Workpiece Surface Research Articles

Region-Based Approach for Machining Time Improvement in Robot Surface Finishing

Traditionally, in robotic surface finishing, the entire workpiece is processed at a uniform speed, predetermined by the operator, which does not account for variations in the machinability across different regions of the workpiece. This conventional approach often leads to inefficiencies, especially given the diverse geometrical characteristics of workpieces that could potentially allow for different machining speeds. Our study introduces a region-based approach, which improves surface finishing machining time by allowing variable speeds and directions tailored to each region’s specific characteristics. This method leverages a task-oriented strategy integrating robot kinematics and workpiece surface geometry, subdivided by the clustering algorithm. Subsequently, methods for optimization algorithms were developed to calculate each region’s optimal machining speeds and directions. The efficacy of this approach was validated through numerical results on two distinct workpieces, demonstrating significant improvements in machining times. The region-based approach yielded up to a 37% reduction in machining time compared to traditional single-direction machining. Further enhancements were achieved by optimizing the workpiece positioning, which, in our case, added up to an additional 16% improvement from the initial position. Validation processes were conducted to ensure the collaborative robot’s joint velocities remained within safe operational limits while executing the region-based surface finishing strategy.

Portable Machine Tools by Small Piezoelectric Robots for Scalable and Waviness‐Adaptive Fabrication of Surface Microstructures

Surface functional microstructures exhibit extensive application requirements in an array of breakthrough areas. One critical problem that restricts their industrial application is the lack of scalable fabrication techniques due to the limitation of conventional machine tools. This study proposes a scalable surface texturing technique using a portable small (30 × 19 × 22 mm) three‐leg robot that walks and works on the workpiece surface. Due to the elliptical tool vibration, microgrooves can be created on the workpiece surface periodically; meanwhile, the machining force drives the robot to walk forward. Surface texturing experiments are conducted on aluminum and copper workpieces to explore the machining performance of the small robot. The robot can reach a maximum moving velocity of 6.3 mm s−1 and can produce microstructures with a spacing of 4–14 μm on workpiece surfaces. Owing to its unique working principle, the small robot can maintain a constant depth of cut, demonstrating its capacity to adapt to the surface waviness of the workpiece. Finally, the motion straightness of the robot is greatly improved by combining it with the auxiliary track, and multiline microstructures are obtained. In short, the developed small robot presents a promising solution to the challenge of scalable surface texturing.

Investigation on the influence of mesoscale geometric features on the surface white layer characteristics in titanium alloy milling using ball end mills

A white layer will be generated on the machined surface when milling titanium alloy. Its existence will make the surface of the workpiece more brittle, and it is easy to produce cracks during the machining process, which greatly harms machining. Aiming at this problem, this paper takes the ball-end milling cutter with mesoscopic geometric characteristics as the research object, establishes the theoretical model of the white layer thickness of the workpiece under the micro-texture and cutting edge factors, analyzes the single factor of micro-texture parameters and cutting edge parameters, and the interaction between them and cutting parameters on the milling force-thermal characteristics and the white layer of the workpiece. The influence law reveals its mechanism from the macro and micro perspectives. It uses the white layer thickness as the evaluation index to optimize the mesoscopic geometric characteristic parameters by using the simulated annealing algorithm. The results demonstrate that the mesoscopic geometric feature of the ball-end milling cutter effectively reduces the thickness of the white layer, achieving a 38% reduction compared to that observed with a non-textured milling cutter. The thickness of the white layer exhibits a positive correlation with the distance L from the blade and a negative correlation with the edge radius R. The interaction between the cutting edge radius R and the cutting depth a p influences the milling force and heat, alters the micro-texture of the workpiece surface, induces the α + β phase transformation, and affects the white layer thickness. Based on the predictive model for white layer thickness, the optimization results for comprehensive milling performance are as follows: R is 59.39 μm, L is 110.01 μm, D is 58.68 μm, L1 is 130.59 μm, a p is 0.30 mm, V is 147.39 mm/min, f is 0.08 mm/z.

Coupling Taguchi experimental designs with deep adaptive learning enhanced AI process models for experimental cost savings in manufacturing process development

The Aluminum alloy AA7075 workpiece material is observed under dry finishing turning operation. This work is an investigation reporting promising potential of deep adaptive learning enhanced artificial intelligence process models for L18 (6133) Taguchi orthogonal array experiments and major cost saving potential in machining process optimization. Six different tool inserts are used as categorical parameter along with three continuous operational parameters i.e., depth of cut, feed rate and cutting speed to study the effect of these parameters on workpiece surface roughness and tool life. The data obtained from special L18 (6133) orthogonal array experimental design in dry finishing turning process is used to train AI models. Multi-layer perceptron based artificial neural networks (MLP-ANNs), support vector machines (SVMs) and decision trees are compared for better understanding ability of low resolution experimental design. The AI models can be used with low resolution experimental design to obtain causal relationships between input and output variables. The best performing operational input ranges are identified for output parameters. AI-response surfaces indicate different tool life behavior for alloy based coated tool inserts and non-alloy based coated tool inserts. The AI-Taguchi hybrid modelling and optimization technique helped in achieving 26% of experimental savings (obtaining causal relation with 26% less number of experiments) compared to conventional Taguchi design combined with two screened factors three levels full factorial experimentation.

Piecewise approximation and local differential compensation of contact stress distribution of workpiece surface in robotic belt grinding

Piecewise approximation and local differential compensation of contact stress distribution of workpiece surface in robotic belt grinding

Characterization of surface integrity of 7075-T6 aluminum alloy subjected to microbiologically induced corrosion during high-speed machining

Microbiologically Influenced Corrosion (MIC) is one of the primary causes of corrosion damage and equipment failure in industrial environments. This paper aims to investigate the impact of microbiologically influenced corrosion on the surface integrity of 7075-T6 aluminum alloy. Through experiments involving cryogenic treatment and machining, the study systematically compares the effects of different microbiologically influenced corrosion environments on 7075-T6 aluminum alloy. Techniques such as X-ray Diffraction (XRD), surface roughness measurement, Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), and work hardening were used to elucidate the influence of natural seawater (Planktonic microorganisms, PM) and marine sediment (Benthic microorganisms, BM) corrosion on the surface integrity of 7075-T6 aluminum alloy.The results indicate that, compared to PM corrosion, BM corrosion results in a smaller surface roughness of 7075-T6 aluminum alloy. Specifically, the BM-10d specimen exhibits the smallest roughness at 0.353 μm. XRD and EDS analyses show that the corrosion products after microbiological corrosion are primarily a mixture of Al2O3, AlO(OH), and Al(OH)3. The peak intensity of AlO(OH) in the (200) crystal plane of the BM-5d corrosion product is notably higher than that of the 7075-T6 aluminum alloy under other conditions. In the PM environment, the corrosion products fully cover the entire surface of the workpiece and are accompanied by significant cracking. In contrast, in the BM environment, the corrosion products mainly exhibit a granular structure, are scattered across the workpiece surface, and the exposed substrate can be observed.The microhardness of the aluminum alloy after microbiological corrosion shows a trend of increasing initially, then decreasing, and finally stabilizing. The maximum depth of the hardened layer for PM-10d is 120 μm, with a maximum hardness of 178.74 HV. Compared to PM corrosion, BM corrosion results in a significantly greater hardened layer depth for 7075-T6 aluminum alloy, with the BM-10d hardened layer depth reaching approximately 140 μm and the peak hardness at 185.36 HV. Additionally, in the BM environment, the precipitates are fewer compared to those in the PM environment and exhibit a non-continuous, non-grain-boundary precipitation band.

Lap joining of Ti6Al4V titanium alloy by vortex flow-based friction stir welding

The current study uses a novel vortex flow-based friction stir lap welding (VFSLW) process to weld 1.4 mm thick Ti6Al4V sheets, trying to replace the diffusion bonding in the superplastic forming/diffusion bonding process. The mechanical properties and joining mechanism of the VFSLW joint were investigated. Good weld formation was obtained at 300–350 rpm and 80 mm/min. No hook defect was formed in the lap interface. The lap joint fractured across the stir zone (SZ) in the top plate under the optimal parameters. The cracks initiated from the oxidation defect, where the oxides on the workpiece surface were involved in the SZ by the vortex during the welding. It suggests that a good argon shield is very important for the VFSLW of titanium alloy. The highest tensile strength reaches ~890 MPa, up to 95 % of the base material. The formation of an α + β lamellar structure in the SZ is due to the peak welding temperature exceeding the β-transus temperature. In the bonded zone (BZ), a very thin layer with ultrafine α grains was formed by dynamic recrystallization in the α phase field, although its two sides are α + β lamellar structures. This is because of the oxidation on the workpiece surface during the welding process and the O element is a strong α stabilizer.

The capability of Acoustic Emission features to monitor diamond-coated burr grinding wear and effectiveness

Within manufacturing there is a growing need for autonomous Tool Condition Monitoring (TCM) systems, with the ability to predict tool wear and failure. This need is increased, when using specialised tools such as Diamond-Coated Burrs (DCBs) for grinding high strength ceramics or glass, in which the random nature of the tool, inconsistent manufacturing methods and high wear rates create large variance in tool life. This unpredictable nature leads to a significant fraction of a DCB tool's life being underutilised due to premature replacement. Workpiece surface damage, increased grinding forces and large-scale diamond grain pullout could all be the result of high levels of runout and in-circularity common within electroplated DCBs. As such it is important to not only monitor the overall tool wear but also tool condition. Acoustic Emission (AE) presents as an indirect on-machine sensing method highly suited to grinding applications. The high frequency range of AE, >20 kHz, prevents machine noise from dominating the acquired signals, isolating the micro-scale machining processes within noises machine environments. AE resulting from the grinding process has the potential to monitor not only tool wear but also runout and circularity. A series of DCB wear tests have been conducted, each consisting of the continuous acquisition of AE during grinding and frequent tool surface measurements. Preliminary results demonstrate AE kurtosis can be seen as an indicator of each tool’s runout, representing the fraction of time the tool and workpiece are in contact during a revolution. As a result, an indirect monitoring system capable of monitoring wear and tool state with AE could be utilised within the manufacturing sector.

Recent Patents for Optical Component Polishing Technology

Background: Fluid jet polishing, Airbag polishing, Magnetorheological polishing, and Ion beam polishing are all emerging polishing technologies commonly used for processing optical components, which can be used to manufacture various high-precision and high-quality optical components. Their processing mechanisms are to remove materials by high-speed jet impacting the surface of the workpiece; using a spherical flexible airbag as a polishing tool to obtain a super-smooth surface by adding polishing fluid containing fine abrasives; controlling the magnetic field to form a flexible polishing belt of Magnetorheological fluid, which undergoes relative motion to achieve material removal; using a neutral ion beam to bombard the surface of the workpiece to remove workpiece surface atoms and obtain a super-smooth surface through energy and momentum transfer between ions and workpiece atoms. The characteristics and removal mechanisms of various polishing methods are briefly described, and the advantages and key issues that need to be addressed for each polishing technology are pointed out, and suggestions and prospects for future research, application, and development are also given. Objective: In order to meet the growing demand for high-precision optical components and mass-manufactured optical components, this paper aims to study the various polishing technologies that are continuously improved and suggestions are made for future research and development directions. Method: This paper reviews the current patents related to various polishing technologies, such as Fluid jet polishing, Airbag polishing, Magnetorheological polishing and Ion beam polishing and other representative polishing technologies. Results: Various types of polishing technologies have been studied, and the main problem at the current stage is the lack of accuracy. The problem of the polishing device, such as fluid jet polishing, only considers the change of fluid velocity and pressure to construct the removal function model for analysis and summary, and suggestions for the latest research progress of various polishing technologies are given. Conclusion: The improvement and optimization of polishing technology are beneficial to improving the polishing accuracy and quality of optical components and have great help for the future development of related patents.

Technological support of workpiece surface quality based on local cryogenic impact during processing of austenitic steels

Technological support of workpiece surface quality based on local cryogenic impact during processing of austenitic steels

Optimization of Material Removal Rate and Wear Rate in EDM Machining of Inconel 625 Using a Novel Nano Al-Ni Composite Electrode: A Response Surface Methodology Approach

The electric discharge machine is a novel machining technique. When the tool and the work item do not communicate. Components composed of difficult-to-machine hard materials. In the current experimental inquiry, the process factors that influence the machining concert process and its effectiveness are explored. The response table for each set of machining limitations is used in conjunction with the response surface methodology in the research to determine the appropriate levels of machining factors. The work's machining input parameters are optimized for maximum material removal rate (MRR) and reduce the electrode wear rate (EWR) when electro-discharge machining Inconel 625 using the tool Nano Al-Ni composite electrode. Another analysis of variance is to identify the factors causing the different answers mentioned above. EDAX was also used to investigate the material composition of the workpiece. Machined workpiece surfaces were evaluated using scanning electron microscopy to assess surface accuracy and microstructural characteristics (SEM). The following conclusions may be drawn from this work. The MRR parameter that is most affected is pulse off time. As pulse-off time lengthens, MRR increases. According to the response graph, the greatest MRR value that can be attained under the ideal parameters of Ip = 8A, T-ON = 50μs, and T-OFF= 100μs is 0.0115 g/min. The magnitudes of MRR range from 0.0091 to 0.044 g/min. Impact of T ON and T OFF: Higher EWR is 0.0022 g/min is seen in runs with T ON = 70 μs and T OFF = 100 μs.

Pulsed Unipolar-Polarisation Plasma Electrolytic Polishing of Ni-Based Superalloys: A Proof of Conception

The enhanced performance of aerospace equipment drives parts development towards integration, complexity, and structural optimization. This advancement promotes metal near-net fabrication technologies like wire electrical discharge machining (WEDM) and 3D printing. However, the high initial surface roughness from WEDM or 3D printing poses significant challenges for the high-performance surface finishing required. To effectively reduce the surface roughness of the workpieces with high initial surface roughness, this paper proposes pulsed unipolar-polarisation plasma electrolytic polishing (PUP-PEP). The study examined the material removal mechanisms and surface polishing quality of PUP-PEP. This technique combines the high current density and material removal rate of the electrolytic polishing mode with the superior surface polishing quality of PEP through voltage waveform modulation. For an Inconel-718 superalloy part fabricated by WEDM, PUP-PEP reduced surface roughness from Ra 7.39 μm to Ra 0.27 μm in 6 min under optimal conditions. The roughness decreased from Ra 7.39 μm to Ra 0.78 μm in the first 3 min under pulsed unipolar-polarisation voltage, resulting in a remarkable 233% increase in efficiency compared to that with conventional PEP. Subsequently, the voltage output voltage is transformed into a constant voltage mode, and PEP is continued based on PUP-PEP to finally reduce the workpiece surface roughness value to Ra 0.27 μm. The proposed PUP-PEP technology marks the implementation of ‘polishing’ instead of conventional rough-finish machining processes, presenting a new approach to the surface post-processing of metal near-net fabrication technologies.

Influence of tool wear on geometric surface modeling for TC4 titanium alloy milling

Addressing the insufficient accuracy of milling surface roughness prediction model, the formation causes of different roughness were analyzed, and a surface roughness prediction model which takes tool wear into account was established based on an improved Z-MAP algorithm. Combining tool geometry and tool wear morphology, a mathematical model of surface profile was built; And the motion trajectory equations of the milling cutter teeth were established via machining kinematics. The servo rectangular encirclement and Newton iterative method were adopted to improve the Z-MAP algorithm. Combining the Z-MAP algorithm with the insert motion trajectory equations, the values at different height coordinates of the workpiece grid nodes were obtained, allowing numerical simulation of workpiece surface geometry and analysis of the effect of cutting trajectory overlap on the machined surface morphology. TC4 titanium alloy milling experiment was conducted to validate the simulation model. The simulated surface roughness Sa exhibited significant deviation from experimental values before tool wear, with a maximum error of 53.08 %. Nevertheless, the simulated values of Sa were closer to experimental values after tool wear, with a maximum error of 15.45 % and a minimum of only 3.07 %. Additionally, the predicted results for the bearing length ratio Rmr(c) were consistent with experimental values. The mathematical model for surface roughness taking tool wear into account effectively predicted the shape profile and surface roughness of the machined surface, providing theoretical guidance and technical support for practical production.

Finite-time SMC-based admittance controller design of macro-micro robotic system for complex surface polishing operations

In the field of robotic polishing, achieving uniform material removal typically involves addressing the issue of constant contact force control. However, multi-source external disturbances in the polishing scenarios of complex workpiece surfaces can severely affect the robot’s force control accuracy. To enhance the responsiveness and disturbance rejection capabilities of robots in the compliant polishing process, this paper proposes an adaptive admittance controller with practical finite-time stability. A virtual control input is introduced into the basic admittance control framework in light of the state space theory, aiming to provide flexibility for common adaptive law designs. On this basis, a robust sliding mode control (SMC) algorithm is proposed to suppress external disturbances. The force tracking error is theoretically proven to achieve finite-time convergence when applying the proposed control strategy. Experimental results across various polishing scenarios demonstrate that, compared with the existing admittance control strategies, the proposed method can reduce fluctuations of the polishing force and improve the surface quality, thus verifying its effectiveness.

Study on the groove geometry of pad in water dissolution polishing of soft brittle materials based on trajectory analysis

During the water dissolution polishing process of soft brittle materials, the pad's groove geometry plays a significant role in determining the performance. This not only affects the flow of the slurry but also directly impacts the overall distribution of the water core on the pad surface, thereby influencing the polishing effect. A trajectory model of the water core on the workpiece surface was established through kinematic analysis and the characteristics and effects of the pad's groove geometry in circular, radial, composite, and grid were studied combined with the trajectory analysis. The coefficient of variation and power spectral density were established to evaluate the trajectory uniformity. The trajectory density distribution was quantitatively analyzed to obtain a better understanding of the material removal uniformity. The simulation and experiment results indicated that the existence of groove geometry will greatly affect the flow of slurry and the surface quality. The grid groove had a better distribution of water core, which means better material removal. There exists a tradeoff between the number of grooves and their spacing. These insights offer a fresh perspective and serve as a valuable reference for further research and analysis into the groove characteristics of pads.

Surface roughness and fracture cracks of Al2O3/TiO2 composite coating by wet chemical mechanical grinding with structured abrasives pad

In the fields of wind power, and other industries, the Al2O3/TiO2 coating is prepared and ground on the bearing ring, in order to obtain the insulation resisting the electrical erosion for the motors at high voltage. A novel wet chemical mechanical grinding (WCMG) method is proposed to finish this hard-brittle composite material, utilizing the structured diamond abrasives pad and the NaOH solution. The softened workpiece's surface under the chemical reaction was demonstrated by means of Raman spectrum, indentation and scratching tests. The analytical model of surface roughness and fracture cracks is established based on the synthesis of geometry and kinematics, contact mechanics, material removal and indentation fracture mechanics. The surface roughness of coating was reduced from initial Sa 3.293 μm down to final Sa 0.049 μm in the WCMG process with grain size 3 μm and pH 12.01, mostly attributed to the ductile removal of chemically softened coating surface.

Моделирование и оптимизация процесса накатывания роликом AL6061-T6 для достижения минимального отклонения от круглости, минимальной шероховатости поверхности и повышения ее микротвердости

Introduction. Roller burnishing is one of the most common methods of improving the surface quality of parts, wear resistance, microhardness, and corrosion resistance. The process involves compressing and smoothing the workpiece using the pressure of a hardened roller. It is often used to improve part performance and lifespan in sectors including automotive, aerospace, and medical equipment manufacturing. The literature reviewed shows that the roller burnishing process effectively improves the overall surface quality and hardness of the workpiece. In addition, roller burnishing is considered as an affordable method to enhance the functionality and robustness of machined parts by reducing the likelihood of surface defects such as like scratches and cracks. However, very few studies have been reported on the modeling and optimization of roller burnishing of Al6061-T6 for minimum surface roughness, better microhardness, and roundness. The methods of investigation. In the current work, roller burnishing of Al6061-T6 is modeled and optimized for superior microhardness, roundness, and minimal surface roughness. Under dry-cutting conditions, the performance of roller burnishing of Al6061 specimens is assessed in terms of process factors such as cutting speed, feed, and number of passes. Mathematical models to predict the surface roughness, microhardness, and deviation in roundness are developed based on the experimental results. Results and Discussion. The coefficient of correlation for the developed models is found to be close to 0.9, which indicates that it can be reliably used to predict and optimize the roller burnishing of the Al6061-T6. According to this study, the use of the following cutting parameters leads to the lowest variation in roundness (4.282 µm), the better microhardness (119.2 Hv), and the lowest surface roughness (0.802 µm): cutting speed 344 rpm, feed 0.25 mm/rpm and four passes. Further, the study reveals that increasing the number of passes (beyond four) does not significantly improve the surface roughness or microhardness. However, it does lead to a slight increase in the roundness deviation. Therefore, in order to achieve optimal results, it is recommended to use a maximum of four passes during roller burnishing of Al6061 specimens under dry cutting conditions. These results imply that roller burnishing can effectively improve the overall quality and hardness of the workpiece surface. In addition, roller burnishing is considered as an affordable method to increase the functionality and robustness of machined parts by reducing the likelihood of surface defects like scratches and cracks.

A visual measurement method for grinding surface roughness combining filter and branch convolution network

ABSTRACT The visual measurement method of grinding surface roughness is mainly predicted by designing image feature indicators. In contrast, the self-extraction method of grinding surface features based on deep learning has problems such as noise, low resolution and poor perception of details. This paper proposes a visual measurement method for grinding surface roughness to address these problems by combining filters and branching convolutional networks. The method adopts a two-branch convolutional neural network, inputs the images using filter denoising and the original grinding workpiece surface images simultaneously, self-extracts roughness correlation features and fuses them to achieve feature enhancement, effectively improves the recognition accuracy and generalisation ability of the model, and verifies the robustness of the model in the case of rusting on the workpiece surface. The experimental results show that the method can effectively solve the problem of the grinding process’s weak and difficult recognition of surface roughness feature information and provide a basis for automated visual online measurement of grinding surface roughness.

Improving the Performance of the Machining Process by Using Ultra‐Advanced Tools in a Clean Turning of Inconel 686 Using the Minimum Quantity Lubrication Method

ABSTRACTThe high tensile strength and high resistance of nickel‐based superalloy 686 against high temperatures and corrosion rates have made it a widely used in important applications such as the aerospace industry, high pollution‐ and corrosion‐resistance equipment manufacturing and petrochemical industry. Therefore, the machining of this advanced alloy with its unique properties is extremely important and can be challenging. Significant increase in input parameters levels, reduction of machining costs, improvement of surface and subsurface properties and clean production are among the issues that should be considered in dealing with Inconel 686 turning operations. Simultaneous application of advanced tools such as polycrystalline diamond (PCD) and polycrystalline cubic boron nitride (PCBN) and optimised minimum quantity lubrication (MQL) method and evaluating the results obtained with a wide range of output parameters related to machining process performance and tribological properties can be proposed as an innovation and a solution to this problem in this article. This study analyses several output parameters with different speeds and feeds to evaluate the effect of cutting insert type on machining process performance and tribological properties. The output parameters include tool wear, residual stress, cutting zone temperature, surface smoothness, machining forces and workpiece surface defects. The results indicated that using the optimised MQL method reduces the size of lubricant droplets and increases the surface covered by cooling. With these changes, the performance of the machining process and the parameters related to the surface integrity increase significantly. Among the parameters associated with the performance of the machining process, the PCD tool reduces the cutting zone temperature by 23%, the tool wear by 19% and the machining forces by 18% compared to the PCBN tool. In the parameters related to surface integrity, this method reduces the residual stress by 19% and the surface roughness by 9% compared to the PCBN tool. From the production index perspective, the PCD tool can significantly increase the cutting speed and feed rate, reducing production time and costs.

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.