Multi-response optimization of EDM with Al–Cu–Si–TiC P/M composite electrode

The present study investigates the relationship of process parameters in electro-discharge of CK45 steel with novel tool electrode material such as Al–Cu–Si–TiC composite produced using powder metallurgy (P/M) technique. The central composite second-order rotatable design had been utilized to plan the experiments, and response surface methodology (RSM) was employed for developing experimental models. Analysis on machining characteristics of electrical discharge machining (EDM) die sinking was made based on the developed models. In this study, titanium carbide percent (TiC%), peak current, dielectric flushing pressure, and pulse on-time are considered as input process parameters. The process performances such as material removal rate (MRR) and tool wear rate (TWR) were evaluated. Analysis of variance test had also been carried out to check the adequacy of the developed regression models. Al–Cu–Si–TiC P/M electrodes are found to be more sensitive to peak current and pulse on-time than conventional electrodes. The observed optimal process parameter settings based on composite desirability are TiC percent of 18%, peak current of 6 A, flushing pressure of 1.2 MPa, and pulse on-time of 182 μs for achieving maximum MRR and minimum TWR; finally, the results were experimentally verified. A good agreement is observed between the results based on the RSM model and the actual experimental observations. The error between experimental and predicted values at the optimal combination of parameter settings for MRR and TWR lie within 7.2% and 4.74%, respectively.     

Investigations into the effect of tool shapes with size factor consideration in sink electrical discharge machining (EDM) process

In sink electric discharge machining (EDM) process, the tool shape and size along with wear are of great importance because they adversely affect the accuracy of machined features. This paper presents the application of response surface methodology (RSM) for investigating the effect of tool shapes such as triangular, square, rectangular, and circular with size factor consideration along with other process parameters like discharge current, pulse on-time, pulse off-time, and tool area. The RSM-based mathematical models of material removal rate (MRR) and tool wear rate (TWR) have been developed using the data obtained through central composite design. The analysis of variance was applied to verify the lack of fit and adequacy of the developed models. Further, the confirmation tests were performed to ascertain the accuracy of the developed models. The investigations revealed that the best tool shape for higher MRR and lower TWR is circular, followed by triangular, rectangular, and square cross sections. From the parametric analysis, it is also observed that the interaction effect of discharge current and pulse on-time is highly significant on MRR and TWR, whereas the main factors such as pulse off-time and tool area are statistically significant on MRR and TWR.     

Comparative study of different dielectrics for micro-EDM performance during microhole machining of Ti-6Al-4V alloy

In microelectrodischarge machining (micro-EDM), dielectric plays an important role during machining operation. The machining characteristics are greatly influenced by the nature of dielectric used during micro-EDM machining. Present paper addresses the issues of micro-EDM utilizing different types of dielectrics such as kerosene, deionized water, boron carbide (B₄C) powder suspended kerosene, and deionized water to explore the influence of these dielectrics on the performance criteria such as material removal rate (MRR), tool wear rate (TWR), overcut, diameteral variance at entry and exit hole and surface integrity during machining of titanium alloy (Ti-6Al-4V). The experimental results revealed that MRR and TWR are higher using deionized water than kerosene. Also, when suspended particles, i.e., boron carbide-mixed dielectrics are used, MRR is found to increase with deionized water, but TWR decreases with kerosene dielectric. Further analysis is carried out with the help of scanning electron microscope (SEM) micrographs, and it is found that the thickness of white layer is less on machined surface when deionized water is used as compared to kerosene. Also, a comparative study of machining time has been carried out for the four types of dielectrics at different machining parametric settings. Furthermore, the investigation on the machined surface integrity and wear on microtool tip have also been done in each type of the dielectrics with the help of SEM micrographs and optical photographs. Hence micro-EDM machining on Ti-6Al-4V work material with B₄C-mixed dielectrics is performed in the investigation and reported the performance criteria of the process. It can be concluded from the research investigation that there is a great influence of mixing of boron carbide additive in deionized water dielectrics for enhancing machining performance characteristics in micro-EDM during microhole generation on Ti-6Al-4V alloy.     

INVESTIGATING THE EFFECTS OF EDM PARAMETERS ON SURFACE INTEGRITY,MRR AND TWR IN MACHINING OF Ti–6Al–4V

Ti–6Al–4V is a kind of difficult-to-cut material with poor machinability by traditional machining methods, while electrical discharge machining (EDM) is suitable for machining titanium alloys. In this paper, three input machining parameters including pulse current, pulse on time and open circuit voltage were changed during EDM tests. To investigate the output characteristics; material removal rate (MRR), tool wear ratio (TWR) and different aspects of surface integrity for Ti–6Al–4V samples such as topography of machined surface, crack formation, white layer (recast layer) thickness and microhardness were considered as performance criteria. The variations of MRR and TWR versus input machining parameters were investigated by means of main and interaction effect plots and also verified by ANOVA results. The effect of pulse energy based on pulse on time and pulse current variations against recast layer thickness and microhardness was studied. The possibility of forming different chemical elements and compounds on the work surface after EDM process was investigated by EDS and XRD analyses. The experimental results revealed that general aspects of surface integrity for machined samples are mostly affected by pulse current and pulse on time. The approximate density of cracks, micro holes and pits on the work surface is intensively dependent on pulse energy variations. Although increase of pulse energy improves the material removal efficiency but leads to increase of average thickness and microhardness of recast layer.     

Effects of Powder Characteristics on Electrodischarge Machining Efficiency

This paper presents the effects of various powder characteristics on the efficiency of electrodischarge machining (EDM) SKD-11. The additives examined include aluminium (Al), chromium (Cr), copper (Cu), and silicon carbide (SiC) powders that have significant differences in their thermophysical properties. The machining mechanism with the addition of the foreign particles, the tool wear rate (TWR), and the material removal rate (MRR) have been investigated. It was found experimentally that the particle concentration, the particle size, the particle density, the electrical resistivity, and the thermal conductivity of powders were important characteristics that significantly affected the machining performance in the EDM process. Proper addition of powders to the dielectric fluid increased the MRR and, thus, decreased the TWR. Under the same particle concentration experiments, the smallest suspended particle size led to the greatest MRR and, thus, the lowest TWR. Of the additives investigated, chromium powder produced the greatest MRR and the lowest TWR, whereas the process without foreign particles has the converse effects. The addition of copper powder to the dielectric fluid was found to make almost no difference to the pure kerosene EDM system.     

Influence of parameters and optimization of EDM performance measures on MDN 300 steel using Taguchi method

Maraging steel (MDN 300) exhibits high levels of strength and hardness. Optimization of performance measures is essential for effective machining. In this paper, Taguchi method, used to determine the influence of process parameters and optimization of electrical discharge machining (EDM) performance measures on MDN 300 steel, has been discussed. The process performance criteria such as material removal rate (MRR), tool wear rate (TWR), relative wear ratio (RWR), and surface roughness (SR) were evaluated. Discharge current, pulse on time, and pulse off time have been considered the main factors affecting EDM performance. The results of the present work reveal that the optimal level of the factors for SR and TWR are same but differs from the optimum levels of the factors for MRR and RWR. Further, discharge current, pulse on time, and pulse off time have been found to play a significant role in EDM operations. Detailed analysis of structural features of machined surface was done by using scanning electron microscope (SEM) to understand the influence of parameters. SEM of electrical discharge machining surface indicates that at higher discharge current and longer pulse on duration give rougher surface with more craters, globules of debris, pockmarks or chimneys, and microcracks than that of lower discharge current and lower pulse on duration.     

Investigation of near dry EDM compared with wet and dry EDM processes

Journal of Mechanical Science and Technology - Material removal rate (MRR), tool wear ratio (TWR) and surface roughness (SR) obtained by near-dry EDM process were compared with wet and dry EDM at...     

超声电火花复合加工速度工艺试验研究

电火花加工的最大缺点是加工速度低，为了解决这个问题，人们进行了各种试验研究。其中超声电火花复合在加工小孔中可一定程度地提高加工速度，但就其作用机理和适用范围仍存在许多争论。本次试验在D703F高速电火花小孔加工机床上附加陶瓷换能器和变幅杆，通过夹紧装置将变幅杆与工具电极相连，实现电极超声振动的电火花小孔加工。在不同的电参数（电流强度和脉冲宽度）和电极参数（电极直径）下，进行了2种加工方法下的加工速度对比试验。找到了在加工小孔时，是否采用超声电火花复合加工工艺的分界点，对其增加加工速度的现象提出了新的解释。     

Multi-response optimization of machining process parameters for powder mixed electro-discharge machining of H-11 die steel using grey relational analysis and topsis

Electro-discharge machining (EDM) is an enormously used nonconventional process for removing material in die making, aerospace, and automobile industries. It consists of limitations like poor volumetric material removal rate (MRR) and reduced surface quality. Powder mixed EDM (PMEDM) is a new development in EDM to enhance its machining capabilities. The present work investigates the effect of powder concentration (C_p), peak current (I_p), pulse on time (T_on), duty cycle (DC) and gap voltage (V_g) on MRR, tool wear rate (TWR), electrode wear ratio (EWR), and surface roughness (SR) simultaneously for H-11 die steel using SiC powder. Taguchi's L₂₇ orthogonal array has been used to conduct the experiments. Multiobjective optimization using grey relational analysis (GRA) and technique for order of preference by similarity to ideal solution (TOPSIS) has been used to maximize the MRR and minimize the TWR, EWR, and SR and determine the optimal set of process parameters. Analysis of variance (ANOVA) has been performed to understand the significance of each process parameter. Results were verified by conducting confirmatory tests. GRA and TOPSIS exhibit an improvement of 0.1843 and 0.14308 in the preference values, respectively. Microstructure analysis has been done using scanning electron microscope (SEM) for the optimum set of parameters.     

Neuro-fuzzy and neural network-based prediction of various responses in electrical discharge machining of AISI D2 steel

In the present research, two neuro-fuzzy models and a neural network model are presented for predictions of material removal rate (MRR), tool wear rate (TWR), and radial overcut (G) in die sinking electrical discharge machining (EDM) process for American Iron and Steel Institute D2 tool steel with copper electrode. The discharge current (I _p), pulse duration (T _on), duty cycle (τ), and voltage (V) are considered as inputs to the network. A full-factorial design was used to conduct the experiments with various levels of I _p, T _on, τ, and V. The analysis of variance results reveal that I _p is the most influencing factor for MRR and G, having the highest degree of contributions of 87.61% and 81.90%, respectively. In case of TWR, T _on has the highest degree of contribution of 46.05% and is the most significant factor. The half of the experimental data set was used to train the networks and was tested for convergence with a different set of data to obtain appropriate number of neurons, epoch, and the fuzzy rule base. The mean square error convergence criteria, both in training and testing, came out very well. The developed models are found to approximate the responses quite accurately. Moreover, the predicted results based on above models have been confirmed with unseen validation set of experiments and are found to be in good agreement with the experimental results. The comparison results reveal that the artificial neural network and the neuro-fuzzy models are comparable in terms of accuracy and speed, and further, the proposed models can be employed successfully in prediction of MRR, TWR, and G of the stochastic and complex EDM process.     

Drilling of micro-holes on copper using electrochemical micromachining

Electrochemical micromachining (EMM) is one of the best micromachining techniques for machining electrically conducting, tough, and difficult-to-machine materials with suitable machining parameter combinations. For the micro-fabrication of components like nozzle plate for ink jet printer head and delicate 3D electronic circuit board components, EMM is predominantly used. In this paper, the effect of process parameters such as such as electrolyte concentration, machining voltage, frequency, and duty cycle on the material removal rate (MRR) and overcut were studied using copper workpiece. According to Taguchi’s quality design concepts, an L₁₈ orthogonal array is used. ANOVA is also performed to determine the most significant parameter that influences the EMM process. The optimum process parameters for lower overcut and higher MRR are found out and confirmation tests were carried out to validate the prediction. The confirmation test results show 19 and 20.78?% improvements of overcut and MRR, respectively, with respect to the initial parametric setting.     

Material removal rate and electrode wear ratio study on the powder mixed electrical discharge machining of cobalt-bonded tungsten carbide

In this article, a material removal rate (MRR) and electrode wear ratio (EWR) study on the powder mixed electrical discharge machining (PMEDM) of cobalt-bonded tungsten carbide (WC-Co) has been carried out. This type of cemented tungsten carbide was widely used as moulding material of metal forming, forging, squeeze casting, and high pressure die casting. In the PMEDM process, the aluminum powder particle suspended in the dielectric fluid disperses and makes the discharging energy dispersion uniform; it displays multiple discharging effects within a single input pulse. This study was made only for the finishing stages and has been carried out taking into account the four processing parameters: discharge current, pulse on time, grain size, and concentration of aluminum powder particle for the machinability evaluation of MRR and EWR. The response surface methodology (RSM) has been used to plan and analyze the experiments. The experimental plan adopts the face-centered central composite design (CCD). This study highlights the development of mathematical models for investigating the influence of processing parameters on performance characteristics.     

Optimal parameter settings for rough and finish machining of die steels in powder-mixed EDM

The present study was undertaken to identify the appropriate parameter settings for rough and finish machined surface for EN31, H11, and high carbon high chromium (HCHCr) die steel materials in a powder-mixed electric discharge machining process. The effect of seven different process variables along with some of their interactions was evaluated using a dummy-treated experimental design and analysis of variance. Material removal rate (MRR), tool wear rate, and surface finish were measured after each trial and analyzed. The parameter settings for rough and finished machining operations were obtained. EN31 exhibited maximum MRR as compared to the other two materials at similar process settings. Copper (Cu) electrode with aluminum suspended in the dielectric maximized the MRR. Suspending powder in the dielectric resulted in surface modification. Graphite powder showed a lower MRR but improved the surface finish. HCHCr require higher current and pulse on settings for initiating a machining cut and works best in combination with tungsten–Cu electrode and graphite powder for improved finish. The MRR for H11 is lower than EN31 but significantly higher than HCHCr under same process conditions.     

Optimization of machining parameters in the abrasive waterjet turning of alumina ceramic based on the response surface methodology

A study on the radial-mode abrasive waterjet turning (AWJT) of 96 % alumina ceramic is presented and discussed. An experimental investigation is carried out to explore the influence of process parameters (including water pressure, jet feed speed, abrasive mass flow rate, surface speed, and nozzle tilted angle) on the material removal rate (MRR) when turning 96 % alumina ceramic. The experiments are conducted on the basis of response surface methodology (RSM) and sequential approach using face-centered central composite design. The quadratic model of RSM associated with the sequential approximation optimization (SAO) method is used to find optimum values of process parameters in terms of surface roughness and MRR. The results show that the MRR is influenced principally by the water pressure P and the next is abrasive mass flow rate m _a . The optimization results show that the MRR can be improved without increasing the surface roughness when machining 96 % alumina ceramic in the radial-mode abrasive waterjet turning process.     

Effect of ultrasonic vibration of tool on electrical discharge machining of cemented tungsten carbide (WC-Co)

This paper deals with the effect of copper tool vibration with ultrasonic (US) frequency on the electrical discharge machining (EDM) characteristics of cemented tungsten carbide (WC-Co). It was found that ultrasonic vibration of the tool (USVT) was more effective in attaining a high material removal rate (MRR) when working under low discharge currents and low pulse times (finishing regimes). In general, the surface roughness and the tool wear ratio (TWR) were increased when ultrasonic vibration was employed. It was observed that application of ultrasonic vibration significantly reduced arcing and open circuit pulses, and the stability of the process had a remarkable improvement. This study showed that, there were optimum conditions for ultrasonic assisted machining of cemented tungsten carbide, although the conditions may vary by giving other input parameters for those which had been set constant in the present work.     

Employing severe plastic deformation to the processing of electrical discharge machining electrodes

The tool electrode has a significant role in electrical discharge machining (EDM) performance, as it affects machining efficiency, surface quality and the geometrical accuracy of the machined component. This study presents a new approach for developing a pure copper electrode using severe plastic deformation (SPD) to enhance the machining characteristics during EDM. Equal channel angular pressing (ECAP) is selected because it is the most successful SPD method of processing bulk materials. Finite element analysis, microstructural assessment as well as nanoindentation tests are carried out to determine the behavior of pure copper after one and two ECAP passes. The effectiveness of EDM when using ECAP-treated electrodes is evaluated by introducing new techniques of measuring the volumetric overcut (VOC) and corner sharpness. In addition, tool wear rate (TWR), material removal rate (MRR), electrode wear ratio, surface roughness, surface crack density and the critical crack zone are studied. The results emphasize that an electrode subjected to one pass of ECAP can enhance the workpiece accuracy by decreasing the VOC and increasing corner sharpness by 13 and 66%, respectively. It is also revealed that the nanohardness enhancement following ECAP leads to lower TWR and electrode wear ratio. An investigation of the surface characteristics indicates a thinner recast layer is achieved when using one ECAP pass-treated electrode, which leads to 26% lower surface crack density.     

Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing electro chemical machining process

Electrochemical machining process (ECM) is increasing its importance due to some of the specific advantages which can be exploited during machining operation. The process offers several special privileges such as higher machining rate, better accuracy and control, and wider range of materials that can be machined. Contribution of too many predominate parameters in the process, makes its prediction and selection of optimal values really complex, especially while the process is programmized for machining of hard materials. In the present work in order to investigate effects of electrolyte concentration, electrolyte flow rate, applied voltage and feed rate on material removal rate (MRR) and surface roughness (SR) the adaptive neuro-fuzzy inference systems (ANFIS) have been used for creation predictive models based on experimental observations. Then the ANFIS 3D surfaces have been plotted for analyzing effects of process parameters on MRR and SR. Finally, the cuckoo optimization algorithm (COA) was used for selection solutions in which the process reaches maximum material removal rate and minimum surface roughness simultaneously. Results indicated that the ANFIS technique has superiority in modeling of MRR and SR with high prediction accuracy. Also, results obtained while applying of COA have been compared with those derived from confirmatory experiments which validate the applicability and suitability of the proposed techniques in enhancing the performance of ECM process.     

分散剂在电火花小孔加工中的作用机理及试验研究

从研究水分散剂的分散机理入手,分析研究了水分散剂对电火花小孔加工的排屑、加工速度和加工质量的影响。通过电火花小孔加工中采用自来水工作液和分散剂工作液的加工效果对比,发现在电火花小孔加工的水基工作液中加入一定比例的分散剂后,不仅使电火花小孔加工的加工速度提高、电极相对损耗降低,而且有效脉冲数增加,二次放电数明显减少,工具电极作用端和被加工孔的锥度变小,加工质量提高。     

Finite element prediction of material removal rate due to traveling wire electrochemical spark machining

Manufacturing engineers are facing new challenges during machining of electrically nonconducting or partially conducting materials such as glass, quartz, ceramics, and composites. Traveling wire electrochemical spark machining (TW-ECSM), a largely unknown technology, has been applied successfully for cutting these types of materials. However, hardly any theoretical work has been reported related to machining performance of TW-ECSM process. The present work is an attempt in this direction. In the present work, a 3-D finite element transient thermal model has been developed to estimate the temperature field and material removal rate (MRR) due to Gaussian distributed input heat flux of a spark during TW-ECSM. First, the developed code calculates the temperature field in the workpiece and then MRR is calculated using this temperature field. The calculated MRR has been compared with the experimental MRR for verifying the approach. Computational experiments have been performed for the determination of energy partition and spark radius of a single spark. The effects of various process parameters such as energy partition, duty factor, spark radius, and ejection efficiency on MRR have been reported. It has been found that MRR increases with increase in energy partition, duty factor, and ejection efficiency but decreases with increase in spark radius.     

Investigation of electro-discharge micro-machining of titanium super alloy

Being a difficult-to-cut material, titanium alloy suffers poor machinability for most cutting processes, especially the drilling of micro-holes using traditional machining methods. Although electrical discharge machining (EDM) is suitable for machining titanium alloys, selection of machining parameters for higher machining rate and accuracy is a challenging task in machining micro-holes. The present research attempts to optimize micro-EDM process parameters for machining Ti-6Al-4V super alloy. To verify the optimal micro-EDM process parameters settings, metal removal rate (MRR), tool-wear rate (TWR), over cut (OC) and taper were chosen as observed performance criteria. In addition, four independent parameters such as peak current, pulse-on time, flushing pressure, and duty ratio were adopted for evaluation by the Taguchi method. From the ANOVA and S/N ratio graph, the significant process parameters and the optimal combination level of machining parameters were obtained. It is seen that machining performances are affected mostly by the peak current and pulse-on time during micro-electro-discharge machining of titanium alloy. Mathematical models have been developed to establish the relationship between various significant process parameters and micro-EDM performance criteria. In-depth studies have also been made to examine the influence of various process parameters on the white layer and surface topography through SEM micrographs of machined micro-hole.