Machining Of Ti6Al4V Research Articles

Investigating the efficiency of mixtures based on supercritical CO2 and lubricants by friction tests under conditions similar to the machining of Ti6Al4V

New supercritical carbon dioxide (scCO2)-based cutting fluids combining the cooling from scCO2 and lubrication from various additives are investigated in this study. Selected components, including ionic liquids, vegetable and mineral oils, water, and PEG, were introduced into supercritical CO2, and tribological tests were performed on a CNC lathe to analyze their influence on Ti6Al4V/WC-Co contact. Forces and temperatures were recorded to compare the perfomances of the scCO2-lubricant mixtures for future use in machining. The analysis of the apparent friction coefficient and sticking zone showed a noticeable decrease by ionic liquids when combined with scCO2 at a speed of 100 m/min and 4 mL/min delivery flow rate. The other lubricants (water and PEG vegetable oils) performed similarly to standard mineral oil and are less expensive, which could help in developing future low-cost yet effective cooling and lubrication methods for the machining industry.

Enhancing orthogonal finishing machining of Ti6Al4V with laser-ablated tool geometry modifications

Finishing machining of Ti6Al4V, known for its high strength and heat conduction resistance, demands optimisation to achieve high-quality end products. This study explores modifying the chip contact length on the rake face and altering the flank face with a cavity to minimise process forces and temperatures while maintaining cutting edge integrity. The research validates the manufacturability of ultra-short pulsed laser-ablated tool geometry modifications, indicating potential for industrial scale-up. Extensive experimental evaluations under dry conditions assess the impact of tool modifications at various feed rates for planing and turning. Significant reductions in process forces and temperatures were observed with rake face modifications, particularly at a cavity distance of approximately 34 µm. Ideal performance was noted for feed rates between 0.035 and 0.045 mm for planing and 0.040 to 0.045 mm/rev for turning. Smoothed Particle Hydrodynamics (SPH) simulations employing a Johnson-Cook material model were used to analyse chip formation and to predict the process forces. These simulations revealed a clear change in the chip formation and lower process forces and temperatures. The SPH results closely matched experimental outcomes, with a discrepancy of less than 7 % in cutting forces for both tool types, although feed forces were underestimated by about 50 %. The effect of the tool modification is reflected accurately at the respective feeds.

An Attempt for Numerical Optimisation of a Micro-Groove Geometry at The Rake Face When Turning Ti6Al4V Alloy with Indexable Inserts

Machining of Ti6Al4V is considered difficult because the material removal rates are relatively small if the tool wear shall be low. In recent years the reduction of process forces as well as tool wear have been investigated by introducing textures (pockets) into the tool surface. To advance the understanding how those textured tools function and to reduce the experimental effort, a smoothed particle hydrodynamics (SPH) model of the orthogonal cutting process with a parametrised tool containing a single pocket on the rake face with variable position and depth is presented. This simulation model is used to enhance the understanding of rake face textures in order to design optimum cutting tools for given process parameters. Using an optimisation algorithm, an optimum texture geometry is determined numerically and is then experimentally validated, followed by a discussion, why process force reductions are lower than predicted.

The effect of graphene solution on mixed powder electrical discharge milling of Ti6Al4V

Abstract Ti6Al4V is the most widely used materials in aerospace, medical, nuclear power and other fields. However, due to its unique properties such as low thermal conductivity, titanium alloy poses challenges in machining processes. Electrical discharge milling (EDM) is a machining method that utilizes the electrical corrosion phenomenon of pulsed spark discharge between two electrodes to remove materials, which is highly suitable for the machining of Ti6Al4V. This paper investigates a mixed powder EDM approach for titanium alloy using a graphene solution medium known for its green and sustainable characteristics. Compared to conventional deionized water medium processing which without powder particles, the material removal rate can be increased by 50%, the surface hardness after processing was 2.5 times higher than that of the substrate, the electrode wear rate could be reduced by 40%, the surface roughness values were reduced by more than 20%. Besides that, the micro-cracks and micro-pores on the workpiece surface can be significantly reduced. Subsequently, single factor experiments and orthogonal experiments were conducted using material removal rate, electrode wear rate, and surface roughness as process indicators. The influence of processing parameters on process indicators was investigated based on optimal selection method and analysis of variance (ANOVA). Finally, the optimized parameters in graphene solution mixed powder EDM for Ti6Al4V were obtained. When using the process combination A3B3C1D2, the maximum MRR can be obtained.

A FEM-based coupled thermo-mechanical model of laser-assisted machining of Ti6Al4V—a focus on chip morphology

A FEM-based coupled thermo-mechanical model of laser-assisted machining of Ti6Al4V—a focus on chip morphology

Machinability of Ti6Al4V Alloy: Tackling Challenges in Milling Operations

This study investigates strategies for improving the 3D milling of Titanium Alloy Grade 5 (Ti6Al4V) by optimizing machining parameters and cutting tool engagement techniques. Ti6Al4V presents significant machining challenges due to its low machinability index (20%), which directly impacts manufacturing efficiency. High temperatures during machining, often exceeding 8820C, lead to phase transformations, creating a harder Beta lamellar equiaxed microstructure. This, coupled with the alloy's poor thermal conductivity, results in heat concentration at the cutting tool interface, accelerating thermo-chemical wear and potentially catastrophic tool failure. This study explores how controlled cooling methods, coupled with appropriate lubrication, can effectively dissipate heat and flush away chips, mitigating the detrimental effects of high temperatures. Furthermore, the selection of cutting tool materials and coatings with high thermal conductivity and chemical inertness, along with aggressive rake angles and higher relief angles, are examined as methods to improve shearing, minimize smearing, and enhance surface quality. By optimizing these parameters, this study aims to provide manufacturers with practical strategies to overcome the challenges of Ti6Al4V machining, ultimately increasing tool life and overall milling efficiency.

A thermo-mechanical fully coupled model for high-speed machining of Ti6Al4V

PurposeThis study aims to further refine the model, explore the influence of cutting parameters on the machining process, and apply it to practical engineering to improve the efficiency and quality of titanium alloy machining.Design/methodology/approachThis paper establishes a comprehensive thermo-mechanical fully coupled orthogonal cutting model. This paper aims to couple the modified Johnson–Cook constitutive model, damage model and contact model to construct a two-dimensional orthogonal cutting thermo-mechanical coupling model for high-speed cutting of Ti6Al4V. The model considers the evolution of microstructures such as plastic deformation, grain dislocation rearrangement, dynamic recrystallization, as well as stress softening and hardening occurring continuously in Ti6Al4V metal during high-speed cutting. Additionally, the model incorporates friction and contact between the tool and the workpiece. It can be used to predict parameters such as cutting process, cutting force, temperature distribution, stress and strain in titanium alloy machining. The study establishes the model and implements corresponding functions by writing Abaqus VUMAT and VFRICTION subroutines.FindingsThe use of different material constitutive models can significantly impact the prediction of the cutting process. Some models may more accurately describe the mechanical behavior of the material, thus providing more reliable prediction results, while other models may exhibit larger deviations. Compared to the Tanh model, the proposed model achieves a maximum improvement of 8.9% in the prediction of cutting force and a maximum improvement of 20.9% in the prediction of chip morphology parameters. Compared to experiments, the proposed model achieves a minimum prediction error of 2.8% for average cutting force and a minimum error of 0.57% for sawtooth parameters. This study provides a comprehensive theoretical foundation and practical guidance for orthogonal cutting of titanium alloys. The model not only helps engineers and researchers better understand various phenomena in the cutting process but also serves as an important reference for optimizing cutting processes.Originality/valueThe originality of this research is guaranteed, as it has not been previously published in any journal or publication.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0168/

Sustainable high-speed milling enhancement of GnP-reinforced titanium nanocomposites under dry environment

No studies have been done on using graphene nanostructure reinforcement material to improve titanium alloy's dry high-speed machining performance, which is crucial for green manufacturing. This study seeks to understand the impact of graphene on improving the high-speed machining of Ti6Al4V (Ti64) nanocomposites. High-density Ti64-based nanocomposite samples with varying amounts of GnPs (0 wt%, 0.6 wt%, 1.2 wt%, and 2.4 wt%) were fabricated using ball milling and HFIHS sustainable technologies. Subsequently, a detailed investigation was conducted to examine the impact of the GnP contents on high-speed milling performance, namely, cutting force components, surface quality, and machined surface and subsurface microhardness. The variable milling parameters include the cutting speed and feed rate. The results showed that the inclusion of GnPs significantly affected the dry high-speed milling of the nanocomposites. The nanocomposites containing 1.2 wt% and 2.4 wt% of GnP-Ti64 exhibited lower cutting forces than the base-Ti64 without GnP (0 wt% Gnp). At a 100 m/min cutting speed, the cutting and feed forces decreased by 35% and 44%, respectively, compared to the base-Ti64 specimens. This is attributed to lower machining friction due to the presence of graphene and TiC (formed due to the reaction of Ti and GnP particles during sintering) at grain boundaries, facilitating material removal and reducing cutting force. Although the nanocomposites had a higher microhardness, they all showed improved surface quality in comparison to the base-Ti64 specimens. For example, at a feed rate of 270 mm/min the nanocomposites contain 0.6 wt%, 1.2 wt%, and 2.4 wt.% GnPs showed roughness reductions of 6%, 27%, and 38%, respectively, compared to the base-Ti64. Regarding surface and sub-surface hardness after machining, the 2.4 wt.% GnP samples showed superior performance in terms of minimal post-milling hardness variations compared to the base hardness of the material. All GnP-Ti64 milled specimens showed considerably improved surface morphology compared to the base-Ti64 machined specimens. Overall, the nanocomposites containing 1.2 wt% and 2.4 wt% GnPs are strong contenders for reducing cutting forces, enhancing surface roughness, and lowering the fluctuations in microhardness, leading to green manufacturing.

Effects of discharge current and discharge duration on the crater morphology in single-pulse arc machining of Ti6Al4V

Effects of discharge current and discharge duration on the crater morphology in single-pulse arc machining of Ti6Al4V

Effects of machining parameters, ultrasonic vibrations and cooling conditions on cutting forces and tool wear in meso scale ultrasonic vibrations assisted end-milling (UVAEM) of Ti–6Al–4V under dry, flooded, MQL and cryogenic environments – A statistical analysis

Ti–6Al–4V, an alloy of titanium has recently gained focus of research to overcome its machinability challenges. Miniaturization in devices has forced a shift towards micro and meso-scale machining. Sustainability and green manufacturing concepts have shifted focus in machining from cutting fluids towards modern cooling approaches to minimize or eliminate them. In present research, cutting forces & tool wear in Ultrasonic Vibrations Assisted End Milling of Ti–6Al–4V at meso-scale under Dry, Flooded, Minimum Quantity Lubrication & Cryogenic cooling have been analyzed to develop optimum machining parameters. Taguchi L16 orthogonal array was designed to perform experiments keeping Cutting Speed, Feed per tooth, Depth of cut, Ultrasonic vibrations amplitude & Cooling environment as inputs. ANOVA was used to analyze contribution ratios by these parameters towards cutting forces & tool wear. Results indicated that machining conditions, cooling environment and Ultrasonic Vibrations influence cutting forces & tool wear. Depth of cut had the highest influence with 63.41% contribution towards cutting forces while cutting speed remained the highest influencing factor with 39.86% contribution towards tool wear. Cutting forces were reduced by 33.49%, 16.93% and 4.91% while tool wear was reduced by 26.43%, 9.48% and 5.17% under Minimum Quantity Lubrication environment compared to dry, flooded and cryogenic cooling respectively. Cutting forces and tool wear under ultrasonic vibrations were reduced by 24.52% and 13.16% respectively as compared to Conventional Machining (CM). For optimum results, Minimum Quantity Lubrication with low Cutting Speed, Depth of cut, Feed per tooth and high amplitude of ultrasonic vibrations is recommended to machine Ti–6Al–4V.

Sustainable approach for machining of Ti6Al4V using micro-pillar textured turning tool insert

The use of cutting fluids (CF) in metal cutting is questioned due to environmental and biological impacts, encouraging the adoption of dry machining to minimize these effects. However, dry machining accelerates tool wear, particularly in difficult-to-machine materials like Titanium and Nickel alloys. Approaches, such as rake surface texturing, address this challenge and promote sustainability in metal cutting. This study explored the impact of an innovative micro-pillar texture pattern fabricated using a combination of Laser Beam Micro Machining (LBμM) and Reverse Micro Electrical Discharge Machining (RμEDM) for the dry machining of Ti6Al4V. The investigation considers various parameters, including tool wear, contact length, titanium adhesion, cutting forces, cutting temperature, and chip morphology. An indirect approach was adopted to estimate the temperature of the tool tip using the temperature measured at a distant location. Implementing the textured tool with 15 μm deep micro-pillars in the dry machining of Ti6Al4V exhibited the best overall performance for various responses. A notable reduction of more than 40% for both tool-chip contact length and titanium adhesion, compared to a plain tool, indicated a perceptible decrease in the seizure zone at the interface. Moreover, the textured tools demonstrated a remarkable maximum reduction of 56.4% in flank wear, ensuring the prolonged retention of a sharp cutting edge. The responses for contact length, adhesion, and flank wear contributed to an 18.8% decrease in cutting force and a substantial 45.7% reduction in thrust force. Force analysis further confirmed the directional independence of the texture pattern. Under the influence of surface texturing, chip morphology changed to shorter, untangled, and tightly curled, with a 30.8% reduction in curl radius. A theoretical estimation based on the minimum energy approach was also performed to demonstrate an increment in the shear plane angle.

Investigation of friction modeling on numerical Ti6Al4V cutting simulations

Friction significantly influences chip formation, thereby highlighting its modeling critical in numerical cutting simulations. Notably, issues like the underestimation of feed force in simulations are often attributed to inadequate friction models. Nevertheless, diverse conclusions in the literature regarding friction’s behavior complicate the accurate implementation of this input. Additionally, the enormous number of the available friction models and their varied calibration methods introduce further debates over which aspects of friction modeling should receive more focus. These controversies and deficiencies hinder progress in further understanding friction’s role in chip formation through numerical studies. Instead of proposing or calibrating new friction models, the current study, based on Ti6Al4V machining simulations, attempts to readdress the aforementioned controversies in a neutral stance by conducting sensitivity studies using a hybrid Smoothed Particle Hydrodynamics (SPH) - Finite Element Method (FEM) solver with Graphics Processing Units (GPU) acceleration, which is capable of efficiently executing high-resolution computations. The significant impact of friction particularly at the end of the tool-chip contact on the chip formation, physical contact states and process forces are highlighted. The behaviors of physical parameters including normal contact pressure, sliding velocity, and temperature-dependent friction models in the literature are also evaluated. Several aspects such as the shear flow stress limit, the relationship between friction and process forces, and the selection of different models are discussed. In conclusion, pragmatic recommendations for friction modeling and cutting simulation work are provided. On the one hand, the available complex physical parameter dependent friction models could not prove their necessity and should be approached cautiously. Instead, the constant Coulomb friction model without the shear stress limit, despite its simplicity, demonstrates effective and sufficient for a single set of metal cutting simulations. On the other hand, reliable on-site measurement techniques of the coefficient of friction (COF) at the tool-chip sliding contact area should be developed, with consideration of the contact length and the state of material flow. Combined with careful cutting edge preparation and suitable constitutive models, the overall accuracy of numerical cutting simulations including the feed force prediction is expected to be improved.

A novel finite element model for thermally induced machining of Ti6Al4V

Titanium alloys, including Ti6Al4V, are considered hard to cut materials due to their low thermal conductivity, low elastic modules and high chemical reactivity. This leads to high cutting forces and high surface roughness. Thermal assisted machining is used to improve the machinability of Ti6Al4V. To improve the performance of thermal assisted machining, this study investigates how are the cutting force, cutting zones temperatures, chip morphology, shear plane angle and strain rate are affected by the cutting speed and the heating element characteristics during thermally assisted machining of Ti6Al4V. A 2D numerical model simulating orthogonal cutting process was created using ABAQUS/Explicit software. In this model, Johnson Cook constitutive model was used to describe the material behavior during cutting process. Also, Johnson Cook damage model was used to simulate chip separation mechanism. After the verification of the model by comparison with results found in the literature, a number of simulations were run at different levels of four factors: cutting speed (40, 60, 80, 100, 120 and 140 m/min), heat source temperature (200, 400 and 600 °C), heating source distance from the cutting tool (0.3, 0.6 and 0.9 mm) and heating source size/diameter (0.6, 0.8 and 1 mm). Taguchi L18 orthogonal mixed level design was used to plan for simulation runs using Minitab software. ANOVA analysis was used to investigate the significance of the four factors. The response table of means and the main effect of means are used to compare between the four factors and find their ranking. Based on 95% confidence Interval (CI), the results show that cutting speed has a significant effect on cutting force, strain rate, chip compression ratio, cutting tool nose temperature, cutting tool and chip temperature in the secondary deformation zone, average chip thickness at peaks and average chip thickness at valleys and average pitch. This conclusion is based on the P-values which are << 0.05 and the contribution which reaches 99.01%. Similarly, based on P-values (< 0.05) and contributions (up to 12.16%), the heating source temperature has a significant effect on average chip thickness at valleys, chip compression ratio and strain rate. The cutting speed has Rank 1 among the four factors affecting cutting force, cutting zones temperatures, chip morphology, shear plane angel and stain rate. The effect of instantaneous heating directly before cutting process is negligible compared to the effect of plastic deformation and fracture mechanism in the cutting zone.

Thermo-metallo-mechanical based phase transformation modeling for high-speed milling of Ti–6Al–4V through stress-strain and temperature effects

The optimization of machining parameters, tool longevity, and surface quality in High-Speed Milling (HSM) of Ti–6Al–4V relies immensely on understanding the local phase transformation. This study endeavors to build a Finite Element (FE) model capable of forecasting phase alterations during the rapid thermal fluctuations intrinsic to Ti–6Al–4V machining. Dynamic phase transformation models were initially introduced to capture rapid heating and cooling phenomena. Using a user-defined subroutine, the phase transitions predictive models were integrated into the HSM simulation within Abaqus/Explicit. Simulation outcomes unveiled phase transitions primarily occurring within the serrated chip and at the tool-workpiece interface. Notably, during rapid heating, when the cutting speed increased to 350 m/min, the β-phase volume fraction surged from 7.5 to 96.38%. A similar trend was observed with feed rate adjustments (i.e., 0.15–0.25 mm/tooth), where β-phase increased from 7.5 to 67.84%. Rapid cooling facilitated the reversion of the transformed β-phase back into the α'-phase. Finally, some advanced characterization techniques were employed to validate the developed thermo-metallo-mechanical coupled FE model for phase transformation. The simulation results verified by the experimental data promotes a better understanding of phase alteration mechanisms and microstructural evolution in HSM of Ti–6Al–4V. The current research is also beneficial for crucial insights into optimizing the machining conditions and their impact on tool-material interactions and surface integrity.

Scale-dependent wetting behavior of bioinspired lubricants on electrical discharge machined Ti6Al4V surfaces

The relationships between the geometric features of material surfaces and topographically related phenomena, such as wetting, change with the scale of observation. In these studies, multiscale analyzes allow characterizing the relationships between electrical discharge machining parameters, complex surface topographic structures and contact angles. Importantly, it was possible to indicate the best scales for observing the phenomena of lubricant flow on electro-discharged surfaces and to identify key geometric parameters of the surface affecting the contact angle. This paper proposes scale-dependent contact angle analyzes of electro-discharge machined Ti6Al4V alloy for biomedical implant applications. Liquids imitating synovial fluid in joints were used as lubricants. The research focuses on comparing the impact of discharge energy on surface microtexture, chemical composition, contact angle and surface free energy. The analysis of the lubrication behavior on micro-textured surfaces in contact mechanics co-determines the tribological properties. The research results confirm the effectiveness of modeling the specific wettability of implant surfaces with bioinspired lubricants.

Comparative investigation and optimization of cutting tools performance during milling machining of titanium alloy (Ti6Al4V) using response surface methodology

The purpose of this paper is to study the optimization of the cutting performance of three different cutting inserts, during the machining operation of titanium alloy (Ti6Al4V) by making use of the response surface methodology (RSM) on a computer numerical control (CNC) milling. The cutting tools employed for the optimisation of the cutting performance during machining operation are silicon, aluminium, oxygen, nitrogen (SiAlON), cubic-boron nitride and carbide cutting inserts. Scanning electron microscope (SEM) was used for the determination of the tool wear for the cutting inserts being compared during machining of Ti6Al4V, and the cutting parameters, which are cutting speed (Vc), feed per tooth (fz) and depth-of-cut that were evaluated from the cutting tools as per the manufacturer’s design specifications. The determination of the tool wear on the cutting inserts was achieved by using the SEM, while the machining operation for the experimental trails was performed from the CNC milling machine, where face milling operation was executed. The optimization process showed that carbide cutting inserts yielded the best performing results and were considered the most significant choice of cutting insert in machining Ti6Al4V when compared to SiAlON and CBN cutting inserts. This choice was from the cutting tool life obtained where a cutting tool life of 29 min was obtained from a use of carbide cutting inserts; 28 min resulted from a use SiAlON cutting inserts and 26 min from a use of CBN cutting inserts. This work finds appropriate value in assisting the machinists in the selection of the best most performing and cost-effective cutting tool.

Sustainability assessment of electron beam melted Ti6Al4V machining: energy consumption and lubricant use

ABSTRACT Electron Beam Melting (EBM) is typically used to produce high performance titanium parts, but it falls short in ensuring the high surface finishing always requested for aerospace applications, and this leads to the need of a post-building finishing resulting in additional resources and energy consumption. An optimization of the post-processing is necessary and the literature lacks guidelines in this regard. In this study, 18 cylindrical samples were produced by EBM and then postprocessed by wet and dry turning by using the same process parameters. Surface roughness, tool wear rate, specific cutting energy and energy consumption were investigated and compared to understand the best compromise to remove the same total depth of cut (2.4 mm). Results showed that dry turning can result in saving up 9% in total energy consumption. Also, feed rate and depth of cut can be varied by fixing the spindle speed without significantly affecting surface roughness by saving up to 73% in total energy consumption.

An investigative study on the parameters optimization of the electric discharge machining of Ti6Al4V

&lt;abstract&gt; &lt;p&gt;This investigative study explored the field of electrical discharge machining (EDM), with a particular focus on the machining of Ti6Al4V, a titanium alloy that finds widespread application in aerospace, airframes, engine components, and non-aerospace applications such as power generation and marine and offshore environments. Ti6Al4V presents difficulties for conventional metal cutting techniques because of high cutting forces, poor surface integrity, and tool wear. This has led to the adoption of unconventional techniques like EDM. However, problems like high electrode wear rates, low material removal rates, long machining times, and less-than-ideal surface finishes still exist, especially in large-scale applications. By addressing the particular difficulties associated with large-scale electrical discharge machining and by putting forth a multi-objective optimization strategy, this research makes a substantial contribution to the field. With an emphasis on the optimization of input parameters like pulse on time (T&lt;sub&gt;on&lt;/sub&gt;), pulse off time (T&lt;sub&gt;off&lt;/sub&gt;), voltage (HV), and current (LV), which are critical in large-scale industrial applications, the study attempts to evaluate the optimal parameter states that simultaneously accomplish multiple goals during the machining process. This work is the first to simultaneously optimize all relevant output responses, such as material removal rate (MRR), electrode wear rate (EWR), machining time (Tm), surface roughness (Ra), and base radius. Previous studies have concentrated on one or two output responses. To optimize MRR, EWR, Tm, Ra, and base radius, the experiments were carefully planned using design of experiment (DOE) and response Surface methodology (RSM). Regression analysis and ANOVA are two statistical techniques that were used with Minitab 15 to help interpret experimental data and build a solid regression model specifically for Ti6Al4V. Throughout the experiment, a variety of input factor settings were employed, and the responses to those were noted. The following parameters were used to obtain the experimental data: current (LV) at 30 and 50 A, voltage (HV) at 0.3 and 0.7 V, pulse on time (T&lt;sub&gt;on&lt;/sub&gt;) at 4 and 6.5 µs, and pulse off time (T&lt;sub&gt;off&lt;/sub&gt;) at 5.5 and 6.5 µs. T&lt;sub&gt;on&lt;/sub&gt; and current are the most significant variables that influence most of the output responses. By addressing the simultaneous optimization of multiple output responses, this investigative study not only sets a new standard in the field but also identifies current bottlenecks and offers solutions.&lt;/p&gt; &lt;/abstract&gt;

Assessment of Machinability of Ti6Al4V Alloy Under Dry Conditions

Titanium alloys pose significant challenges during machining, necessitates a thorough investigation into the impact of process parameters on machining Ti6Al4V alloy. This study investigates into the machinability of Ti6Al4V alloy under dry machining conditions using uncoated tools. The experimental design studiedthe effect of process parameters on the cutting power, surface roughness and material removal rate during dry machining of Ti6Al4V alloy. Utilizing Taguchi design of experiments, unified cutting experiments were conducted under dry conditions employing uncoated tools. The study findings revealed that optimal cutting parameters lead to improved cutting energy consumption, reduced tool wear, and enhanced surface finish and material rates. Analysis of Variance (ANOVA) and regression modelling were employed to obtain an objective function capable of predicting the best cutting conditions. ANOVA showed that cutting speed is the main factor for an increase in the cutting power with major contribution of 73 % whereas feed rate is the key factor for surface roughness with the contribution of 80 %. These results help to gain the advantages of dry machining under optimal conditions, facilitating clean production with minimal energy consumption and improved surface quality.

Experimental Investigations of Using Aluminum Oxide (Al2O3) and Nano-Graphene Powder in the Electrical Discharge Machining of Titanium Alloy.

In the present study, a comprehensive parametric analysis was carried out using the electrical discharge machining of Ti6Al4V, using pulse-on time, current, and pulse-off time as input factors with output measures of surface roughness and material removal rate. The present study also used two different nanopowders, namely alumina and nano-graphene, to analyze their effect on output measures and surface defects. All the experimental runs were performed using Taguchi's array at three levels. Analysis of variance was employed to study the statistical significance. Empirical relations were generated through Minitab. The regression model term was observed to be significant for both the output responses, which suggested that the generated regressions were adequate. Among the input factors, pulse-off time and current were found to have a vital role in the change in material removal rate, while pulse-on time was observed as a vital input parameter. For surface quality, pulse-on time and pulse-off time were recognized to be influential parameters, while current was observed to be an insignificant factor. Teaching-learning-based optimization was used for the optimization of output responses. The influence of alumina and nano-graphene powder was investigated at optimal process parameters. The machining performance was significantly improved by using both powder-mixed electrical discharge machining as compared to the conventional method. Due to the higher conductivity of nano-graphene powder, it showed a larger improvement as compared to alumina powder. Lastly, scanning electron microscopy was operated to investigate the impact of alumina and graphene powder on surface morphology. The machined surface obtained for the conventional process depicted more surface defects than the powder-mixed process, which is key in aeronautical applications.