Investigation of magnetic field-assisted EDM of composites

The Electrical Discharge Machining (EDM) technique was performed under the magnetic field influence to determine the material removal mechanism as well as surface roughness (SR) of nonmagnetic material. This study presents an exploration of the hybrid EDM technique assisted by magnetic field, with an aim to improve process performance. Herein, magnetic field intensity, peak current, duration of pulse-on/off, tool electrode material, and SiC percentage distribution were opted as the machining parameters. The chosen parameters were analyzed for their effects on the material removal rate (MRR) and SR while machining of SiC-reinforced aluminum-based metal matrix composites. Taguchi methodology was adopted for optimization of process parameters to achieve better MRR and lower SR. The experimental results witnessed improved surface finish and enhanced material removal ability of the process and also inferred that the magnetic field-assisted EDM facilitated the process stability.     

Constrained multi-objective optimization of EDM process parameters using kriging model and particle swarm algorithm

This paper investigates the highly nonlinear relationship between process parameters and machining responses, including material removal rate (MRR), surface roughness (SR), and electrode wear rate (EWR) of electric discharge machining (EDM) using Kriging model. Subsequently, an emerging multi-objective optimization algorithm called particle swarm is used to determine the best machining conditions that not only maximize the machining speed but also minimize the EWR with a constraint of the SR. The experiment was carried out with P20 steel on a CNC EDM machine using copper electrode. The research result shows that the MRR increases sharply when increasing the discharge current just like other researches pointed out. However, the relationship between EWR and current is complicated. EWR appears the minimum value when the current is around 30?A. The speed of change of MRR per unit of EWR is the highest when the SR is around 14.5?µm. The combination of Kriging regression model and particle swarm optimization is considered as an intelligent process modeling and optimization of EDM machining. The proper selection of process parameters helps the EDM operator to reduce the machining time and cost.     

Parametric optimization of multiwalled carbon nanotube-assisted electric discharge machining of Al-10%SiCp metal matrix composite by response surface methodology

The demand for miniaturized products having a glossy surface or nano-level surface is increasing exponentially in automobile, aerospace, biomedical, and semiconductor industries. The mirror-like surface finish has generated a need to develop advanced machining processes. The addition of powder particle into electric discharge machining (EDM) oil is considered a promising technique to achieve surface integrity at the miniaturization level. In this research, the Al–10%SiC_p metal matrix composite (MMC) has been machined after mixing the appropriate amount of multiwalled carbon nanotubes (MWCNTs) into the EDM dielectric fluid. An advanced experimental setup has been designed and fabricated in the laboratory for conducting the experiments. This proposed technology is called nano powder mixed electric discharge machining (NPMEDM). The input parameters of NPMEDM are also optimized using central composite rotatable design (CCRD) based on response surface methodology (RSM) in order to obtain the best surface finish and material removal rate (MRR). The MRR has been increased by 38.22% and surface finish has been improved by 46.06% after mixing the MWCNTs into the EDM dielectric fluid. The results indicate that the combination of parameters A5, B5, C5, and D5 might have produced maximum MRR, whereas A1, B1, C1, and D3 have produced minimum surface roughness (SR).     

Optimization of material removal rate and surface roughness during electric discharge machining of ultra-fine grained Al6082 using Taguchi technique

In the current work, the statistical analysis of various electric discharge machining parameters on Al6082 ultra-fine grained aluminium alloy using Taguchi method has been presented. Repetitive corrugation and straightening (RCS) method was employed to obtain ultra-fine grained aluminium alloy. The electric discharge machining studies were carried out for test variables – pulse off time, pulse on time and current (I). The specimens were machined in dielectric medium with current range of 3 A to 9 A in step of 3 A. Machining features of the samples analysed statistically by adopting the Taguchi's - design of experiments (DOE) methodology. Impact of parameters on material removal rate (MRR) and surface roughness (SR) were examined via signal-to-noise ratio (S/N ratio, expressed in decibel, dB) as well as analysis-of-variance (ANOVA). Outcomes disclose that every selected response explicitly surface roughness (SR) and material removal rate was significantly influenced by parameters. The material removal rate was found to rise with discharge current and decrease with the duration of pulse on time and the duration of pulse off time. On the other hand, the surface roughness increased with increase in peak current and decreased with pulse on time and pulse off time especially. The machining mechanisms were examined by scanning electron microscopy.     

Optimization of photochemical machining process parameters for manufacturing microfluidic channel

In the present study, the investigation on photochemical machining (PCM) of stainless steel (SS-304) by ferric chloride as etchant is reported. SS-304 is machined by PCM process to obtain accurate dimensions and better geometrical features. Weighted grey relational analysis (WGRA) technique is used in optimization of PCM process parameters. DoE (L₂₇) orthogonal array is applied to evaluate machining parameters, such as concentration of etchant, etching time, and temperature of etchant. The multiobjective optimization technique is used to optimize material removal rate (MRR), surface roughness (R_a), undercut (U_c) and etch factor (EF). Weighted grey relational grade is calculated to minimize U_c and surface roughness and to maximize MRR and EF. The quality characteristics MRR, EF, U_c, and R_a are reporting the improvement after the confirmatory test. The optimum machining parameters are processed to manufacture the microfluidic channel used in biomedical applications. The microfluidic channels and its assembly with Y-type for mixing of fluid with a size of 100 µm, 200 µm, and 300 µm are developed and investigated.     

WEDM of Mg/CRT/BN composites: Effect of materials and machining parameters

The current work presents a detailed exploration on real-time wire electric discharge machining (WEDM) experiments and grey relational analysis (GRA)–based multi-criteria optimization of material and machining characteristics for lowered surface roughness (R_a) and improvised material removal rate (MRR) of the newly developed magnesium/boron nitride/cathode ray tube (Mg/BN/CRT) hybrid metal matrix composites (MMCs). The composites were fabricated through powder metallurgy (PM) route by reinforcing silica-rich E-waste CRT panel glass powder crushed for different particle sizes (10, 30, and 50?µm) at various weight percentages (5%, 10%, and 15%) and with 2% boron nitride (BN). Taguchi-based orthogonal array procedure was utilized to formulate the experimental plan for WEDM considering reinforcement level and size, pulse on time (P_on), pulse off time (P_off), and wire feed (W_f) as the input process parameters. ANOVA results reveal that P_on and wt% of reinforcement has more effect on R_a and MRR than any other considered parameters. The developed mathematical model for R_a and MRR predicted values similar to that of experimental results. Multi-criteria optimization was done through GRA technique and the so recommended optimum parameter set furnishes higher MRR (22.34?mm³/min) and reduced R_a (2.87?µm).     

Performance evaluation of Al2O3 nano powder mixed dielectric for electric discharge machining of Inconel 825

Electrical discharge machining (EDM) process is popular for machining conductive and difficult-to-cut materials, but low material removal rate (MRR) and poor surface quality are major limitations of the process. These limitations can be overcome by adding the suitable powder in the dielectric. The powder particles influence electric field intensity during the EDM process which in turn improve its performance. The size (micro to nano) and properties of the mixed powder also influence the machining efficiency. In this regard, the objective of the present work is to study the performance of EDM process for machining Inconel 825 alloy by mixing Al₂O₃ nanopowder in deionized water. The experimental investigation revealed that maximum MRR of 47?mg/min and minimum SR of 1.487?µm, which are 44 and 51% higher in comparison to conventional EDM process, respectively, can be achieved by setting optimal combinations of process parameters. To analyze these observed process behavior, pulse-train data of the spark gap were acquired. The discharge waveform identifies the less arcing phenomenon in the modified EDM process compared to conventional EDM. Further, surface-topography of the machined surface was critically examined by capturing field emission scanning electron microscopy and atomic force microscopy images.     

Effect of deep cryotreated tungsten carbide electrode and SiC powder on EDM performance of AISI 304

Abstract

Powder mixed electric discharge machining (PMEDM) is a further advancement of conventional EDM process in which electrically conductive powder is suspended in the dielectric fluid to enhance the material removal rate (MRR) along with the surface quality. Cryotreatment is introduced in this process for improving the cutting tool properties as well as tool life. In this investigation, EDM is performed for the machining of AISI 304 stainless steel using cryotreated double tempered tungsten carbide electrode when SiC powder is suspended in the kerosene dielectric. The influence of process parameters viz. pulse on time, peak current, duty cycle, gap voltage and powder concentration on tool wear rate (TWR), surface roughness (R_a), and MRR has been studied. Metallographic analysis was carried out for the machined surfaces. By the addition of powder concentration and cryotreated double tempered electrode, significant improvement in the machining efficiency has been found out. When cryotreated electrode used MRR, TWR and R_a decreased by 12%, 24% and 13.3%, respectively and when SiC powder used MRR increased by 23.2%, TWR and R_a decreased by about 25% and 14.2%, respectively.     

Application of new tool material for electrical discharge machining (EDM)

In EDM, Cu and graphite are commonly used as tool materials. The poor wear resistance is the drawback of these tools. In the current study, an attempt has been made to develop a ZrB₂-Cu composite as an EDM tool material to overcome this problem. Initially, the ZrB₂ powder is prepared by self-propagating high-temperature synthesis (SHS) technique and synthesized powder is mixed with different amounts of Cu powder. Dense composite is developed by a pressureless sintering at 1250°C. The composites are tested as tool material at different EDM process parameters during machining of mild steel. The ZrB₂-40 wt% Cu composite shows highest metal removal rate (MRR) with significant tool removal rate (TRR) than other composites. The performance of ZrB₂-40 wt% Cu composite is compared to conventional Cu tool. The composite shows higher MRR with less TRR than Cu tool but it shows more average surface roughness and diameteral overcut than Cu tool.     

Multi-attribute decision-making of cryogenically cooled micro-EDM drilling process parameters using TOPSIS method

The geometrical characteristics of the micro-holes along with the performance measures are matter of critical concern in micro-electrical discharge machining (μEDM) process. This paper presents the multi-attribute decision-making of cryogenically cooled micro-EDM (CμEDM) drilling process. Current (I_p), pulse on duration (T_on), pulse off duration (T_off), and gap voltage (V_g) were the input process parameters preferred to optimize the multiple responses of geometrical characterization including taper angle (TA), overcut (OC), circularity at the entry and exit (C_ent and C_exit), and performance measures including material removal rate (MRR), tool wear rate (TWR), and average roughness (R_a). The Taguchi-based L₂₇ orthogonal array (OA) is used to carry out the experimental runs, and technique for order of preference by similarity ideal solution (TOPSIS) approach is used for the identification of optimal parameters on AISI 304 stainless steel. The optimized result achieved from this approach suggests improved TA, OC, C_ent, C_exit, MRR, and lower TWR, surface roughness (SR) with the combinations of CμEDM drilling process such as I_p of 15 A, T_on of 10?µs, T_off of 30?µs, and V_g of 30?V. Analysis of variance (ANOVA) was conducted to identify the major influencing parameter.     

Experimental investigation and optimization during the fabrication of arrayed structures using reverse EDM

In recent years, reverse electric discharge machining (R-EDM) has been evolved as a method for the fabrication of arrayed structures for surface texturing which find applications in fabrication of fins and component assembly. In this study, the feasibility of R-EDM process in the fabrication of arrayed features of ?3?mm and height 2?mm on mild steel has been investigated utilizing response surface methodology (RSM)-based experimentation. Influence of control variables such as peak current (I_p), pulse-on time (T_on), and flushing pressure (F_p) on some of the vital geometric characteristics like taper and cylindricity error along with material removal rate (MRR), surface roughness (SR), microhardness, and surface morphology of pillared structure has been investigated. Analysis of variance (ANOVA) results show that I_p has a significant influence followed by T_on on MRR. I_p has a significant contribution toward SR, taper, and cylindricity error. High microhardness was found in heat-affected zone (HAZ). The optimal combination of parameter obtained using principal component analysis (PCA)-based grey relational analysis (GRA) is determined to be I_p?=?10 A, T_on?=?100 μs, and F_p?=?0.3?kg/cm², which was further ascertained using confirmatory test.     

WEDM process parameter optimization of FSPed copper-BN composites

A systematic view on evaluating the machining characteristics of Wire Cut Electrical Discharge Machining (WEDM) employing Taguchi Method and Grey Relational Analysis based multiobjective optimization is provided in this research article. The outcome of various WEDM processing parameters including pulse discharge on time (Pulse_ON), pulse discharge off time (Pulse_OFF), wire feed rate (Wire_FR) along with the material characteristics of varying Boron Nitride (BN) volume fractions while machining a friction stir processed (FSPed) copper-BN surface composite was investigated. The output responses considered in this research include Material Removal Rate (MRR) and Surface roughness (R_a) that was obtained from the L27 orthogonal array based on the above said input factors. ANOVA was performed, and Pulse_ON and BN volume fraction were found most significant for MRR, while Pulse_ON and Pulse_OFF influence the most in attaining minimal R_a values. Based on the obtained experimental values for MRR and R_a, a mathematical model was developed based on the control factors and was proved to be precise in predicting the output response. An optimal combination of input control factors was finalized through grey relational analysis, and the same proved to achieve the utmost MRR (20.19?mm³/min) and nominal R_a(3.01?µs) values.     

Parametric Evaluation on Near-Dry Electric Discharge Machining

Near-dry electric discharge machining (EDM) is an eco-friendly process. It does not produce toxic fumes and consequent health hazards. The near-dry EDM generally utilizes a mixture of two phase (liquid and air) dielectric for machining. This investigation reports the influence of four processing parameters, viz. current, flushing pressure, duty factor, and lift on three responses. The responses measured were material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR). The work material chosen was high speed steel (HSS). Mathematical models have been proposed herein for evaluation of the effect of processing parameters in near-dry EDM. These models were developed using response surface methodology (RSM). The experimental results reveal that the process parameters taken into consideration were significant for MRR. The TWR was negligible in near-dry EDM. This process gives a finer surface finish with thinner recast layer even at higher discharge energies as compared to conventional EDM.     

Effect of tool rotation in near-dry EDM process on machining characteristics of HSS

Rotary tool near-dry electrical discharge machining (RT-ND-EDM) is a process variant of EDM, which utilizes two phase dielectric medium instead of a conventional liquid or gaseous dielectric medium. The present work, RT-ND-EDM was investigated while machining of high speed steel (AISI M2 grade) using glycerin-air dielectric medium. The effect of various input process parameters was investigated on material removal rate (MRR), surface roughness (SR), and hole overcut (HOC). The input parameters considered were tool rotation speed, current, pulse on time, liquid flow rate, and gas pressure. Experiments were designed and conducted using response surface methodology. Regression models were also developed. The results revealed that the tool rotation speed has a significant effect on MRR, SR, and HOC. FE-SEM micrographs showed that the machined surfaces obtained by RT-ND-EDM have relatively lower micro-cracks, debris accumulation and craters. Also, deep through holes were successfully drilled in 24 mm plate using RT-ND-EDM process.     

Influence of input parameters on the near-dry WEDM of Monel alloy

Near-dry wire electrical discharge machining (WEDM) is a modified WEDM process, which has no adverse effects on the environment, in which metal removals have been done with the dielectric medium being used in the form of a mist. As the increase in production by reducing the machining time is a costly affair, the input parameters attract considerable attention for their optimization. The predominant control characteristics in this study are the time-bound material removal and surface quality. The time duration of the electrical pulse on and off, wire feed, air inlet pressure, and water flow rate are the parameters considered for this experimental analysis. In this paper, the optimization techniques such as RSM method and analysis of variance (ANOVA) were used to route the experiments and optimize the responses of near-dry WEDM process for machining the material Monel alloy. A model has been formulated mathematically for the two vital responses needed, under the influence of regression analysis. Additivity test has been performed to validate the mathematical model. The air–water mixture in the form of a mist was used in place of dielectric medium to study the impact on material removal rate (MRR), surface roughness (R_a), and environment. It was observed that a high surface finish could be obtained at 3 bar pressure.     

Modeling and Analysis of Machinability Evaluation in the Wire Electrical Discharge Machining (WEDM) Process of Aluminum Oxide-Based Ceramic

The wire electrical discharge machining (WEDM) allowed success in the manufacture of the hard, fragile, and materials difficult to cut, especially for electroconductive ceramic materials. In this study, the mathematical models of material removal rate (MRR) and surface roughness (SR) used for the machinability evaluation in the WEDM process of aluminum oxide-based ceramic material (Al₂O₃ + TiC) have been carried out. The experimental plan adopts the face centered central composite design (CCD). The mathematical models using the response surface methodology (RSM) are developed so as to investigate the influences of four machining parameters, including the peak current, pulse on time, duty factor, and wire speed, on the performance characteristics of MRR and SR. It has been proved that the proposed mathematical models in this study would fit and predict values of the performance characteristics, which would be close to the readings recorded in experiment with a 95% confidence level. The significant parameters that critically affect the performance characteristics are examined.     

Examinations concerning the electric discharge machining of AZ91/5B4CP composites utilizing distinctive electrode materials

In this study, investigation has been conducted in the focus of obtaining better surface finish in the electro discharge machining (EDM) of AZ91/5B₄C_p magnesium composites using distinctive sort of anode viz. copper, tungsten–copper, brass, aluminum and 20Gr/AA6061 (GRAL-20) composites. The process parameters, pulse on time and current were performed to research the machining qualities through material removal rate (MRR) and tool wear rate (TWR). The machined composites were examined by optical microscopy (OM) and scanning electron microscopy (SEM). The formation of black spots was observed on machining with copper–tungsten and these black spots were not found when GRAL-20 was used as electrode. Machined with GRAL-20 electrode leads to the increase in spark gap, hence adequate flushing occurs; it eliminates re-melted layers on machined surface results in better surface roughness value. The results revealed that GRAL-20 electrodes posses better MRR followed by copper electrode whereas tungsten–copper exhibits better TWR followed by GRAL-20 electrode.     

Experimental analysis of magneto rheological abrasive flow finishing process on AISI stainless steel 316L

In this experimental study, the surface quality of AISI stainless steel 316L was improved to a nano-level surface finish by means of magneto rheological abrasive flow finishing process. In order to determine the effect of input process parameters toward the responses such as final surface roughness (SR) and material removal rate (MRR), response surface model was built up and optimal parameters were found using the desirability analysis. Based on the experimental design, 20 experiments were conducted and the minimum SR and maximum MRR obtained are 53.46?nm and 1.757?mg/s, respectively, and their optimized values are 53.10?nm and 1.817?mg/s. By using the regression equations obtained for SR and MRR as input, an evolutionary optimization algorithm called as firefly algorithm has been utilized where the required surface finish was constrained as ≤60?nm and the optimized results were confirmed by means of validation experiments. The obtained results depict that the voltage to the electromagnet plays a most significant role to produce minimum SR and maximum MRR. Moderate and least significant contributions are given by the hydraulic pressure and number of cycles, respectively, toward the responses.     

Influence of materials and machining parameters on WEDM of Al/AlCoCrFeNiMo0.5 MMC

The current study intends to optimize the wire electric discharge machining (WEDM) parameters while machining the newer AlCoCrFeNiMo_0.5 high entropy alloy (HEA) particles-reinforced aluminum composites. AlCoCrFeNiMo_0.5 HEA particles produced through arc melting technique are reinforced here for different weight % (0%, 3%, 6%, 9%, 12%, and 15%) along with pure aluminum by the way of powder metallurgy. WEDM studies were conducted by varying the appropriate parameters, namely, pulse ON time, pulse OFF time, and wire feed. Based on the selected parameters, through Taguchi method L18 orthogonal array is designed; the optimal parameter combination for better surface finish, material removal rate (MRR), and reduced kerf width (KW) is identified. For better understanding, through ANOVA, also the effect of each input variables over these adopted response variables was analyzed. The yielded results reveal that addition of AlCoCrFeNiMo_0.5 HEA as reinforcement has considerable effect over the response variablessuch that MRR and KW reduces; surface roughness increases with increase in HEA %. ANOVA results confirm that pulse ON time has higher effect over the response variables than any other parameters involved for the study. Multi-objective optimization done through Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodology answers that MRR and surface finish have improved, whereas KW gets reduced noticeably.