Optimisation of process parameters for multi-performance characteristics in EDM of Al2O3 ceramic composite

The advantages of electrical discharge machining (EDM) in machining of complex ceramic components have promoted research in the area of EDM of ceramic composites. The recent developments in ceramic composites are focused not only on the improvements of strength and toughness, but also on possibilities for difficult-to-machine shapes using EDM. One such EDM-machinable ceramic composite material (Al₂O₃–SiC_w–TiC) has been developed recently and has been selected in the present study to investigate its EDM machinability. Experiments were conducted using discharge current, pulse-on time, duty cycle and gap voltage as typical process parameters. The grey relational analysis was adopted to obtain grey relational grade for EDM process with multiple characteristics namely material removal rate and surface roughness. Analysis of variance was used to study the significance of process variables on grey relational grade which showed discharge current and duty cycle to be most significant parameters. Other than discharge current and duty cycle, pulse-on time and gap voltage have also been found to be significant. To validate the study, confirmation experiment has been carried out at optimum set of parameters and predicted results have been found to be in good agreement with experimental findings.     

Performance and surface alloying characteristics of Cu–Cr and Cu–Mo powder metal tool electrodes in electrical discharge machining

The main objective of this study is to investigate the effect of Cu–Cr and Cu–Mo powder metal (PM) tool electrodes on electrical discharge machining (EDM) performance outputs. The EDM performance measures used in the study are material removal rate (MRR), tool electrode wear rate (EWR), average workpiece surface roughness (R_a), machined workpiece surface hardness, abrasive wear resistance, corrosion resistance, and workpiece alloyed layer depth and composition. The EDM performance of Cu–Cr and Cu–Mo PM electrodes produced at three different mixing ratios (15, 25, and 35 wt% Cr or Mo), compacting pressures (P_c = 600, 700, and 800 MPa), and sintering temperatures (T_s = 800, 850, and 900 °C) are compared with those machined with electrolytic Cu and Cu PM electrodes when machining SAE 1040 steel workpiece. Analyses revealed that tool materials were deposited as a layer over the work surface yielding high surface hardness, strong abrasion, and corrosion resistance. Moreover, the mixing ratio, P_c, and T_s affect the MRR, EWR, and R_a values.     

A dual response surface-desirability approach to process modeling and optimization of Al2O3 powder-mixed electrical discharge machining (PMEDM) parameters

This paper presents an effort to model and optimize the process parameters involved in powder-mixed electrical discharge machining (PMEDM). Aluminum oxide (Al₂O₃) fine abrasive powders with particle concentration and size of 2.5–2.8 g/L and 45–50 μm, respectively, were added into the kerosene dielectric liquid of a die-sinking electrical discharge machine. The experiments were carried out in planing mode on a specially designed experimental set up developed in laboratory. The CK45 heat-treated die steel and commercial copper was used as work piece and tool electrode materials, respectively. Response surface methodology, employing a face-centered central composite design scheme, has been used to plan and analyze the experiments. Based on the preliminary and screening tests as well as the working characteristics of selected EDM machine, discharge current (I), pulse-on time (T _on), and source voltage (V) were designated as the independent input variables to assess the process performance in terms of material removal rate (MRR) and surface roughness (Ra). Suitable mathematical models for the response outputs were obtained using the analysis of variance technique, in which significant terms (main effects, two factor interactions, and pure quadratic terms) were chosen according to their p values less than 0.05 (95 % of confidence interval). Having established the suitable regression equations, a search optimization procedure, based on the use of desirability functions, optimizes the process performance in each machining regime of finishing (Ra?≤?3 μm), semifinishing (3 μm?≤?Ra?≤?4.5 μm), and roughing (Ra?≥?4.5 μm). The results are sets of optimum points which make the MRR as high as possible and keep the Ra and all machining parameters in their specified ranges simultaneously. Finally, the modeling and obtained optimization results were also discussed and verified experimentally. It was shown that the error between experimental and anticipated values at the optimal combination settings of input variables are all less than 11 %, confirming the feasibility and effectiveness of the adopted approach.     

Optimization of machining parameters using magnetic-force-assisted EDM based on gray relational analysis

This work developed a novel process of magnetic-force-assisted electrical discharge machining (EDM) and conducted an experimental investigation to optimize the machining parameters associated with multiple performance characteristics using gray relational analysis. The main machining parameters such as machining polarity (P), peak current (I _P), pulse duration (τ _P), high-voltage auxiliary current (I _H), no-load voltage (V), and servo reference voltage (S _V) were selected to explore the effects of multiple performance characteristics on the material removal rate, electrode wear rate, and surface roughness. The experiments were conducted according to an orthogonal array L18 based on Taguchi method, and the significant process parameters that affected the multiple performance characteristics of magnetic-force-assisted EDM were also determined form the analysis of variance. Moreover, the optimal combination levels of machining parameters were also determined from the response graph and then verified experimentally. The multiple performance characteristics of the magnetic-force-assisted EDM were improved, and the EDM technique with high efficiency, high precision, and high-quality surface were established to meet the demand of modern industrial applications.     

Development of an inversion model for establishing EDM input parameters to satisfy material removal rate, electrode wear ratio and surface roughness

Electro-discharge machining (EDM) has grown tremendously over the last few decades. Due to its extensive capabilities, this technique has been increasingly adapted to new industrial applications within the field of aerospace, medical, die and mould production, precision tooling, etc. The novelty of the research presented in this paper lies in solving an inversion model, based on the least squares theory, which involves establishing the values of the EDM input parameters (peak current level, pulse-on time and pulse-off time) to ensure the simultaneous fulfilment of material removal rate (MRR), electrode wear ratio (EWR) and surface roughness (SR). The inversion model was constructed from a set of experiments and the equations formulated in the forward model described in the first part of this paper. In the forward model, the well-known ANOVA and regression models were used to predict the EDM output performance characteristics, such as MRR, EWR and SR in the EDM process for AISI 1045 steel with respect to a set of EDM input parameters.     

Surface Improvement Using a Combination of Electrical Discharge Machining with Ball Burnish Machining Based on the Taguchi Method

This study investigates the feasibility of improving surface integrity via a novel combined process of electrical discharge machining (EDM) with ball burnish machining (BBM) using the Taguchi method. To provide burnishing immediately after the EDM process, ZrO₂ balls were attached to the tool electrode in the experiments. To verify the optimal process, three observed values, i.e. material removal rate, surface roughness, and improvement ratio of surface roughness were chosen. In addition, six independent parameters were adopted for evalu-ation by the Taguchi method. From the ANOVA and S/N ratio response graph, the significant parameters and the optimal combination level of machining parameters were obtained. Experimental results indicate that the combined process effectively improves the surface roughness and eliminates the micro pores and cracks caused by EDM. Therefore, the combination of EDM and BBM is a feasible process by which to obtain a fine-finishing surface and achieve surface modification.     

Fabrication of micro-end mill tool by EDM and its performance evaluation

Abstract

Micro-milling is a fast, cheap and controlled process compared to other micro-fabrication processes such as lithography, laser/electron/ion beam machining, etc. However, scarcity of cutting tools of very small dimensions often results in limited application of micro-milling. In the present study, electro discharge machining (EDM) is used for fabrication of micro-end mill tool. To ensure high dimensional accuracy of the tool, a parametric study is conducted by replicating the a tungsten carbide block to a tungsten carbide (WC) block. The relationships between the drilled cavities on the block and the features on the micro-tool are established. The influence of machining parameters (voltage, capacitance and spindle speed) on the response variables (entrance diameter, hole depth, material removal rate (MRR) and surface roughness) is reported. Capacitance is found more dominant as compared to other selected process parameters. Using optimized parameters from the parametric study, a WC micro-end mill tool of 100?µm diameter is fabricated. Channel of around 110 µm width, 40?µm depth and surface roughness of 70?nm is successfully fabricated on aluminum. The performance of the fabricated tool is compared with a commercial end mill tool by milling micro channels on stainless steel.     

The effect of process parameters on machining of magnesium nano alumina composites through EDM

The effects of electrical discharge machining (EDM) parameters on drilled-hole quality such as taper and surface finish are evaluated. Microwave-sintered magnesium nano composites (reinforced with 0.8 and 1.2 wt.% of nano alumina) are used as work materials. Experiments were conducted using Taguchi methodology to ascertain the effects of EDM process parameter. The process parameters such as pulse-on time, pulse-off time, voltage gap, and servo speed were optimized to get better surface finish and reduced taper. ANOVA analyses were carried out to identify the significant factors that affect the hole accuracy and the surface roughness. Confirmation tests were performed on the predicted optimum process parameters. Pulse-on time and the servo speed are identified as major response variables. Micro structural changes and the effects of nano particle reinforcement in the drilled hole were studied through SEM micrographs.     

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.     

Assessing the effects of different dielectrics on environmentally conscious powder-mixed EDM of difficult-to-machine material (WC-Co)

Electrical discharge machining (EDM) is a well-known nontraditional manufacturing process to machine the difficult-to-machine (DTM) materials which have unique hardness properties. Researchers have successfully performed hybridization to improve this process by incorporating powders into the EDM process known as powder-mixed EDM process. This process drastically improves process efficiency by increasing material removal rate, micro-hardness, as well as reducing the tool wear rate and surface roughness. EDM also has some input parameters, including pulse-on time, dielectric levels and its type, current setting, flushing pressure, and so on, which have a significant effect on EDM performance. However, despite their positive influence, investigating the effects of these parameters on environmental conditions is necessary. Most studies demonstrate the use of kerosene oil as dielectric fluid. Nevertheless, in this work, the authors highlight the findings with respect to three different dielectric fluids, including kerosene oil, EDM oil, and distilled water using one-variable-at-a-time approach for machining as well as environmental aspects. The hazard and operability analysis is employed to identify the inherent safety factors associated with powder-mixed EDM of WC-Co.     

Soft computing models and intelligent optimization system in electro-discharge machining of SiC/Al composites

In this paper, a multi-variable regression model, a back propagation neural network (BPNN) and a radial basis neural network (RBNN) have been utilized to correlate the cutting parameters and the performance while electro-discharge machining (EDM) of SiC/Al composites. The four cutting parameters are peak current (I_p), pulse-on time (T_on), pulse-off time (T_off), and servo voltage (S_v); the performance measures are material remove rate (MRR) and surface roughness (Ra). By testing a large number of BPNN architectures, 4-5-1 and 4-7-1 have been found to be the optimal one for MRR and Ra, respectively; and it can predict them with 10.61 % overall mean prediction error. As for RBNN architectures, it can predict them with 12.77 % overall mean prediction error. The multivariable regression model yields an overall mean prediction error of 13.93 %. All of these three models have been used to study the effect of input parameters on the material remove rate and surface roughness, and finally to optimize them with genetic algorithm (GA) and desirability function. Then, an intelligent optimization system with graphical user interface (GUI) has been built based on these multi-optimization techniques, in which users can obtain the optimized cutting parameters under the desired surface roughness (Ra).     

Estimating the effect of process parameters on surface integrity of EDMed AISI D2 tool steel by response surface methodology coupled with grey relational analysis

In this investigation, a hybrid optimization approach is used for the estimation of minimal surface integrity of surface created in electrical discharge machining (EDM). A new combination, response surface methodology coupled with the grey relational analysis method has been proposed and used to optimize the machining parameters of EDM. The significant input parameters such as pulse current (Ip), pulse duration (Ton), duty cycle (Tau) and discharge voltage (V ) are considered, and white layer thickness, surface roughness, and surface crack density have been considered as responses for this study. Thirty experiments were conducted on American Iron and Steel Institute (AISI) D2 steel work piece materials based on central composite design. The optimum conditions of the machining parameters were obtained from the grey relational grade. Analysis of variance is used to find the percentage contribution of the input parameters and found that Tau was the most influencing parameter followed by Ton and Ip in EDM of D2 steel. The $R^2$ value for the grey relational grade model was 0.918. These results provide useful information about how to control the responses and ensure the high-quality surfaces-quality surfaces. This method is simple with easy operability. The assessment outcome provides a scientific reference to obtain the minimal condition of surface integrity, and they were found to be a pulse current of 1 A, a pulse duration of 50 μs, a duty cycle of 80 %, and discharge voltage 40 V.     

Modelling and experimental investigation of process parameters in EDM of Si<Subscript>3</Subscript>N<Subscript>4</Subscript>-TiN composites using GRA-RSM

Electric discharge machining (EDM) is a highly promising machining process of ceramics. This research is an out of the paradigm investigation of EDM on Si₃N₄-TiN with Copper electrode. Ceramics are used for extrusion dies and bearing balls and they are more efficient, effective and even have longer life than conventional metal alloys. Owing to high hardness of ceramic composites, they are almost impossible to be machined by conventional machining as it entirely depends on relative hardness of tool with work piece. Whereas EDM offers easy machinability combined with exceptional surface finish. Input parameters of paramount significance such as current (I), pulse on (P_on) and off time (P_off), Dielectric pressure (DP) and gap voltage (SV) are studied using L₂₅ orthogonal array. With help of mean effective plots the relationship of output parameters like Material removal rate (MRR), Tool wear rate (TWR), Surface roughness (Ra), Radial overcut (ROC), Taper angle (α), Circularity (CIR), Cylindricity (CYL) and Perpendicularity (PER) with the considered input parameters and their individual influence were investigated. The significant machining parameters were obtained by Analysis of variance (ANOVA) based on Grey relational analysis (GRA) and value of regression coefficient was determined for each model. The results were further evaluated by using confirmatory experiment which illustrated that spark eroding process could effectively be improved.     

Improving Electrical Discharge Machined Surfaces Using Magnetic Abrasive Finishing

Abstract

A recast layer is invariably present on surfaces produced by electrical discharge machining (EDM). For some metals with high hardness, the recast layer may contain micro-cracks. This damaged layer can affect the service life of the parts produced by this method. This investigation demonstrates that magnetic abrasive finishing (MAF) process using unbonded magnetic abrasives (UMA), can improve the quality of EDM machined surfaces effectively. The UMA used herein is a mechanical mixture of steel grit and SiC abrasive. SKD11 tool steel was used as the workpiece. Experimental results show that the recast layer and micro-cracks on EDM machined surfaces can be completely removed and a new surface of roughness on the order of 0.04 μm Ra can be produced. Additionally, experiments using the Taguchi method and L₁₈ orthogonal array enable the determination of the optimum process conditions for improving the surface finish. Further, the significance of the control factors was identified with the assistance of analysis of variance (ANOVA), and the optimum combination of the process parameters was verified by conducting several confirmatory experiments.     

Reducing electrode wear ratio using cryogenic cooling during electrical discharge machining

In this study, cooling effect of copper electrode on the die-sinking of electrical discharge machining of titanium alloy (Ti-6Al-4V) has been carried out. Investigation on the effect of cooling on electrode wear and surface roughness of the workpiece has been carried out. Design of experiment plan for rotatable central composite design of second order with four variables at five levels each has been employed to carry out the investigation. Current intensity (I), pulse on-time (t _on), pulse off-time (t _off), and gap voltage (v) were considered as the machining parameters, while electrode wear and surface roughness are the responses. Analysis of the influence of cooling on the responses has been carried out and presented in this study. It was possible to reduce electrode wear ratio up to 27% by electrode cooling. Surface roughness was also reduced while machining with electrode cooling.     

Experimental Investigation on Electrical Discharge Drilling of Ti-6Al-4V Alloy

This article describes the experimental investigation related to creation of holes in aerospace titanium alloy workpiece using static electrode machining and electrical discharge drilling (EDD) process. Special attachment for holding and rotating the tool electrode was developed and installed on electrical discharge machining (EDM) machine by replacing the original conventional tool holder provided on die sinking EDM. The effect of input parameters such as gap current, pulse on-time, duty factor and RPM of tool electrode on output parameters for average hole circularity (C_a) and average surface roughness (R_a) have been studied. It is observed that the effect of rotating electrode machining has considerable influence on the output parameters over stationary electrode machining. The micro-graphs and photographs of few selected samples were taken by SEM and metallurgical microscope, which also commensurate with the findings of the study.     

Experimental investigation and parameter optimization of near-dry wire-cut electrical discharge machining using multi-objective evolutionary algorithm

The near-dry wire-cut electrical discharge machining (WEDM) process is an environment-friendly manufacturing process, in which there is no harmful effect to the operators. The authors focus on the non-polluting ways to cut the materials and to meet the technical requirements like high material removal rate (MRR) and low surface roughness (Ra). In the near-dry WEDM, the finite discrete periodic series sparks between the wire electrode and conducting work material separated by minimum quantity of deionized water mixed with compressed air (air-mist) as a dielectric medium. In the present research, parametric analysis of the process has been performed with the molybdenum wire tool and high speed steel (HSS-M2) work piece. Experiments have been performed using air-mist as the dielectric medium to study the impact of gap voltage, pulse-on time, pulse-off time, air-mist pressure and discharge current on the MRR and Ra using the mixed orthogonal (L₁₈) array-Taguchi method. Taguchi based analysis of variance test was performed to identify the significant parameters. The gap voltage, pulse-on time, discharge current and air-mist pressure were found to have momentous effects on MRR and Ra. The best regression models for MRR and Ra have been developed by regression analysis. The optimal rough and finish cutting parameters have been predicted by Pareto-front using the multi-objective evolutionary algorithm (MOEA).     

Modeling and analysis of the effects of machining parameters on the performance characteristics in the EDM process of Al2O3+TiC mixed ceramic

Electric discharge machining (EDM) has achieved remarkable success in the manufacture of conductive ceramic materials for the modern metal industry. Mathematical models are proposed for the modeling and analysis of the effects of machining parameters on the performance characteristics in the EDM process of Al₂O₃+TiC mixed ceramic which are developed using the response surface methodology (RSM) to explain the influences of four machining parameters (the discharge current, pulse on time, duty factor and open discharge voltage) on the performance characteristics of the material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR). The experiment plan adopts the centered central composite design (CCD). The separable influence of individual machining parameters and the interaction between these parameters are also investigated by using analysis of variance (ANOVA). This study highlights the development of mathematical models for investigating the influences of machining parameters on performance characteristics and the proposed mathematical models in this study have proven to fit and predict values of performance characteristics close to those readings recorded experimentally with a 95% confidence interval. Results show that the main two significant factors on the value of the material removal rate (MRR) are the discharge current and the duty factor. The discharge current and the pulse on time also have statistical significance on both the value of the electrode wear ratio (EWR) and the surface roughness (SR).     

Application of Taguchi-grey multi responses optimization on process parameters in electro erosion

Convention Taguchi method deals with only single response optimization problems. Since the electrical discharge machining process involved with many response parameters, Taguchi method alone cannot help to obtain optimal process parameters in such process. In the present work, an endeavor has been made to derive optimal combination of electrical process parameters in electro erosion process using grey relational analysis with Taguchi method. This multi response optimization of the electrical discharge machining process has been conducted with AISI 202 stainless steel with different tool electrodes such as copper, brass and tungsten carbide. Gap voltage, discharge current and duty factor have been used as electrical excitation parameters with different process levels. Taguchi L₂₇ orthogonal table has been assigned for conducting experiments with the consideration of interactions among the input electrical process parameters. Material removal rate, electrode wear rate and surface roughness have been selected as response parameters. From the experimental results, it has been found that the electrical conductivity of the tool electrode has the most influencing nature on the machining characteristics in EDM process. The optimal combination of the input process parameters has been obtained using Taguchi-grey relational analysis.     

An integrated optimization of cutting parameters and tool path generation in ultraprecision raster milling

This paper provides a new methodology for the integrated optimization of cutting parameters and tool path generation (TPG) based on the development of prediction models for surface roughness and machining time in ultraprecision raster milling (UPRM). The proposed methodology simultaneously optimizes the cutting feed rate, the path interval, and the entry distance in the feed direction to achieve the best surface quality in a given machining time. Cutting tests are designed to verify the integrated optimization methodology. The experimental results show that, in the fabrication of plane surface, the changing of entry distance improves surface finish about 40 nm (R _a ) and 200 nm (R _t ) in vertical cutting and decreases about 8 nm (R _a ) and 35 nm (R _t ) in horizontal cutting with less than 2 s spending extra machining time. The optimal shift ratio decreases surface roughness about 7 nm (R _a ) and 26 nm (R _t ) in the fabrication of cylinder surfaces, while the total machining time only increases 2.5 s. This infers that the integrated optimization methodology contributes to improve surface quality without decreasing the machining efficiency in ultraprecision milling process.