Powder Mixed Electrical Discharge Machining Research Articles

EDMNet: unveiling the power of machine learning in regression modeling of powder mixed-EDM

EDMNet: unveiling the power of machine learning in regression modeling of powder mixed-EDM

Electro-discharge deposition of zinc powder on 316L stainless steel: Synthesis, deposition rate, and characterization

This study investigated the potential of powder-mixed electrical discharge machining (PM-EDM) to deposit metallic powder, specifically zinc powder, on 316L stainless steel (316L SS). This study aimed to evaluate the effect of zinc (Zn) deposition on 316L SS for oil and gas application. Minitab 19 software was employed to design the experiments using screening DOE option and to analyse and model the results through screening response optimiser from Minitab 19 software. Surface morphology, microstructure and coating thickness were examined through field-emission scanning electron microscopy (FESEM) and scanning electron microscope (SEM). The results suggested an improvement in the coating thickness with an increase in powder concentration and discharge current. An average coating thickness of 91.47 μm was achieved in samples fabricated at 20 g/L powder concentration. X-ray diffraction analysis revealed the formation of hard carbides, such as Cr3C2 and TiC, on the PM-EDMed 316L SS surface. Further characterisation through energy-dispersive X-ray spectroscopy confirmed the deposition of both the tool electrode and Zn powder particles. The adhesion test confirmed that all specimens failed under 100% adhesive failure. The hydrophobicity analysis confirmed that the coated surfaces are hydrophobic. Significant improvement has been established for microhardness, wear resistance and corrosion performance. Screening results revealed that discharge current, pulse-on time, and powder concentration were the most significant parameters. The average predicted errors of 2.055%, 6.782%, and 2.396% for material deposition rate, tool wear rate, and surface roughness were achieved, respectively. These affirmed the excellent reproducibility of the model developed. This study presents a methodology for the formation of carbide- and oxide-based coatings specifically for oil and gas applications (flanges and connectors).

Optimization and characterization of boric acid powder mixed electrical discharge machining of Ti-6Al-4V ELI

The powder mixed electrical discharge machining (PMEDM) process is used for enhancing machining efficiency and improving the surface characteristics of the workpiece compared to normal EDM. The present study evaluates the effect of boric acid powder mixed in deionized water in PMEDM of Ti-6Al-4V ELI (extra low interstitial). The PMEDM process is assessed by evaluating material removal rate (MRR) and surface roughness (SR) at varying powder concentration (PC), current and pulse duration ( Ton). Boric acid PMEDM exhibits advantageous for both MRR and SR, where MRR increases and SR decreases with an increase in PC. To simultaneously achieve higher MRR and lower SR, the grey-fuzzy logic method is employed. Initially, the raw input data is normalized into grey numbers and a single index is obtained through grey relational analysis. Subsequently, triangular membership functions are assigned to the inputs and output. Fuzzy logic rules are then formulated, and grey fuzzy relational grade (GFRG) is calculated for each condition. The optimum condition (GFRG = 0.787) is attained at 15 g/l PC, 9 A current and 106 µs Ton, resulting in a 63% improvement compared to the initial condition. At the optimum condition, MRR increased by 145% and SR decreased by 29% compared to the initial condition. The effect of boric acid in PMEDM can be visualized through the formation of smooth surfaces, exhibiting reduced SR, smaller and shallower craters, and fewer debris and globules. Additionally, the boric acid PMEDM experiments resulted in the formation of a hard TiB phase on Ti-6Al-4V, thus improving its wear resistance.

Enhancing the machining productivity in PMEDM for titanium alloy with low-frequency vibrations associated with the workpiece

Abstract The incorporation of frequency vibration into the powder mixed electric discharge machining (PMEDM) process has the potential to significantly enhance the productivity and quality of the machining process, as well as to provide a great deal of opportunities in this sector. An analysis and evaluation of the machining productivity (material removal rate [MRR]) in PMEDM with low-frequency vibration was carried out in this work by considering SKD61 as a workpiece. The oil dielectric solution mixed with titanium powder was used as a dielectric medium with red copper (Cu) as the electrode. At this point in time, the process technology parameters that have been chosen for inquiry are as follows: current (I), pulse on time (T on), powder concentration (C p), P, F, and A. The Taguchi technique (L25) was used to create the experimental matrix. With the use of analysis of variance, it was able to examine the impact that the factors had on MRR, and the analysis was utilized to ascertain the highest possible value of MRR. I was the parameter that has the most significant effect, according to the findings, whereas T on was the parameter that has the least significant effect. The maximum value of the MRRmax is equal to 31.29 mm3/min.

An experimental investigation and machine learning predictions to enhance microhardness in powder mixed electrical discharge machining

An experimental investigation and machine learning predictions to enhance microhardness in powder mixed electrical discharge machining

Analysis and experimental investigation of powder concentration and stirring velocity on powder mixed electrical discharge machining performance with 3D printed electrodes

In this work, CuO mixed lemon peel dielectric is used along with the 3D printed aluminium electrodes to enhance the electrical discharge machining (EDM) performance. This work mainly focuses on improving the surface quality by optimizing the powder concentration and stirring velocity. A full factorial of 27 experiments is carried out with input parameters such as pulse off time with 3 levels (28, 58 and 98 μs), powder concentration with 3 levels (1, 2 and 3 g/L) and stirring velocity with 3 levels (900, 1800 and 2700 rpm), while keeping the current, pulse on and voltage as constant. For all trials, the output responses viz. surface roughness (SR) and material removal rate (MRR) are noted. It is evidenced that EDM performance is influenced by the stability of powder mixed dielectric. To understand the most influential input parameter and its level, analysis of variance (ANOVA) and grey relational analysis (GRA) are carried out. The output analysis exhibited that powder concentration of 2 g/L, stirring velocity of 1800 rpm and pulse off time of 28 μs as the best combination for the best quality of finish (4.72 μm) with high MRR (0.0035 g/min) than the 1 g/L PC with 900 rpm SV for the best quality finish (5.87 μm) along high MRR (0.0029 g/min) and 3 g/L PC with 2700 rpm SV for the best quality finish (5.38 μm) with high MRR (0.0030 g/min) having pulse off time of 28 μs. The experimental findings are validated with a 3D surface plot and SEM images taken on the machined surface. Also, a simulation model is built to understand the flow velocity profiles. This helps ensure the minimum stirring velocity to be maintained to enhance the stability of powder mixed dielectric.

Machinability investigation and surface modification of nano-TiB2 and AlN grafted MWCNT hybridized Al 7075 matrix ternary composite through powder-mixed EDM

This paper accentuates powder-mixed electrical discharge machining (EDM) performance of a newly designed nano-TiB2 and AlN grafted multiwall carbon nano-tube (MWCNT) hybridized Al 7075 matrix ternary composite. The hybrid metal matrix composite (MMC) was fabricated through squeeze casting route, preceded by two-stage reinforcement addition, mechanical agitation, and ultrasonic treatment. EDM was carried out using cryogenic treated Cu electrode and Al2O3 particle-mixed dielectric medium. Influence of EDM process variables, that is, peak current ( I P), pulse-on time ( T ON), and powder concentration ( P C) on machinability of the hybrid MMC was studied considering material removal rate (MRR), tool wear rate (TWR), and average surface roughness ( Ra) as quality indicators. Effects of machining and Al2O3 particle addition on surface morphology of the hybrid MMC were also explored through scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), and elemental mapping. Results reveal elevation of MRR, reduction of TWR and improvement of surface finish during powder-mixed EDM in comparison to the non-mixed (conventional) EDM. Maximum traces of Al2O3 particle deposition was identified on the machined surfaces while using the powder concentration of 1.5 g/l within the dielectric.

Numerical and experimental investigation into the energy distribution in powder mixed EDM

This study investigates the discharge energy distribution during Powder Mixed Electrical Discharge Machining (PMEDM) at different values of pulse duration, peak current and powder concentration. A finite element method (FEM) based numerical model has been developed to estimate the power distribution factor by reverse simulation. The developed model has been used for determining the fraction of discharge energy distributed to the electrodes. The model and experimental values of total fraction of discharge energy are in close agreement with the error varying between 0.47 % to 14.04 % for tool and 0.82 % to 9.82 % for workpiece. Parametric influence on components of discharge energy has also been discussed.

Experimental investigations of using MWCNTs and nano-graphene particles for the enhancement of machining performance using powder-mixed EDM of Udimet-720

Experimental investigations of using MWCNTs and nano-graphene particles for the enhancement of machining performance using powder-mixed EDM of Udimet-720

Prediction of machining performances in powder mixed electro-discharge machining to process skd61 steel by response surface methodology

In electro-discharge machining (EDM) with mixing powder, it is called powder mixed electro-discharge machining (PMEDM), then machining performances- i.e. material removal rate(MRR) and tool wear rate (TWR) has great significance in evaluating the effectiveness and machining accuracy of the machining method. Therefore, in this study, response surface methodology (RSM) was utilized for estimating functions of process variables {comprising peak current (Ip), pulse on time (Ton), and powder concentration (Cp)} for the machining performances for processing SKD61 steel during EDM process with tungsten compound powder. Box-Behnken matrix was utilized for designing and conducting a series of empirical trials. Analysis of variance (ANOVA) was applied to evaluate the adequate of predictive models. The outcomes reveal that the predicted models of MRR and TWR have a high precision with R2 values of MRR and TWR being 99.2% and 99.11%, respectively. The error comparison of the predictive and empirical values for the confirmed experiments is less than 5%, this once again consolidates that the developed models' accuracy. These development models can efficiently prognosticate the desired machining performances of the PMEDM method for processing SKD61 steel

PERFORMANCE EVALUATION AND ECONOMIC ASSESSMENT IN ELECTRICAL DISCHARGE MACHINING OF SS316 USING GRAPHITE POWDER DISPERSED IN BIODEGRADABLE PALM OIL DIELECTRIC

In today’s rapidly evolving manufacturing industry, researchers and engineers are constantly seeking innovative methods to improve machining processes. One such area of interest is the use of electrical discharge machining (EDM) for difficult-to-machine metals like SS316. This research compares the performance and economic aspects of traditional EDM and powder-mixed EDM when machining SS316 using copper electrode. Graphite powder dispersed in biodegradable palm oil is investigated as a dielectric media with the aim of enhancing EDM performance. According to the findings, the analysis of the cutting performance of different machinability aspects revealed that using graphite powder mixed with palm oil as a dielectric in EDM outperformed conventional EDM relating to material removal, surface finish, surface hardness, electrode wear rate and hole overcut. The flushing condition and unique properties of graphite powder and palm oil, such as cooling, and thermal conductivity, contributed to the improved performance observed in EDM processes. These findings highlight the potential of graphite powder mixed with palm oil as a promising alternative dielectric in EDM, offering enhanced machining capabilities and improved surface quality. The total machining expenditure per part under PMEDM (INR 505.50) is lowered by 9.2% than expenditure under conventional EDM (INR 525). The surface microhardness of the machined component attained using graphite powder-mixed EDM is enhanced in comparison to that achieved using standard EDM due to the creation of a carbon-rich re-solidified layer.

Nanopowder-mixed EDM on biodegradable Mg alloy AZ31B for improved surface characteristics and biocompatibility

Powder-mixed electrical discharge machining (PM-EDM) was conducted on biodegradable magnesium (Mg) alloys for biomedical applications. The Mg alloy AZ31B has shown outstanding mechanical properties, similar to human bone, and is lightweight. Efforts were made to enhance the EDM capabilities by a PM-EDM process using nanopowder mixed in the dielectric medium and copper tool electrode amid the machining of Mg alloy AZ31B, followed by investigating surface modification by minimum machining time, morphology, chemistry, topography and wettability of the surfaces. The surface produced by nano PM-EDM operation exhibits minimal cracks and craters, an acceptable range of recast layer thickness (2.4 − 2.7μm), satisfactory corrosion resistance and surface roughness (Ra = 2.87μm) as well as suitable hydrophobic behaviour (CA122q) and bioactivity with Ringer’s solution, suggesting an improvement in the degradation rate. Thus, PM-EDM-induced surface modification suggests the suitability of Mg alloy AZ31B as a biodegradable implant in adults and children.

Comparing surface characteristics of Cu-Al-Fe alloys using thermal-based machining processes

The exceptional shape memory properties and load-handling capabilities of shape memory alloys makes them perfect for a spectrum of applications, such as actuators in robotics, control of aircraft wings and biomedical applications. Other than nickel-titanium shape memory alloy there are also various combinations of elements that show the same memory effect, namely Cu-Al-Fe, Cu-Al-Zn, and Cu-Al-Fe-Mn. However, a major problem often associated with shape memory alloys is the technical difficulty associated with machining them. Consequently, they do not tend to last longer when put to use. An optimal selection of input process parameters has a direct influence on the physical properties of these compounds. The traditional machining process, such as drilling, milling and grinding, pose a great threat to their properties. Hence, the research community has focused their study towards unconventional processes, such as (i) Wire Electric Discharge Machining, and (ii) Laser Beam Machining. In this research study, machining of the Cu-Al-Fe shape memory alloy was performed using three unconventional machining processes, namely (i) electric discharge machining (EDM), (ii) laser beam machining (LBM), (iii) powder-mixed electric discharge machining (PMEDM) and the effect of input process parameters were analysed. Various characterization tests provide useful information specific to changes in the microstructure and thermal behaviour of the alloy. The results show that the samples machined with PMEDM, EDM and LBM have surface roughness values of 2.377, 3.120 and 3.432 µm, respectively, which proves that PMEDM is best suited for machining the CuAlFe smart alloy.

Surface roughness prediction of AISI D2 tool steel during powder mixed EDM using supervised machine learning

Surface integrity is one of the key elements used to judge the quality of machined surfaces, and surface roughness is one such quality parameter that determines the pass level of the machined product. In the present study, AISI D2 steel was machined with electric discharge at different process parameters using Jatropha and EDM oil. Titanium dioxide (TiO2) nanopowder was added to the dielectric to improve surface integrity. Experiments were performed using the one variable at a time (OVAT) approach for EDM oil and Jatropha oil as dielectric media. From the experimental results, it was observed that response trends of surface roughness (SR) using Jatropha oil are similar to those of commercially available EDM oil, which proves that Jatropha oil is a technically and operationally feasible dielectric and can be efficiently replaced as dielectric fluid in the EDM process. The lowest value of S.R. (i.e., 4.5 microns) for EDM and Jatropha oil was achieved at current = 9 A, Ton = 30 μs, Toff = 12 μs, and Gap voltage = 50 V. As the values of current and pulse on time increase, the S.R. also increases. Current and pulse-on-time were the most significant parameters affecting S.R. Machine learning methods like linear regression, decision trees, and random forests were used to predict the surface roughness. Random forest modeling is highly accurate, with an R2 value of 0.89 and an MSE of 1.36% among all methods. Random forest models have better predictive capabilities and may be one of the best options for modeling complex EDM processes.

Investigation of processing characteristics of PCD in ultrasonic-assisted graphene powder mixed EDM

Polycrystalline diamond is widely used in many fields including ultra-precise machining, optical material and semiconductor electronic devices due to its excellent physical properties. However, traditional mechanical processing methods of polycrystalline diamond leads to severe tool wear, low efficiency and high costs. Although electrical discharge machining can overcome some limitations, it usually exhibits a low material removal rate and poor surface quality. This study aims to explore the effect of graphene powder and ultrasonic vibration on polycrystalline diamond by electrical discharge machining. It was found that the synergistic effect of graphene powder and ultrasonic vibration can achieve a good surface quality. The results show that ultrasonic-assisted powder mixed electrical discharge machining can obtain the smallest surface roughness (1.98 μm) at low parameter and the biggest material removal rate (0.773 mg/min) at high parameter compared with ultrasonic assisted electrical discharge machining and powder mixed electrical discharge machining. In addition, after ultrasonic-assisted powder mixed electrical discharge machining, the minimum value (0.807) of ID/IG is obtained. For polycrystalline diamond, this study also proposes a removal mechanism that diamond converts into graphite and is peeled under tensile stress.

Performance analysis of powder-assisted micro-drilling operation using micro-EDM

Miniaturization is governed by the precise and accurate micro-machining operations of various applications. Micro-EDM has emerged as a feasible method for attaining microscale high-precision drilling. The present paper aims to conduct an experimental investigation for drilling micro-holes on copper using the Alumina (Al2O3) powder mixed Micro-EDM technique. Process parameters, including voltage, feed rate, and powder concentration, are varied in experimentation to evaluate their impact on response measures like MRR, TWR, taper angle, and aspect ratio. ANOVA determines the individual contribution of process parameters on each response measure. Voltage is the primary factor influencing MRR (93.5%), TWR (58.24%), and aspect ratio (67.3%), whereas the interaction effect of voltage with powder concentration primarily affects the taper angle (32.36%). Furthermore, the GRA method has optimized the multiple parameters for different responses. The optimum combination of parameters was obtained at a voltage of 125 V, powder concentration of 0.8 g/L, and tool travel speed of 9 µm/s at which better responses are received. The results obtained from FESEM analyses indicate that utilizing alumina (Al2O3) Nano-powder in the dielectric fluid leads to improved effectiveness and reduces the formation of micro-cracks, and micro-voids. Furthermore, the formation of recast layer is reduced by 36.49% as compared to without powder mixed EDM oil during micro-drilling operations.

Assessment of electro-discharge machining for nimonic C-263 utilizing aluminum powder-infused green dielectric

ABSTRACT Aluminum powder-mixed EDM is operated on Nimonic C-263 with varied process parameters using eco-friendly deionized water as a dielectric. Performance evaluation includes material removal rate (MRR), tool wear rate (TWR), average surface roughness (Ra), EDM ratio (ER), and SEM analysis. MRR has been found to increase with higher peak current (Ipc), pulse-on-time (To), and pulse-off-time (Tf), achieving a peak of 2.183777 mm3/min at 12 A Ipc and 12 g/lit powder concentration (C). TWR is minimum (0.002455 mm3/min) at 12 g/lit C and 7 µs Tf. The least Ra (1.182 µm) is observed at 9 g/lit C and 7 µs Tf; however, it increases with higher duty cycle. ER rises with Ipc and Tf while it declines with To. SEM images reveal larger craters and debris globules at higher Ipc. Overall, optimized parameters enhance MRR while minimizing TWR and Ra, albeit with observed debris formation at higher Ipc.

The evaluation of machining performances and surface roughness of TZM-molybdenum superalloy processed by silicon carbide powder mixed EDM process using RSM and ANOVA

In the present era, the concept of Industry 4.0 plays a significant part in improving the efficiency, quality, and utilization of resources by automation and enabling intelligent operations in manufacturing processes. As a result, there is a requirement to develop an environment that improves efficiency as well as quality in order to accomplish net zero in manufacturing. The objective of powder mixed electric discharge machining (PMEDM) is to enhance the quality of the surface and machining efficiency of traditional electrical discharge machining. The PMEDM method was applied to TZM-molybdenum superalloy in the present investigation by incorporating silicon carbide particles into the dielectric medium. Powder concentration, peak current, pulse on time, pulse off time, and gap voltage were the considered input variables for the investigation. The impacts of the input variables on the surface of the specimen’s roughness and the rate of material removal (MRR) were examined. The experiment model was built using response surface methodology. To find out if the input factors were significant with regard to each response, an analysis of variance (ANOVA) was performed. Powder concentration, pulse current, gap voltage, and pulse on time are found to be the important input variables for both surface roughness and MRR based on ANOVA analysis.

Numerical analysis of the powder mixed electrical discharge machining (PMEDM) process for TZM-molybdenum superalloy using finite element method

The powder mixed electrical discharge machining (PMEDM) process was simulated via finite element analysis in the current study to assess heat behavior and material removal rate. The goal of this paper is to conduct a thorough experimental and thermal examination of electrical discharge machining (EDM) in order to forecast its cutting characteristics and subsequently optimize the output variables using a response surface methodology for simulations and choosing the most suitable set of process variables related to the PMEDM process. This study’s objective is to design a 2D axisymmetrical transient thermal model that might also describe the physics of material removal in a single spark PMEDM operation on a Titanium Zirconium Molybdenum (TZM) superalloy. ANSYS (version 9.1) software is used to perform transient heat transfer simulations to determine the temperature profile with the amount of material removal at different current, pulse on and off times, gap voltages, and fraction of heat that enters the specimen. The PMEDM process produced craters with a lower diameter and depth, which increased the material removal rate and enhanced the surfacing quality. Compared to the conventional EDM process, the inclusion of powder raised the heat flux given to the work material by 10%–12%. It has been determined that with the single spark modeling technique, the temperature significantly dropped in both the radial and depth directions. The computational results are compared with experimental observations for similar machining conditions, and both results agree satisfactorily.

Machining characteristics in ultrasonic vibration-assisted powder-mixed electrical discharge machining of TiN ceramics

This study aims to investigate the application and machining characteristics of brittle conductive ceramics using ultrasonic vibration-assisted powder-mixed electrical discharge machining (UV-PMEDM) technology. Titanium nitride (TiN) ceramics are widely used in aerospace, biomedicine, and electronics due to their excellent properties. However, the conventional mechanical machining methods of these materials result in severe tool wear, high costs, and low efficiency. Although electrical discharge machining (EDM) can overcome some limitations, it typically exhibits a low material removal rate and poor surface quality. This study utilizes the UV-PMEDM technology to process TiN ceramics. Single-factor experiments are conducted to analyze the effects of processing parameters, including ultrasonic amplitude, powder concentration, pulse-on time, and pulse-off time, on the material removal rate, surface roughness, and relative electrode wear rate, which indicate the EDM processing performance. With the assistance of ultrasonic vibration and mixed powders, the material removal rate of TiN ceramics using UV-PMEDM reaches 0.50 mm3/min, while maintaining a relative electrode wear rate below 1 % and surface roughness lower than 4.2 μm. The synergistic combination of ultrasonic vibration and mixed powders significantly enhances the processing efficiency and reduces surface roughness of TiN ceramics. These findings contribute to a better understanding of machining strategies for brittle conductive ceramics.