End Milling Of Titanium Alloy Research Articles

An investigation into the surface integrity and cutting force characteristics in titanium alloy end milling using soluble oil and MQL as coolants

Ti–6Al–4V, a titanium alloy, is a lightweight material characterized by a relatively high strength-to-weight ratio. Due to its exceptional resistance to corrosion, this material is extensively used in the aerospace and automotive sectors. Additionally, its biocompatibility has enabled its use in the medical field. An inherent difficulty in end milling titanium alloy is its modest thermal conductivity and covalent reactivity with other compounds. The low thermal conductivity of the alloy results in elevated tool temperatures, which expedites tool wear and diminishes tool longevity. To address these issues, end milling is performed using lubricants such as minimum quantity lubrication (MQL) and soluble oil. A variety of cutting speed, feed, and depths of cut were employed during the end milling process to analyze their influence on surface integrity and tool life. Optimization of the cutting parameters was achieved using ANOVA and Taguchi methods. The cutting speed influenced the cutting force in both soluble oil and MQL as coolants. Minor tool burning was observed when using soluble oil, whereas this issue was not encountered with MQL. Additionally, MQL demonstrated a faster heat removal rate compared to soluble oil during the milling process.

Determining residual stress profile induced by end milling from measured thin plate deformation

Lots of residual stress data is usually required to support the machining process optimization of the thin-walled component. In this work, an inverse method to determine the residual stress profile for end milling titanium alloy Ti-6Al-4V is developed based on the measured thin plate deformation. Firstly, the hyperbolic tangent function is introduced to parameterize the residual stress profile of end milling. Then the mapping relationship between the residual stress profile and the bending deflection of thin plate is established. Furthermore, a solution algorithm to determine the characteristic coefficients of the residual stress profile from the measured deflection is proposed. And the residual stress profiles under different cutting conditions are inversely solved. Finally, six groups of end milling verification experiments are conducted and a high average prediction accuracy of 90.19% is obtained. The proposed reverse method can quickly obtain the residual stress profile by measuring the machining deformation of thin plate.

Prediction of cutting forces using MRA, GMDH and ANN techniques in micro end milling of titanium alloy

Micro End Milling is an specific procedure for manufacturing biomedical, automotive, naval, aerospace and mining parts especially for super alloys. Surface finish is the necessity output parameter after machining these alloys in the said applications. The study of cutting forces is mandatory to know the required surface finish to be generated on the work material. The influence of machining parameters can be investigated by experimental and predicted results that are very useful for the practitioner engineers inorder to evaluate. In this manuscript, experimental investigation of cutting forces was done and a comparison of the modelling methods - multiple regression analysis (MRA), Group method data handling (GMDH) and Artificial Neural Network (ANN) were presented. In the manuscript, the impact of input factors in machining of Ti-6Al-4 V (Grade-5) titanium alloy using uncoated tungsten carbide tools was studied on cutting forces. From the experimental interpretations, it is found that while increasing machining input parameters cutting forces on workpiece subsequently increases. After the adherences of experiments, experimental values are in good agreement with the accuracy of neural network prediction.

Experimental Investigation on Machinability of Titanium Alloy by Laser-Assisted End Milling

The Machining of titanium alloys is challenging because of their high strength, low thermal conductivity, high chemical reactivity, and high stresses at the cutting tool edges. Laser-assisted machining is an effective way to improve the machinability of titanium alloys. This paper presents an experimental investigation of the machinability of cutting force and surface roughness in laser-assisted end milling of titanium alloy Ti-6Al-4V. The absorptivity of Ti-6Al-4V was determined by conducting preheating experiments using a high-power diode laser with a wavelength of 940–980 nm. A thermal analysis was performed using the finite element method to predict temperature distribution. The depth of cut was determined where tensile strength decreased sharply, and the predicted surface temperature is presented in the analysis results. The experiments were performed with conventional machining and laser-assisted machining. Surface roughness, tool wear, and cutting force were evaluated. In contrast to the results of conventional end milling, laser-assisted end milling improved surface roughness. Moreover, laser-assisted end milling proved more effective than conventional end milling in terms of cutting tool damage. Our results proved that heat assistance significantly influenced the magnitude of the cutting forces—while the actual reduction in forces varied slightly depending on the force component, cutting tool, and cutting conditions, force components showed a reduction of roughly 13–46%.

Influence of the application of wear-resistant coatings on force parameters of the cutting process and the tool life during end milling of titanium alloys

The studies were focused on the process of end milling of VT20 titanium alloy with uncoated end milling cutters and cutters with the Ti-TiN-(Ti,Cr,Al)N and Zr-ZrN-(Zr,Cr,Al)N coatings. The investigation of the coating microstructures has revealed that the coatings have nanolayer structures, with the thicknesses of nanolayers within a range of 2–20 nm and the period λ = 75–92 nm. Curves of instantaneous cutting force components (Fp,Fx,Fy) were built. According to the results of the cutting tests, tools with the coatings under study demonstrate the tool life of 2.5–3 times higher compared to the tool life of an uncoated tool. The studies were conducted to investigate the wear and fracture patterns on the coatings during the end milling, and the differences in the processes of coating wear and fracture were revealed.

Axial contact points method for improving end-milling productivity

The article analyzes results of a study on the effects of cutting data on cutting forces when end milling titanium alloys. A solid carbide mill was used. Stability of the milling process is ensured by optimal values of axial depth of cut using the axial contact points (ACP) method. The radial depth of cut and feed were varied to achieve a required level of milling productivity. Cutting forces and vibrations were measured when milling. Vibrations were measured in the frequency and time domains. Possibilities of reducing cutting forces without decreasing the productivity level by choosing optimal values ​​of cutting parameters were studied. The practical significance of the research results for planning milling processes in real production conditions was demonstrated. Ways to improve end milling productivity for titanium alloys by reducing loads on the technological system were identified. Avenues for further research on high-productivity end milling of titanium alloys were proposed.

Tool Quality Life during Ball End Milling of Titanium Alloy Based on Tool Wear and Surface Roughness Models

The prediction and control of milling tool service performance is critical for milling tool design and machining. However, the existing prediction model can hardly quantify tool performance, or precisely describe the relationship between the tool performance and the design or milling parameters. This study redefines the tool lifetime as a function of surface roughness and proposes a new geometric analysis method based on a time-varying wear model. The proposed method can be utilized to evaluate the relationship between tool wear and lifetime. The surface roughness, with respect to tool service performance, is expressed as a time-varying model of the tool and processing parameters. After experimental validation, the influence factors were analyzed through simulation. A generalized method for milling tool design was proposed and successfully applied to a tool performance design case, on a theoretical level. Additionally, the research results prove that basing the tool milling quality life on the surface roughness is extremely feasible and necessary.

Machining time and quadratic mean roughness optimization in ball end milling of titanium alloy Ti-6Al-4V – Aeronautic field

The main goal of this work is to optimize the quadratic mean roughness Rq and the machining time T in ball end milling of the Titanium alloy Ti-6Al-4V. The Taguchi method was applied in this research in order to analyze the impact of each milling parameter on the surface roughness and the machining time. In fact, an orthogonal array L9, a signal to noise ratio S/N analysis and Pareto ANOVA were used to select the optimum levels combination of the milling parameters and to investigate the impact of each milling parameters on the machining time and surface roughness.

Effects of tool vibration on surface integrity in rotary ultrasonic elliptical end milling of Ti–6Al–4V

Titanium alloys have been applied in aerospace, biomedical, and chemical industries due to their superior mechanical properties. As a novel machining method, rotary ultrasonic elliptical machining has been successfully introduced into high-speed side milling of Ti–6Al–4V recently. However, the surface integrity in end milling of titanium alloy using this method is still unclear. In this study, a comprehensive experiment on surface integrity in rotary ultrasonic elliptical end milling of Ti–6Al–4V was conducted at various vibration amplitudes and cutting speeds. Results show that regular substantial micro-vibration textures in the form of separated ridges are obtained on the machined surfaces in RUEEM. Surface roughness values rise from Ra 0.160 μm to Ra 0.758 μm with the increasing cutting speed and vibration amplitude. Both the thickness of subsurface deformed layer and the value of surface micro-hardness increase with rising amplitude at low cutting speeds, while the hardening effect gradually weakens as the cutting speed increases to 160 m/min. Besides, the values of surface compressive residual stress gradually decrease with vibration amplitudes at low cutting speeds, while opposite trends show at the high cutting speed (160 m/min). This study can provide a new method for the effective control of the surface integrity for high-speed end milling of titanium alloy.

Tool Wear Estimation in End Milling of Titanium Alloy Using NPE and a Novel WOA-SVM Model

Accurate identification of the tool wear states in machining of titanium alloys continues to be a thorny problem. Rapid construction of accurate and effective tool wear predictive models with regard to various titanium alloys is indispensable for promoting the development of intelligent manufacturing. This article presents a novel WOA-SVM model that integrates support vector machine (SVM) and whale optimization algorithm (WOA), which is utilized for accurate estimation of the tool wear in end milling of titanium alloy Ti-6Al-4V under variable cutting conditions. The signal features in three domains are extracted from the original cutting forces and constitute the “complete features” that are adopted as the monitoring features. Besides, neighborhood preserving embedding (NPE) is utilized to fuse the monitoring features and realize dimension reduction, which aims at improving the modeling efficiency of the novel WOA-SVM model. The experimental results show that under the premise of guaranteeing prediction accuracy, the utilization of NPE reduces the modeling time-consumption of WOA-SVM by more than 90%. In comparison with the commonly used methods (such as PSO-SVM and GSA-SVM), WOA-SVM takes on comparable prediction accuracy and can reduce the modeling time-consumption by more than 30% in most cases. Moreover, the WOA-SVM model has better prediction accuracy and stability than other classical methods, such as k-nearest neighbor (k-NN), feedforward neural network (FFNN), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and classification and regression tree (CART). Therefore, the combination of NPE and WOA-SVM provides a guarantee for rapidly constructing accurate tool wear predictive models in machining of titanium alloys.

Increase in Efficiency of End Milling of Titanium Alloys Due to Tools with Multilayered Composite Nano-Structured Zr-ZrN-(Zr,Al)N and Zr-ZrN-(Zr,Cr,Al)N Coatings

The study deals with an increase in the tool life parameter for metal-cutting tools and efficiency of end milling for titanium alloys, due to the use of tools with multilayered composite nano-structured Zr–ZrN–(Zr,Al)N and Zr–ZrN–(Zr,Cr,Al)N coatings, deposited through the technology of the filtered cathodic vacuum arc deposition (FCVAD). The studies included the microstructured investigations using SEM, the analysis of chemical composition (Energy-dispersive X-ray spectroscopy, EDXS), the determination of the value of critical failure force (with the use of scratch testing), and the measurement of the microhardness of the coatings under study. The cutting tests were conducted in end milling of titanium alloys at various cutting speeds. The mechanisms of wear and failure for end milling cutters with the coatings under study were studied in milling. The studies determined the advantages of using a tool with the coatings under study compared to an uncoated tool, as well as to tools with the commercial Ti–TiN coating and the nano-structured Ti–TiN–(Ti,Al)N coating. Adding Cr to the composition of the coating can significantly increase the hardness, while the coating retains sufficient ductility and brittle fracture resistance, which allows for a best result when milling titanium alloys.

A hybrid modelling approach towards prediction of cutting forces in micro end milling of Ti-6Al-4V titanium alloy

Prediction of cutting forces in micro end milling is a key aspect for both quality of machining surface and safety of the tool. Further, estimation of cutting coefficients is very much crucial for precise prediction of actual cutting forces. In general, these are obtained by cutting calibration experiments which consume lot of energy and resources. So, to overcome such impediments and to accomplish a purely analytical modelling, this study proposes a hybrid approach for prediction of cutting forces in micro end milling of titanium alloy Ti-6Al-4V. Preliminarily, cutting force coefficients have been evaluated by using finite element simulation considering orthogonal cutting of Ti-6Al-4V using round edge carbide tool. Johnson-Cook material model has been considered for the flow stress calculation in finite element (FE) analysis. Cutting force coefficients have been extracted by simulating the cutting process for a series of undeformed chip thickness (UCT). Finally, mechanistic cutting force model is developed by integrating the small elemental cutting force by incorporating the extracted cutting force coefficients. An improved UCT algorithm which can be used for both lower and higher value of tool run out efficiently is implemented by considering trochoidal trajectory of tool centre, tool run out, minimum chip thickness and elastic recovery and trajectories of all the preceding teeth for one complete revolution of the tool. To validate the proposed model, cutting force experiments have been carried out and results are compared. A comparative analysis shows a very good agreement between predicted and experimental cutting forces.

Improving the performance of end milling of titanium alloys by using tools with multilayer composite nanostructured coatings Zr-ZrN-(Zr, Al) N and Zr-ZrN-(Zr, Cr, Al)N

Improving the performance of end milling of titanium alloys by using tools with multilayer composite nanostructured coatings Zr-ZrN-(Zr, Al) N and Zr-ZrN-(Zr, Cr, Al)N

Tool Wear Analysis of Micro End Mills - Uncoated and PVD Coated TiAlN & AlTiN in High Speed Micro Milling of Titanium Alloy - Ti-0.3Mo-0.8Ni

Titanium and its alloys are used in many applications like bio-medical, marine, automotive and aerospace. Inorder to achieve desired surface finish without traditional coolants, investigation of micro end mills wear analysis in high speed micro end milling process is essential. Micro end mill performance while machining can be evaluated using cutting force analysis. In this paper tool wear investigation of uncoated & PVD coated AlTiN, TiAlN tungsten carbide end mills in high-speed micro end milling of Titanium Alloy - Grade 12 (Near Alpha) - Ti-0.3Mo-0.8Ni- under dry cutting conditions was presented. The present investigation was also supported by the cutting force analysis. Tool wear observation was done by SEM analysis. EDX analysis was performed to know the material constituents and wear mechanisms on the cutting tool tip. It is found that diffusion, oxidation, adhesive and abrasive wear mechanisms were the major phenomena taking place on the cutting edge of micro end mills. From the comparison of cutting tools for machining Titanium Alloy-Grade 12, it was found that uncoated tools performed better than AlTiN and TiAlN tungsten carbide tools.

Relationship between Cutting Heat and Tool Edge Temperature in End Milling of Titanium Alloy

In this study, tool edge temperature was measured by a two-color pyrometer with an optional fiber. During one revolution of spindle, the tool edge passes over the fine hole at workpiece after cutting workpiece. An optical fiber inserted into the fine hole transmits infrared ray radiated from tool edge to two detectors with different spectral sensitivities. One peak signal from each detector can be obtained by each spindle revolution. The tool edge temperature can be calculated by taking the ratio of outputs from these two detectors. The relation between cutting heat calculated from cutting force and tool edge temperature was discussed. The tool edge temperature at the same cutting heat could be compared. The wet cutting condition caused lower tool edge temperature than the others at the same cutting heat. MQL and dry showed almost same tool edge temperature. The dispersion of tool edge temperature in wet cutting is wider than that in dry cutting and MQL cutting.

Experimental Investigation and Estimation of Surface Roughness using ANN, GMDH & MRA models in High Speed Micro End Milling of Titanium Alloy (Grade-5)

In this paper, experimental investigation and estimation of surface roughness using optimization techniques -Artificial Neural Network (ANN), Group method data handling (GMDH) and multiple regression analysis (MRA) inhigh speed micro end milling of titanium alloy (grade-5)were presented. A comparative study was made to know the influence of spindle speed, feed and depth of cut on surface roughness of Ti-6Al-4V-titanium alloy. From the observations, it is clearly seen that prediction accuracy of neural network is higher than other techniques that is in good agreement with experimental values.

An experimental study on end milling of titanium alloy (Ti-6Al-4V) under dry and minimum quantity lubrication conditions

This paper presents the results of an optimisation study of low speed machining of Ti-6Al-4V alloy by technique of order preference by similarity to ideal solution (TOPSIS). End milling was conducted under dry and minimum quantity lubrication (MQL) conditions and at different levels of cutting speed (20 to 40 m/min), feed (0.05 to 0.15 mm/rev) and axial depth of cut (0.4 to 1.2 mm) using a full factorial design. Machinability was evaluated by measuring surface roughness and cutting forces. The micro-hardness below the machined surface for some selected combinations of cutting conditions was also measured. It was found that the feed per rev and depth of cut have the greatest influence on cutting forces and surface roughness under dry and MQL conditions. The minimum cutting forces and minimum surface roughness are obtainable at cutting speed of 30 mm/min, feed of 0.05 to 0.1 mm/rev and depth of cut of 0.4 mm under MQL condition. It was also found that these conditions result in the minimum alteration of micro-hardness beneath the machined surface.

An experimental study on end milling of titanium alloy (Ti-6Al-4V) under dry and minimum quantity lubrication conditions

This paper presents the results of an optimisation study of low speed machining of Ti-6Al-4V alloy by technique of order preference by similarity to ideal solution (TOPSIS). End milling was conducted under dry and minimum quantity lubrication (MQL) conditions and at different levels of cutting speed (20 to 40 m/min), feed (0.05 to 0.15 mm/rev) and axial depth of cut (0.4 to 1.2 mm) using a full factorial design. Machinability was evaluated by measuring surface roughness and cutting forces. The micro-hardness below the machined surface for some selected combinations of cutting conditions was also measured. It was found that the feed per rev and depth of cut have the greatest influence on cutting forces and surface roughness under dry and MQL conditions. The minimum cutting forces and minimum surface roughness are obtainable at cutting speed of 30 mm/min, feed of 0.05 to 0.1 mm/rev and depth of cut of 0.4 mm under MQL condition. It was also found that these conditions result in the minimum alteration of micro-hardness beneath the machined surface.

The prediction of cutting force in end milling titanium alloy (Ti6Al4V) with polycrystalline diamond tools

Cutting force coefficients were conventionally described as the power function of instantaneous uncut chip thickness. However, it was found that the changes in the three controllable machining parameters (cutting speed, feed and axial cutting depth) could significantly affect the values of cutting coefficients. An improved cutting force model was developed in this article based on the experimental investigation of end milling titanium alloy (Ti6Al4V) with polycrystalline diamond tools. The relationships between machining parameters and cutting force are established based on the introduction of the new cutting coefficients. By integrating the effects of varying cutting parameters in the prediction model, cutting forces and the fluctuation of cutting force in each milling cycle were calculated. Validation experiments show that the predicted peak values of cutting forces highly match the experimental results; the accuracy of the model is up to 90% in predicting instantaneous cutting forces.

Improving the performance of milling of titanium alloys using the atomization-based cutting fluid application system

The research presented in this paper investigates the effectiveness of the atomization-based cutting fluid (ACF) spray system in end-milling of titanium alloy, Ti–6Al–4V. To that end, the study has been conducted in two phases. In the first phase, experiments have been carried out to select suitable spray parameters. A numerical model of the ACF spray system has also been developed to gain a physics-based understanding of the cutting fluid film formation on a rotating tool surface and its role in providing cooling and lubrication at the cutting interface. In the second phase, experiments have been conducted to compare the machinability of titanium for different cutting fluid application methods, viz., dry cutting, flood cooling and ACF spray system, on the basis of five machinability parameters, including, tool life, tool wear, cutting forces, surface roughness and chip morphology. Experimental results show that the application of the ACF spray system results in uniform tool flank wear, lower cutting forces and higher surface finish and the tool life extends up to 75% over flood cooling. Additionally, chip morphology analysis reveals that using ACF spray system leads to the formation of shorter and thinner chips, as compared to those when flood cooling is used.