optimization techniques, in which users can obtain the optimized cutting parameters under the desired surface roughness (Ra).     

Contribution of specific work of fracture to size effect in microcutting

Specific work of fracture (R) has been widely used to quantify the energy consumed in formation of new surfaces during metal cutting. R becomes a significant portion of total cutting energy in microcutting, thereby influencing the phenomenon of “size effect. ” Therefore, this work presents an evaluation of specific work of fracture for sharp and rounded-edged tools, knowing cutting forces and shear angles from LS-DYNA simulations of orthogonal microcutting of low-carbon AISI 1215 steel. The R was also evaluated as a function of process parameters such as cutting speed, rake angle, tool edge radius, and uncut chip thickness, so as to illustrate the effect of these variables on the magnitude of R and contribution of R to the specific cutting energy or “size effect.” It is observed that R increases with an increase in uncut chip thickness, whereas it decreases with an increase in cutting speed, rake angle, and tool edge radius. U_R defines the contribution of fracture to the specific cutting energy (U) due to specific work of fracture R. At all the parametric conditions, the contribution of fracture is higher at lower uncut chip thickness and it is of 8–36% in microcutting of AISI 1215 steel.     

Geometry simulation and evaluation of the surface topography in five-axis ball-end milling

Limited by the factors such as dynamic vibrations, cutting heat, and the use of coolant, it is difficult to measure or evaluate the surface quality in real time. Geometry simulation of the surface topography became the main method used in engineering to estimate and control the quality of the surface machining. This paper proposed a new method for geometry simulation and evaluation of a milled surface. Allowing for the coherency in geometric variations management process, the proposed method is developed based on the skin model of a workpiece. To make the simulated surface topography more realistic, the effects of locating errors, spindle errors, geometrical errors of the machine tool, and cutting tool deflections are included. And a new method is adopted to evaluate the milled surface, in which the roughness of the surface is characterized by the modal coefficients, instead of the R _a , R _z , and R _q values. At the end of this paper, measurements and cutting tests are carried out to validate the proposed method.     

AN EXPERIMENTAL STUDY OF ORTHOGONAL MACHINING OF GLASS

An experimental study of machining glass with a geometrically defined cutting tool is presented. Orthogonal cutting conditions are employed to permit a focus on the fundamental modes of chip and surface formation. Analysis of the machined surfaces under an optical microscope identifies four regimes that are distinctly different with respect to either chip formation or surface formation. For a very small target uncut chip thickness, one on the order of the cutting edge radius, pure rubbing of the edge with no chip formation is observed. Edge rubbing imparts light scuffmarks on the machined surface giving it a frosted appearance. At a larger uncut chip thickness, ductile-mode chip formation occurs ahead of the cutting edge and a scuffed surface remains after the subsequent rubbing of the edge across the freshly machined surface. A further increase in uncut chip thickness maintains a ductile-mode of chip formation, but surface damage initiates in the form of surface cracks that grow down into the machined surface and ahead of the tool. The transition to this machining mode is highly dependent on rake angle. Increasing the uncut chip thickness further causes brittle spalling of chips leaving half-clamshell shaped divots on the surface. This experimental identification of the machining modes and their dependence on uncut chip thickness and rake angle supports the use of geometrically defined cutting tools to machine glass in a rough-semi-finish-finish machining strategy as is traditionally employed for machining metals.     

Definition and determination of the minimum uncut chip thickness of microcutting

Uncut chip thickness is comparable to cutting edge radius in micromachining. If the uncut chip thickness is less than a critical value, there will be no chip formation. This critical value is termed as minimum uncut chip thickness (MUCT). Although minimum uncut chip thickness has been well defined in orthogonal cutting, it is often poorly understood in practical complex turning and milling processes. In this paper, a set of definitions of minimum uncut chip thickness for three-dimensional turning and milling processes are presented. This paper presents an analysis of the state-of-the-art research on minimum uncut chip thickness in precision micromachining. Numerical and experimental methods for determination of MUCT values and their effects on process mechanics and surface integrity in microcutting will be critically assessed in this paper. In addition, a detailed discussion on the characteristics of different methods to determine minimum uncut chip thickness and several unsolved problems are proposed for the future work.     

Experimental investigation on chip morphologies in high-speed dry milling of titanium alloy Ti-6Al-4V

An experimental investigation of chip morphologies in high-speed dry milling of Ti-6Al-4V alloy was conducted over a variety of different cutting conditions. Observation on the multi-view characterization of the chips was carried out which includes free surface, back surface, and cross-section of top surface. Structure and shape alterations of the free and back surfaces were analyzed using an optical microscope and a scanning electron microscope (SEM). The microstructural analysis indicated that the chip morphology when dry milling Ti-6Al-4V alloy in high-speed range exhibited a serrated shape for a wide range of cutting conditions. The degree of chip serration is more pronounced and evident with the increase in cutting speed, feed, and depth of cut. A significant variation in the microstructure of the chip including the thickness of the shear bands and the serrated tooth structure for different cutting speeds has been identified. The higher chip serration ratio (CSR) in high cutting speed range may facilitate appropriate machining condition for the occurrence of well-broken chips. Moreover, chip formation takes place by the mechanism of catastrophic thermoplastic shear from the observation of the shear bands using metallurgical analysis techniques. X-ray diffraction results indicated that no evidence of phase transformation was found in the shear localized chips. The variation in chip serration and metallurgical microstructure inside the shear bands and the tool/chip contact zone should be attributed to the reinforcement of coupled thermo-mechanical behavior in the cutting process with the increase in machining parameters.     

Hybrid analytical–numerical solution for the shear angle in orthogonal metal cutting — Part II: experimental verification

The hybrid analytical–finite element model described in Part I is applied to predict the shear angle for a range of cutting velocity, uncut chip thickness, and two tool orthogonal rake angles. Experimental results and an empirical equation are also presented for the influence of the cutting conditions and cutting tool geometry on the chip–tool contact length. It is shown that there is a linear dependence between the chip–tool contact length/uncut chip thickness ratio and chip thickness/uncut chip thickness ratio over the range of cutting conditions assumed. The increase of the shear angle with the tool orthogonal rake is mostly due to the reduction of the specific shear energy in the primary shear zone and the specific friction energy in the secondary shear zone accompanied by a reduction of the chip–tool contact zone. The uncut chip thickness and cutting velocity influence the shear angle through their effect on the interface temperature and hence on the material flow stress in the secondary shear zone. The change in both parameters does not change significantly the specific shear energy in the primary shear zone. The model results are compared with the experimental results for a work material 0.18% C steel. The agreement between the predicted and experimental results is seen to be exceptionally good.     

Improvement of grinding performance and investigation of cutting parameters using a grinding mechanism with secondary rotational axis

“Grinding Mechanism having Advanced Secondary Rotational Axis” (GMASRA) is one of the newer plane surface grinding methods that have an uncommon abrasion mechanism. Unlike conventional methods, in GMASRA, there are two rotations of a wheel. The first rotation is the same as in conventional grinding methods, which is the circumferential rotation. The other rotation is the newly developed axial rotation, where the wheel rotates around itself perpendicular to its radial axis. In this study, the effects of certain cutting parameters on arithmetical mean deviation of the assessed profile (the R_a parameter) were investigated. Particularly, the effects of cutting parameters on R_a in the GMASRA grinding process were examined. The selected cutting parameters were the depth of cut, the number of axial revolutions of the wheel, and the stepover distance of the wheel. Five wheels with different properties were chosen. Additionally, GMASRA was modeled using the Taguchi orthogonal test design. In this orthogonal design, the depth of cut, the spindle speed, and the type of grinding wheel were chosen as the control factors. The effect of the specified control factors on the surface roughness was demonstrated using an analysis of variance (ANOVA) test. Results show that GMASRA produced better R_a values than the conventional method. R_a values were very close to each other in every part of the ground workpieces. According to the modeling results, the spindle speed had the highest effect on R_a, followed by the depth of cut and the type of grinding wheel. GMASRA is also very cost effective and can be adapted to most milling machines and CNC milling machines.     

INFLUENCE OF FRICTION AND PROCESS PARAMETERS ON THE SPECIFIC CUTTING FORCE AND SURFACE CHARACTERISTICS IN MICRO CUTTING

For the production of small quantities of micro devices, machining is a low cost alternative to lithographic processing techniques. However, machining shows process specific size-effects upon miniaturization to the micrometer regime. Hence, the orthogonal turning process is chosen to study the influence of process parameters like uncut chip thickness h, cutting velocity v_c and cutting edge radius r_β on the cutting force and the surface plastification by two-dimensional, thermo-mechanically coupled finite element simulations. A rate-dependent plasticity law is used for investigation of a normalized medium carbon steel (AISI 1045). Furthermore, the characteristics of the influences of the different parameters are analyzed mathematically by similarity mechanics. In particular, the frictional effects on the cutting process are studied in detail using a friction coefficient μ based on experimental results, and the influences of the process parameters on the cutting force and the plastic deformation of the surface layer are determined numerically. These results are compared with experimental measurements. The specific cutting forces are analyzed and discussed in detail. Size-effects observed experimentally are also found by numerical simulations.