High-speed Machining Process Research Articles

Surface Integrity and Machining Mechanism of Al 7050 Induced by Multi-Physical Field Coupling in High-Speed Machining

Improving the surface quality and controlling the microstructure evolution of difficult-to-cut materials are always challenges in high-speed machining (HSM). In this paper, surface topography, defects and roughness are assessed to characterize the surface features of 7050 aluminum alloy (Al 7050) under HSM conditions characterized by high temperature, strain and strain rate. Based on multi-physical field coupling, the mechanism of microstructure evolution of Al 7050 is investigated in HSM. The results indicate that the surface morphology and roughness of Al7050 during HSM are optimal at fz = 0.025 mm/z, and the formation of surface defects (adherent chips, cavities, microcracks, material compression and tearing) in HSM is mainly affected by thermo-mechanical coupling. Significant differences are observed in the microstructure of different machined subsurfaces by electron backscatter diffraction (EBSD) technology, and high cutting speeds and high feed rates contributed to recrystallization. The crystallographic texture types on machined subsurface are mainly {110}<112> Brass texture, {001}<100> Cube texture, {123}<634> S texture and {124}<112> R texture, and the crystallographic texture type and intensity are significantly affected by multi-physical field coupling. The elastic–plastic deformation and microstructural evolution of Al7050 alloy during the HSM process are mainly influenced by the coupling effects of multiple physical fields (stress–strain field and thermo-mechanical coupling field). This study reveals the internal mechanism of multi-physical field coupling in HSM and provides valuable enlightenment for the control of microstructure evolution of difficult-to-cut materials in HSM.

PARAMETER OPTIMIZATION FOR HIGH-SPEED END MILLING ON INCONEL 718 USING UNCOATED CARBIDE TOOL

Inconel 718 with exceptional characteristics is well known as a difficult-to-cut material especially during high-speed machining process. High cutting temperature further damaged the tool which results in low tool life. To overcome this matter, optimization on cutting parameters needed to be conducted in order to achieve longer tool life and desired cutting finish. Sets of optimized parameters consists of different cutting speed and feed rate were listed out through Research Surface Method (RSM) software which the effects and the output values were observed through high-speed end milling work on a 100 x 100 x 150 mm Inconel 718 block. The lowest cutting force and surface roughness at 776.04 N and 0.195 µm were recorded at the lowest parameter combination, while the highest results of 1,322.89 N and 0.478 µm were obtained from the highest parameter combination. Higher cutting parameter further deteriorate the cutting tool due to high heat and drastic reduction in tool life was observed, from 32 minutes of cutting process to only 2 minutes and 40 seconds. The results were further investigated through optimization work and cutting speed is the dominant factor that affected the results. The final model suggested that by using uncoated carbide tools, the lowest cutting speed and feed rate of 50 m/min and 0.05 mm/tooth can be implemented to obtain the desired cutting responses.

Effect of process parameters in high speed machining of Ti-6Al-4 V by using multiple methodology

There are several statistical techniques available for enhancing the different machining aspects of the high speed machining process. Following the completion of the experiments, calculations of several reaction parameters, including MRR and SR, were made. In this study work, the GRA, the Topsis, and the Taguchi approach are compared. This research compares the effects of optimizing an entire operation's machining parameter. In order to encourage an optimal balance between productivity and surface quality, the advancement is thus completed with the usage of subsequently enhanced qualities. In the experiment, the optimum point of view yielded similar results in the case of Topsis and Taguchi techniques. From an optimal point of view those levels were respectively level 2 for cutting speed, level 2 for feed rate, level 3 for depth of cut and level 1 for step over. Confirmatory studies demonstrate that the improvement in preference values in the experimental and initial settings is, respectively, 0.999641 and 0.483, which is sufficient, when TOPSIS and GRA are used.

Effects of build orientation and hatch spacing on high-speed milling behavior of L-PBF 316L stainless steel

Abstract Due to the philosophy of the process, the surface roughness is usually high for the parts produced with laser powder bed fusion (L-PBF) additive manufacturing (AM). Parts produced by this method need surface quality improvement processes for many applications. One of the methods used for this purpose is high speed machining (HSM). HSM is a modern manufacturing technique that offers several benefits, including improved productivity, enhanced product quality, and reduced production costs. In addition, HSM can improve the quality of finished products by reducing machining errors. In this study, samples produced with 316L powder in size of 10 × 10 × 5 mm using three different hatch spacings (60, 70, 80 µm) and building orientations (0°, 45°, 90°) were produced by L-PBF method, and HSM process was applied to these samples. In this context, the present study aimed to investigate the effects of porosity, microstructure and microhardness properties of 316L samples produced by L-PBF method using different hatch spacings and build orientations on cutting forces, surface roughness and burr formation in HSM. When the numerical values of the cutting forces were analyzed in both x and y directions, it was observed that the greatest cutting force occurred in the x direction. While the Fx force ranged from 6.23 to 9.35 N, the Fy force ranged from 4.88 to 8.27 N. It has been determined that as the build orientation increases at the same hatch spacing value, the cutting forces increase due to the increased porosity ratio.

Study on High-Speed Machining of 2219 Aluminum Utilizing Nanoparticle-Enhanced Minimum Quantity Lubrication (MQL) Technique

High-speed machining processes are significantly affected by the accumulation of heat generated by friction in the cutting zone, leading to reduced tool life and poor quality of the machined product. The use of cutting fluids helps to draw the heat out of the area, owing to their cooling and lubricating properties. However, conventional cutting fluid usage leads to considerable damage to human health and the environment, in addition to increasing overall manufacturing costs. In recent years, minimum quantity lubrication (MQL) has been used as an alternative lubricating strategy, as it significantly reduces cutting fluid consumption and eliminates coolant treatment/disposal needs, thereby reducing operational costs. In this study, we investigated microstructural surface finishing and heat generation during the high-speed cutting process of 2219 aluminum alloy using an MQL nanofluid. 2219 aluminum alloy offers an enhanced strength-to-weight ratio and high fracture toughness and is commonly used in a wide range of aerospace and other high-temperature applications. However, there is no relevant literature on MQL-based high-speed machining of these materials. In this study, we examined flood coolant and five different MQL nanofluids made by synthesizing 0.2% to 2% concentrations of Al2O3 nanoparticles into ultra-food-grade mineral oil. The study results reveal the chemistry between the MQL of choice and the corresponding surface finishing, showing that the MQL nanofluid with a 0.5% concentration of nanoparticles achieved the most optimal machining result. Furthermore, increasing the nanoparticle concentration does result in any further improvement in the machining result. We also found that adding a 0.5% concentration of nanoparticles to the coolant helped to reduce the temperature at the workpiece–tool interface, obtaining a good surface finish.

Simulation of high-speed machining processes by multi-edge mills

Based on the results of the numerical experiment by finite element analysis (FEA) the mill design having the initial tooth profile in the form of a trapezoid located along two intersecting spiral lines with angles of inclination of 14 and 71 degrees. As a result, about 70 cutting protrusions – are formed on the cylindrical surface, i.e., the total number of cutting edges in the cutting dynamics can be up to 280 blades. A model and methods for determining the geometric and kinematic parameters of cutting milling the required shape, dimensions and quality of the surface of the detail are proposed. The roughness at optimal cutting modes correspond to the Ra = 1.25-0.63 μm, which is comparable to grinding processing. The shape of individual chip elements can be described as spherical, its dimensions do not exceed 20 μm, and larger chip agglomerates have submicron and nanostructural fragmentation. Due to the increase of edges on the surface of new design mill increase the efficiency and intensity of deformation processes too (the number of single cutting cycles is up to 4000-6000 s-1). This is also in good agreement with the numerical estimates by the FEA method.

A parametric numerical study of ASB-assisted chip formation in high-speed machining of Ti-6Al-4V

ABSTRACT The present study aims at studying the influence of some parameters on the numerical results obtained from the simulation of the high-speed machining process using a commercial finite element computation code, namely Abaqus-Exp. Starting from models available by default in the computation code, comparisons are made between full and weak thermo-mechanical coupling, and the influence of the fracture strain and inelastic heat fraction values is studied. The high-strength Ti-6Al-4 V titanium alloy is taken as an example. Continuous, serrated and segmented chips are reproduced at low, moderate and high cutting speeds and the differences observed between experimental and numerical results are discussed.

A review on environmental friendly cutting fluids and coolant delivery techniques in grinding

Grinding is a very high-speed machining process, specifically, it is complex and often fails to achieve the accuracy, coolants are necessary for grinding to achieve the desired production rates. Coolant disposal is a serious issue since it poses a risk to the environment and land pollution. To reduce the friction and of frictional heating during grinding, suitable coolants and lubrication systems should be used, therefore, many approaches to eco-friendly coolant delivery techniques are been illustrated. Continuous long-term scientific research is needed toward green machining. “Go green, think green, and act green” statement should be followed in the industry during production and manufacturing. This literature survey was needed because it highlights previous and present research work on eco-friendly fluid delivery techniques, also the study explained how important this method will play in considering the future environment and workers’ health.

Chatter detection in milling process based on the combination of wavelet packet transform and PSO-SVM

Chatter is one of the biggest unfavorable factors during the high speed machining process of a machine tool. It severely affects the surface finish and geometric accuracy of the workpiece. To address this obstacle and improve the quality and efficiency of products, it is significantly essential to detect chatter during machining. Therefore, a multi-feature recognition system for chatter detection on the basis of the fusion technology of wavelet packet transform (WPT) and particle swarm optimization support vector machine (PSO-SVM) was proposed in this paper. Firstly, the original vibration signals collected from the acceleration sensor were processed through wavelet packet transform (WPT). The noise and the irrelevant information were remarkably decreased. In addition, the wavelet packets containing chatter-emerging information were chosen and reconstructed. The fourteen time–frequency domain characteristics of the reconstructed vibration signal were calculated and chosen as the multi-feature vectors of chatter detection. Finally, to obtain the optimal radial basis function parameter g and penalty parameter C of the SVM prediction model, the optimization algorithms of k-fold cross-validation (k-CV), genetic algorithm (GA), and particle swarm optimization (PSO) were employed in optimizing the model parameters of SVM. It was indicated that the PSO-SVM improved obviously the accuracy of chatter recognition than the others. In addition, we applied the optimized SVM prediction model by PSO for detecting chatter state in end milling machining. Chatter recognition results indicated that the model accurately predicted the slight chatter state in advance.

Analysis and optimization of machining parameters of Ti-6Al-4 V under high-speed machining

In this research paper, the experiment performed through high-speed machining process is mainly aimed at manufacturing high quality product and reducing the production cost. The role of surface finish is very important in assessing the quality of product. This experiment has been done to find out the optimum response in high-speed machining process. L-9 orthogonal array has been used to complete this work. In order to perform experiment such input parameter like cutting speed, feed rate, depth of cut, stepover has been selected. The main aim of doing this experiment is that it is better to have minimum surface roughness to get a better surface finish. The lowest value got in 9 trials was in trial 3 which is 0.60 µm. The results obtained after the completion of the experiment concludes that the cutting speed and depth of cut were main factors on surface roughness of materials. Confirmation test was carried out and its result was compared with the predicted outcomes. Thereby concluding that it is in good agreement with the experimental findings.

Optimization of Milling Aluminum Alloy 6061-T6 using Modified Johnson-Cook Model

Finite element (FE) simulation is an efficient and time-saving method to optimize the high-speed machining process of aluminum (Al) alloy. The constitutive model accurately described the dynamic mechanical behavior of materials at cutting conditions is the premise of obtaining high-precision simulation results. In this study, the flow stress-strain relationship of AA 6061-T6 is obtained at a high temperature (up to 400 °C) and a high strain rate (up to 1 × 104 s−1). Temperature-dependent Johnson-Cook (J-C) model is proposed by considering dynamic recrystallization effect. By the modified J-C model, a two-dimensional simplified FE model is established to optimize the high-speed milling process of AA 6061-T6 hard drive head (HDH) access arm. The results show that the modified J-C constitutive model has a good prediction accuracy, and the predicted cutting forces are in good agreement with the experimental results. By the finite element simulations, the influences of both cutting parameters and tool geometric parameters on cutting force, chip morphology, cutting temperature, effective stress and effective strain are analyzed during cutting processes of AA 6061-T6. Optimized range of cutting parameters and tool geometric parameters are obtained, which provides a theoretical guidance for the optimization of the cutting processes of Al alloy precision parts.

Prediction of cutting power and surface quality, and optimization of cutting parameters using new inference system in high-speed milling process

During the actual high-speed machining process, it is necessary to reduce the energy consumption and improve the machined surface quality. However, the appropriate prediction models and optimal cutting parameters are difficult to obtain in complex machining environments. Herein, a novel intelligent system is proposed for prediction and optimization. A novel adaptive neuro-fuzzy inference system (NANFIS) is proposed to predict the energy consumption and surface quality. In the NANFIS model, the membership functions of the inputs are expanded into: membership superior and membership inferior. The membership functions are varied based on the machining theory. The inputs of the NANFIS model are cutting parameters, and the outputs are the machining performances. For optimization, the optimal cutting parameters are obtained using the improved particle swarm optimization (IPSO) algorithm and NANFIS models. Additionally, the IPSO algorithm as a learning algorithm is used to train the NANFIS models. The proposed intelligent system is applied to the high-speed milling process of compacted graphite iron. The experimental results show that the predictions of energy consumption and surface roughness by adopting the NANFIS models are up to 91.2% and 93.4%, respectively. The NANFIS models can predict the energy consumption and surface roughness more accurately compared with other intelligent models. Based on the IPSO algorithm and NANFIS models, the optimal cutting parameters are obtained and validated to reduce both the cutting power and surface roughness and improve the milling efficiency. It is demonstrated that the proposed intelligent system is applicable to actual high-speed milling processes, thereby enabling sustainable and intelligent manufacturing.

Design and Development of Database System for Turning and Milling Compound high-speed Machining

In order to realize the advantages of high-speed cutting machine and improve the efficiency of high-speed cutting, a turning and milling compound high-speed machining process database was studied. According to the data information of cutting lathes, workpiece materials, tools and high-speed machining parameters, the functional requirements, system roles and system data relationships of the database system were analyzed. Based on the above information, the functional module, basic database, user permission and system architecture were designed, and a compound high-speed machining database system which is suitable for lathes and milling machines was developed.

Numerical Modeling the Effects of Chamfer and Hone Cutting Edge Geometries on Burr Formation

A finite element based numerical model to simulate orthogonal machining process and associated burr formation process has been developed in the presented work. To incorporate simultaneous effects of mechanical and thermal loadings in high speed machining processes, Johnson and Cook`s thermo-visco-plastic flow stress model has been adopted in the conceived numerical model. A coupled damage-fracture energy approach has been used to observe damage evolution in workpiece and to serve as chip separation criterion. Simulation results concerning chip morphology, nodal temperatures, cutting forces and end (exit) burr have been recorded. Model has been validated by comparing chip morphology and cutting force results with experimental findings in the published literature. Effects of cutting edge geometries [Hone and Chamfer (T-land)] on burr formation have been investigated thoroughly and discussed in length. To propose optimum tool edge geometries for reduced burr formation in machining of an aerospace grade aluminum alloy AA2024, numerical analyses considering multiple combinations of cutting speed (two variations), feed (two variations) and tool edge geometries [Hone edge (two variations), Chamfer edge (four variations)] have been performed. For chamfer cutting edge, the “chamfer length” has been identified as the most influential macro geometrical parameter in enhancing the burr formation. Conversely, “chamfer angle” variation has been found least effecting the burr generation phenomenon.

Effect of rake angle and tool geometry during machining process of AISI 4340 steel in finite element approach

Due to high impact resistance and abrasive resistance, AISI 4340 has been widely used in aircraft landing gear and high power transmission gears. During high speed machining process friction plays more important role in increasing temperature between tool and work piece. Owing to higher temperature in work piece and cutting tool increases wear rate and reduces the tool life. This paper investigates the effect of rake angle in normal cutting tool with various tool geometry and micro groove cutting tool during machining AISI 4340 steel with tungsten carbide cutting tool in simulation environment. Tool wear rate of micro groove cutting tool is minimum compared with other cutting tool with dissimilar tool geometry. Also micro groove tool minimize the cutting tool interface temperature.

A machined substrate hybrid additive manufacturing strategy for injection moulding inserts

In recent years, advances in metal additive manufacturing (AM) technology make the fabrication of complex conformal cooling channels for injection mould possible. However, poor surface finish, inadequate dimensional accuracy, and high manufacturing costs impede the technology to be adopted in the mould-making industry as an alternative. In this study, a time-efficient machined substrate hybrid AM strategy was developed for the fabrication of injection mould inserts using a hybrid additive-subtractive powder bed fusion process. The primary goal is to reduce AM build and post-processing time. Pre-machined support-free substrate blocks with position alignment and referencing features for subsequent machining operations were used for the additive manufacturing and high-speed machining processes. Four mould inserts, selected from a production injection mould, were redesigned with conformal cooling channels and fabricated in a metal powder bed fusion system using the standard AM practice and the proposed hybrid-build method. In comparison with the standard AM practice, a considerable saving in processing time was attained, but with a slight compromise in tensile strength. Through optical microscopy (OM) and scanning electron microscopy (SEM), a strong fusion bonding can be seen at the interface boundary between the additive powder and machined substrate. This new strategy will provide mould performance enhancement at reduced manufacturing costs for the plastic products manufacturing industry.

Deformation characteristics of aramid fiber–reinforced pneumatic wheel and machining analysis

A pneumatic wheel tool with reinforced aramid fiber is presented to finish irregular freeform surface with high hardness. Aramid fiber mainly is selected as a filler to achieve multi-dimension net distribution in polymer. In this case, the wheel can keep the outer abrasive particles more stable and decrease scratch damages of surface in the high-speed machining process. Based on the Halpin-Tsai formula, the orientation coefficient is brought in for the establishment of an elastic modulus prediction model of a fiber-reinforced pneumatic wheel. By ANSYS simulation, rules of stress and strain of pneumatic wheel with different volume ratios of fiber are given. It has been proved out that the fiber-reinforced method can overcome the defect of inner rubber deformation in the contact process. By mixed refining method, pneumatic wheels reinforced by aramid fiber are achieved. Multi-dimension net distribution of aramid fiber–reinforced polymer is observed in a microscopic view. Elastic modulus–predicted model is confirmed by drawing experiments. After that, aramid fiber–reinforced pneumatic wheel machining experiments are carried out. Results show that the fiber-reinforced method can improve surface roughness efficiently in the pneumatic wheel machining process and decrease scratch damages of the surface.

Performance of Low Cost 3D Printed Minimum Quantity Lubrication Applicator Using Palm Oil in Milling Steel

One of the most significant factors in machining process or metal cutting is the cutting tool performance. The rapid wear rate of cutting tools and cutting forces expend due to high cutting temperature is a critical problem to be solved in high-speed machining process, milling. Near-dry machining such as minimum quantity lubrication (MQL) is regarded as one of the solutions to solve this problem. However, the function of MQL in milling process is still uncertain so far which prevents MQL from widely being utilized in this specific machining process. In this paper, the mechanism of cutting tool performance such as tool wear and cutting forces in MQL assisted milling is investigated more comprehensively and the results are compared in three different cutting conditions which is dry cutting, wet cutting (flooding) and MQL. The MQL applicator is constructed from a household grade low-cost 3D printing technique. The chips surface of chips formation in each cutting condition is also observed using Scanning Electron Microscopy (SEM) machine. It is found out that wet cutting (flooding) is the best cutting performance compare to MQL and dry cutting. However, it can also be said that wet cutting and MQL produced almost the same value of tool wear and cutting forces as there is negligible differences in average tool wear and cutting forces between them based on the experiment conducted.

Grain size influence on chip formation in high-speed machining of pure iron

Same metallic materials with varied grain sizes have different material behaviors and are used in different industrial applications. However, machining parameters are normally determined by the materials, and the grain size effect has not been investigated in detail in a machining process. This paper studies the influence of grain sizes for pure iron on cutting force and chip formation in the high-speed machining with a speed of 24 m/s. A grain size–dependent material constitutive model is proposed and calibrated by the split Hopkinson pressure bar tests and then implemented into a finite element model of the high-speed machining process. The cutting force and chip morphology from simulation results have a good agreement with those from cutting experiments. The results show that a smaller grain size leads to more serrated chips in high-speed machining of pure iron due to the thermal- and mechanical-coupled effect at the shear band zone. Under the high-strain and high-temperature conditions, grain refinement occurs in the serrated chips.

Cutting responses of additive manufactured Ti6Al4V with solid ceramic tool under dry high-speed milling processes

Additive manufacturing (AM), an advanced manufacturing technology, has nowadays become increasingly popular in aerospace and biomedical fields since it provides the feasibility of producing complex-shaped Ti6Al4V components with faster speed and lower material waste. In order to achieve desirable shape dimensions and surface characteristics, finish machining operations are generally required. However, premature tool failure usually occurs with common carbide tools during the machining process while the performance of solid ceramic tool for AM Ti6Al4V alloy still remains unclear. To this end, the present work aims at studying the cutting responses of additive manufactured Ti6Al4V alloy with solid ceramic tool under dry high-speed milling processes. Various topics including cutting forces and cutting temperature fields as function of machining parameters were analysed. Furthermore, attention was also paid on the chip morphology, machined surface quality and tool wear mechanisms. The results indicate that the feed rate has greater impact on the magnitudes of cutting forces and temperature fields compared to the cutting speed. The continuous and free broken chips were generated during the milling process and the typically serrated morphology of chips were observed. The solid ceramic tool produces favorable machined surfaces under high-speed machining process apart from the tool edge marks. The mechanisms responsible for tool wear were determined to be micro chipping and chip adhesion owing to the mechanical and thermal loading.