Hard Machining Process Research Articles

Extensive evaluation of microhardness alterations induced in subsurface layers after hard machining of AISI 4340 steel and process optimization

ABSTRACT Hardened AISI 4340 steel is extensively utilised in engineering industries. Owing to the fact that thermo-mechanical loads are applied to surface layers during the hard machining process, severe changes occur at the surface of the machined workpiece. These changes can affect some mechanical properties of the material, including microhardness, and residual stresses generation in material. Therefore, it is significantly influenced by process conditions and there is not any study in literature to extensively evaluate and optimise different indications of microhardness alteration after hard machining of AISI 4340 Steel. In this study, the influence of machining parameters was firstly studied on the microhardness distribution at machining of hardened AISI 4340 steel by experimental tests. Then, the optimal surface microhardness and depth of the affected layer were assessed using the intelligent techniques. In this regard, the optimal process conditions were simultaneously determined using the combination of the Artificial Neural Networks (ANNs) and Non-dominated Sorting Genetic Algorithm (NSGA-II). The results indicated that, both depth of the affected layer and surface microhardness were obtained in optimal state when the cutting speed changes from 720 to 600 (Rpm) and feed rate and depth of cut are 0.05 (mm/rev) and 0.4 (mm), respectively.

Recent research progress on various cooling and lubrication techniques used in sustainable hard machining: A comprehensive review

In recent research, hard machining is an essential manufacturing technology to meet the demand for various industrial product quality and precision. Several key issues like higher heat generation, higher tool wear, higher cutting force and inappropriate surface quality were found in hard machining. Researchers have examined several hard machining-related issues and developed their own suggestions for solutions. It was attempted to research the effects of tool geometry, tool materials and coatings, cutting parameters, and different cooling strategies (coolant and its delivery techniques) on various machinability responses, such as tool wear, tool life, cutting forces, surface roughness, chip morphology etc. In this review article, the different methodologies of cooling and lubrication utilized during hard machining processes have been analysed and their potential application towards sustainable machining is explored. This paper addressed the needs, challenges, and trends towards achieving sustainable hard machining of hard-to-cut materials through the application of dry, minimum quantity lubrication, cryogenic and nanofluids-assisted minimum quantity lubrication cooling strategies. It will be helpful to achieve environmental, economical, ecological and societal benefits to justify sustainable machining. Minimum quantity lubrication hard machining and nano-cutting fluid-assisted minimum quantity lubrication hard machining for sustainability will be immensely beneficial for the replacement of traditional cooling strategies for machining hard-to-cut hardened steel. Furthermore, different computational methods adopted in hard machining for optimization and modelling were also explored to get the optimal solution for industrial applications.

Liquid nitrogen spraying in hard machining process of AISI H13 steel

ABSTRACT The application of liquid nitrogen is being considered nowadays because it is clean and environmentally friendly and improves product quality. The cryogenic cooling can also be useful in hard machining process where workpiece is exposed to high thermo-mechanical loads. Thermal loads are one of the factors affecting residual stresses and microstructural changes in a material. There is no study in literature to evaluate the effect of cryogenic cooling for evaluation of thermo-mechanical loads during the machining of the hardened AISI H13 steel. Therefore, in the present study, to control and investigate the thermal loads, microhardness, white layer thickness, and surface quality in hard machining of AISI H13 steel, the cryogenic cooling system was employed during the process. Results indicated that depth of cut was the most influential item on temperature enhancement of cutting zone, while high feed rates were responsible for enhancement of microhardness surface roughness. Intense and rapid cooling using the liquid nitrogen spraying was found effective strategy to reduce white layer thickness and improve surface quality at the machined surface.

A contemporary advancement of intelligent machining and sustainability aspects in hard machining area: A Critical Review

The intelligent manufacturing devotes considerable effort to towards machining process. This phenomenon is engendered by the growing demand for advanced machining process for manufacturing of precise parts by adopting optimization techniques. This article illustrates the most significant developments in the sustainability aspects as well as optimization and modelling techniques adopted to solve the problems and complexity in hard machining process. Machining realisation necessitates recent and future breakthroughs in technological innovations for Industry 4.0. A significant amount of focus is also paid to the different sustainability aspects, modelling strategies and performance analysis during hard machining process. Many avenues for future study on the needs of intelligent manufacturing are discussed in this article. The future directions for intelligent machine systems and sustainability factors are also discussed for the green, sustainable, and high dimensional accuracy manufacturing in hard machining area.

Machining feasibility and Sustainability study associated with air pressure, air flow rate, and nanoparticle concentration in Nanofluid minimum quantity lubrication-assisted hard milling process of 60Si2Mn steel

In recent years, more efficient hard machining processes have notably increased in demand for higher productivity but environmental friendliness. High hardness and strength as well as the enormous amount of cutting temperature are still the biggest obstacles. Nanofluid minimum quantity lubrication (NFMQL)–assisted hard machining has become a feasible and promising solution to overcome these problems. The work presents the experimental study on the effects of air pressure (5, 6, and 7 bar), air flow rate (150, 200, and 250 L/min), and Al2O3 nanoparticle concentration (0.5, 1.0, and 1.5%) on minimum quantity lubrication (MQL) hard milling process of 60Si2Mn (50÷52HRC) using vegetable oil as the based fluid. Box–Behnken experimental design and ANOVA analysis were employed to investigate the influences and interaction effects of input parameters on cutting forces, surface roughness, and surface microstructure. This study will be used for selecting the optimum air pressure, air flow rate, and Al2O3 nanoparticle concentration for efficient cooling lubrication performance of MQL in sustainable hard machining. The obtained results show that the optimal values for air pressure and nanoparticle concentration. For Q = 200 L/min, the optimal p is 6.0 bar and the optimal nanoparticle concentration (NC) is 0.9%. For Q = 250 L/min, the optimal p is 5.2 bar, and the optimal NC is 1.2%. Furthermore, using air flow rate Q = 250 L/min gives better results than Q = 200 L/min, but the selection will be depended on the specific equipment conditions.

Prediction of surface roughness in hard machining of EN31 steel with TiAlN coated cutting tool using fuzzy logic

Hardened EN31 steel is extensively used to make parts in engineering industries. Hardened steel, due to its special properties is difficult to machine. Cemented carbide, coated tools, ceramics and cubic boron nitride are employed to machine EN31 steel. Choosing the best combination of cutting parameters for good surface finish is a complex task in hard machining process. In this study, Fuzzy logic is employed to predict surface roughness in hard machining of EN31 steel using TiAlN coated cutting tool. Nine metal cutting experiments were performed with three levels of cutting speed, feed rate and depth of cut. Surface finish was measured with a surface roughness tester. For developing the fuzzy logic models, the MATLAB R2020b software was used. The built-in fuzzy logic toolbox was used for building the model. The inference system selected for this model was madman. Triangular membership function is assigned to all the parameters and variables. Nine fuzzy rules were created in linguistic form using the data derived from the machining experiments. It can be concluded that fuzzy logic model is able to estimate surface roughness with acceptable accuracy. High cutting speed and low feed rates delivers good surface finish.

MQL Applied for Hard Machining of Ferrous Alloys Using Hardmetals: A Review

Today, mostly of machining process is carried out under dry machining or minimum quantity lubricant (MQL) method. The MQL is considered as the proper solutions to reduce the amount of lubricant. This is not only reducing in cost, but also maintaining the machine life, safety, and environmentally friendly. Previous research was attempted to develop a minimum quantity cooling technique that made a major contribution to the solution of problems that affect the parts of dry machining operations. However, a gradual phase tool wear should be conditioned to make the tool work optimally and reach better performance. Therefore, this study is aimed to review the effect of the MQL use for both cermet and carbide tools that focused on the tool wear, tool life and economic advantage in hard machining process. The review revealed that MQL with cermet tool derives the good quality lubrication, better penetrates to the cutting area, reduce the cutting temperature, and increase the quality of the surface roughness, thus it recommended instead of carbide for hard machining.

An experimental study on the effect of tool geometry on tool wear and surface roughness in hard turning

The main purpose of this study is to investigate the influence of tool geometry (cutting edge angle, rake angle, and inclination angle) and to optimize tool wear and surface roughness in hard turning of AISI 1055 (52HRC) hardened steel by using TiN coated mixed ceramic inserts. The results show that the inclination angle is the major factor affecting the tool wear and the surface roughness in hard turning. With the increase in negative rake and inclination angles, the tool wear decreases, and the surface roughness increases. However, the surface roughness will decrease when the inclination angle increases to overpass a certain limit. This is a new and significant point in the research of the hard turning process. From this result, the large negative inclination angle (λ = −10°) should be applied to reduce the surface roughness and the tool wear simultaneously. With the optimal cutting tool angles in the research, the hard machining process is improved remarkably with decreases of surface roughness and tool wear 8.3% and 41.3%, respectively in comparison with the standard tool angles. And the proposed tool-post design approach brings an effective method to change the tool insert angles using standard tool-holders to improve hard or other difficult-to-cut materials turning quality.

Tool wear rate of the PCBN, mixed ceramic, and coated cemented carbide in the hard turning of the AISI 52100 steel

The hard turning process is generally performed by PCBN or mixed ceramics tools, which have the mechanical properties that withstand the tribological conditions of the process imposed by the hardened machined material. Coated cemented carbides are also an option for hard machining processes, although relying on the coating deterioration. This paper aims to evaluate the tool wear rate in function of the cutting speed in the hard turning of the steel AISI 52100 with a hardness of 50 HRC for three different types of cutting tool materials: coated cemented carbide, mixed ceramic, and PCBN. The methodology applied to assess the tool wear is based on three-dimensional parameters (volumetric) obtained from a focus variation microscope (FVM). The tool wear rate (WRRM) is calculated based on ordinary least squares (OLS) adopting five values of WRM in five machining time intervals. The face turning experiments were performed at four cutting speeds: vc = 120, 150, 187.5, and 234 m/min. At vc = 120 m/min, the PCBN presented the lowest tool wear rate (182 μm3/s); at vc = 150 m/min, the coated cemented carbide (tool wear rate on the coating) had the best performance (417 μm3/s). The mixed ceramic tool presented a better performance at the higher cutting speeds of vc = 187.5 and 234 m/min, 1206 and 1878 μm3/s, respectively. The methodology applied was reliable to understand and discuss the performance of the machining process through the tool wear rate (WRRM), which is based on the volume of removed material from the tool (WRM). The three-dimensional tool wear parameters can also be applied to machining process optimization, cutting tool wear model creation, benchmarking, and development of new cutting tool materials and grades. Furthermore, the methodology can be considered more agile and precise when compared to the current industrial methodology of tool performance evaluation. Thus, this innovative methodology promotes important information for cutting tool manufacturers and for its customers such as automotive and aeronautic industry.

The efficiency of hard machining processes

The efficiency of hard machining processes

Deep cryogenic treatment of carbide tool and its cutting performances in hard milling of AISI H13 steel

Microstructure and mechanical properties of cutting tool have significant effect on tool wear, especially in hard machining process. As an effective non-destructive modification technology, cryogenic treatment is widely used for carbide tools in order to change its microstructure and phase constituent which reflects the change of hardness, wear resistance and plasticity in macroscale. In this paper, an orthogonal experiment was designed to investigate the effect of deep cryogenic treatment parameters (cryogenic temperature, cooling rate, soaking time, and tempering temperature) on microstructure and mechanical properties of carbide tool with Ti (N, C)-Al2O3 coatings as well as its cutting performances in hard milling of AISI H13 steel. First, the microstructure of carbide tool was observed by means of scanning electric microscope (SEM), energy dispersive spectrometer (EDS) and X-ray diffraction (XRD). The experimental results show that WC grains were refined and large amounts of dispersive carbide was precipitate out. Secondly, the variation of hardness was measured through Vickers tester and the surface microhardness was improved evidently after cryogenic treatment. Range analysis was employed and the analysis results reveal that temperature has the most significant influence on hardness followed by cooling rate, holding time and tempering temperature. Finally, hard milling experiments were carried out and the experimental results indicate that the flank wear VB decreased under same material removal volume and tool wear resistance is strengthened. The research can provide an instruction for improving mechanical and physical properties of cutting tools to increase tool life.

Investigations on the effect of thickness and structure of AlCr and AlTi based nitride coatings during hard machining process

In the present study, hard machining performance of Al2O3/TiCN based mixed ceramic insert was investigated as a function of thin film thickness. Aluminium rich mono-layered and multi-layered nitride coatings with similar mechanical and thermal properties deposited by physical vapor deposition (PVD) technique were considered with three different thin film thicknesses. The machining performance was evaluated mainly by power consumption, surface roughness, cutting temperature and chip reduction coefficient and correlated in terms of tool wear. Coating adhesion to the substrate increased with thickness for AlTiN coated tools whereas for AlCrN coating, 3μm thin coating film exhibited best substrate adhesion which affected the machining behavior. Also, the multilayered structure of AlTiN coating outperformed AlCrN coating under good coating adhesion to the substrate. Cr-based nitride coating illustrated signs of flaking whereas Ti-based coating exhibited only abrasion wear at adverse cutting conditions.

Atomic-scale investigation of carbon atom migration in surface induced white layers in high-carbon medium chromium (AISI 52100) bearing steel

The microstructure and chemical composition of white layers (WLs) formed during hard turning of AISI 52100 steel were studied using atom probe tomography (APT) and transmission electron microscopy (TEM). APT analyses revealed a major difference in the re-distribution of the carbon (C) atoms between WLs formed above and below the Ac1 temperature, i.e. T-WL and M-WL, respectively. In T-WL, the C-atoms segregate to grain boundaries (GBs) forming interconnected or isolated C-rich clusters, ∼5 nm, with a concentration of 9.8 ± 0.3 at.%C. Apart from the GB segregation, in M-WLs, large C-rich regions were found with 24.8 ± 0.4 at.%C. Owing to the chemical composition (stoichiometry) and element partitioning of such regions, they were assigned as θ-carbides (cementite). The APT results reveal that the original θ-carbides remain un-dissolved in the M-WLs, but might be plastically deformed due to the excessive strain that exists in hard machining process. The obtained results are in good agreement with the temperatures that are reached during formation of M-WLs. The isolated nano-sized C-clusters were assigned as off-stoichiometric carbides whereas the interconnected C-rich clusters were attributed to Cottrell atmospheres, evident by the linear shape of the C-enrichment as observed in the APT reconstructions. The C-contents in the nano-sized martensitic and ferritic grains were estimated to 0.50 ± 0.06 at.%C and ∼0.46 ± 0.02 at.%C, respectively. The C-content in the ferritic grains, beyond the C-solubility limit in ferrite (<0.1 at.%) is governed by the high dislocation density inside the grains, supported by the favorable binding energy between dislocations and C-atoms compared to C-atoms and Fe in carbides. No other evidence of redistribution of the substitutional alloying elements was observed. TEM analyses showed that T-WLs comprises of an equiaxed and nano-sized grains with well-defined cell boundaries, whereas the structure in the M-WLs comprised of elongated sub-grains formed via re-orientation of the original martensite followed by breakage/partitioning into elongated sub-grains.

Case-based reasoning (CBR) model for hard machining process

In this research paper, hard machining of two materials viz. AISI 52100 (bearing steel) and AISI D2 (tool steel) at a hardness of 55 HRC is addressed. Taguchi’s technique is used for the design of experiments. Eight different parameters are considered for the experimentation in order to perform comprehensive investigations on hard machining process. Case-based reasoning (CBR) model is developed for predicting the machining performance and its capability is evaluated by conducting validation experiments. The root mean squared error, mean absolute percentage error, and the correlation coefficient between the actual and the model-predicted values of surface roughness and tool life are evaluated to confirm the validity of the CBR model.

Error analysis and in-process compensation on cup wheel grinding of hard sphere

Grinding using cup wheel has been widely used in hard sphere machining process. In conventional sphere grinding (CSG), the linear velocity of the point with the same latitude on the sphere varies, which causes the sphericity error. The misalignment of the machine tool is another source of sphericity error. In this paper, these two types of sphericity errors are analyzed, and an adjustable depth of cut sphere grinding (ADCSG) is proposed to reduce the sphericity error. CSG and ADCSG were carried out on a home-made MD6050 NC precision sphere grinding machine, and the effectiveness of ADCSG is demonstrated with grinding tests. The results showed that ADCSG can reduce the sphericity error effectively compared with CSG. The sphericity error can reach less than 5 μm.

3-D numerical analysis of orthogonal cutting process via mesh-free method

In this paper, the applications of mesh-free SPH (Smoothed Particle Hydrodynamics) methodology to the simulation and analysis of 3-D hard machining process is presented. A Langrangian SPH based model is carried out using the Ls-Dyna software. Classical Lagrangian, Eulerian and ALE methods such as finite element methods (FEM) cannot resolve the large distortions very well. Conventional finite element analysis of metal cutting processes often breaks down due to severe mesh distortion. Recent developments in so called mesh-free or meshless methods provide alternates for traditional numerical methods in modeling the machining processes. SPH is a mesh-free approach, so large material deformations that happen in the analysis of cutting problem are easily managed and SPH contact control permits an “inherent” chip/workpiece separation. Because SPH combines the advantages of mesh-free, langrangian, particle methods, an alternative methodology, which appears to eliminate most of those difficulties is that of meshless methods. The orthogonal cutting process of AISI H13 steel material was modeled and analysed using SPH method. The developed SPH model gained its ability to correctly estimate the cutting forces, as illustrated in two orthogonal cutting situations. Cutting forces were compared for SPH, Langrangian explicit and experimental results. The predicted (SPH) cutting forces agree within 8.43% and 11.70% of the measured values for tangential and normal components respectively. A good agreement between predicted and experimental cutting forces was observed. Key words: Machining, cutting, mesh-free methods, meshless, SPH, Eulerian, ALE, Langrangian

Finite-Element Simulation of Conventional and High-Speed Peripheral Milling of Hardened Mold Steel

A finite-element model (FEM) with the flow stress and typical fracture is used to simulate a hard machining process, which before this work could not adequately represent the constitutive behavior of workpiece material that is usually heat treated to hardness levels above 50 Rockwell C hardness (HRC). Thus, a flow stress equation with a variation in hardness is used in the computer simulation of hard machining. In this article, the influence of the milling speed on the cutting force, chip morphology, effective stress, and cutting temperature in the deformation zones of both conventional and high-speed peripheral milling hardened mold steel is systematically studied by finite-element analysis (FEA). By taking into consideration the importance of material characteristics during the milling process, the similar Johnson–Cook’s constitutive equation with hardened mold steel is introduced to the FEM to investigate the peripheral milling of hardened mold steel. In comparison with the experimental data of the cutting force at various cutting speeds, the simulation result is identical with the measured data. The results indicate that the model can be used to accurately predict the behavior of hardened mold steel in both conventional and high-speed milling.

In-Process Recognition of Chip Forms Using Dynamic Cutting Force Components in Hard Turning

Saw-tooth chip has great effect on the dynamic cutting forces, cutting temperature waviness, PCBN tool life and surface integrity during precision hard part machining. The forming and finish process of saw-tooth chip could be observed through different high frequencies of dynamic cutting forces by wavelet analysis. According to the cutting speed, feed rate, sampling frequency and time, the characteristic parameters of saw-tooth chip type and shear instability could be calculated based on the saw-tooth chip forming frequency formula supported by M.C.Shaw theory. The forming frequency of saw-tooth chip was far smaller than high frequency of cutting forces under the normal cutting parameters during precision hard part machining process, and will be moved similar equal to each other under the high cutting speed. Experimental results and analysis show that the basic characteristics of saw-tooth chip could be calculated through dynamic cutting forces wavelet analysis.

The effect of materials testing modes on finite element simulation of hard machining via the use of internal state variable plasticity model coupled with experimental study

To understand the true nature of hard turning mechanics, a numerical model that incorporates an internal state variable plasticity model via a material user subroutine has been developed with the material constants obtained from the compression and tension tests. A global material failure/damage evolution model was implemented to simulate chip formation that solely depends on the material deformation state. Orthogonal hard turning experiments were performed to validate the numerical model. The purpose of this work was to determine the material property differences under the different stress states by using numerical simulations. The numerical and experimental results illustrated that the material constants from the compression tests captured the true nature of a hard machining process as compression dominates the of material deformation process in hard machining.

HSM strategy study for hardened die and mold steels manufacturing based on the mechanical and thermal load reduction strategy

The paper discussed cutter-work engagement situation hidden behind the mechanical and thermal load effect on cutting edges during high speed hard machining process. The engagement situation was investigated in great detail using experimental and geometrical analytic measures. Experiments were conducted using AlTiN-coated micro-grain carbide end mill cutters to cut hardened die steel. On the basis, a general high speed hard machining strategy, which aimed at eliminating excessive engagement situation during high-speed machining (HSM) hard machining, was proposed. The strategy includes the procedures to identify prone-to-overload areas where excessive engagement situation occurs and then to create a reliable tool path, which has the effect of cutting load reduction to remove the prone-to-overload areas.