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In electrical discharge machining (EDM) process, the production of separate electrodes for rough, semi‐rough and finish machining of dies and moulds having complex surfaces, results in high cost and long lead‐time in manufacturing. The purpose of this paper is to describe the machining performance of electrodes formed by using copper wire bunches (WBs) positioned to conform the surface to be machined was experimentally and theoretically analyzed. In the study, the variations in the machining rate, electrode wear rate, relative wear and workpiece surface roughness were examined for various discharge current and pulse‐time settings.

Copper WBs positioned to conform the surface to be machined in electric discharge machining. The variations in the machining rate, electrode wear rate, relative wear and workpiece surface roughness were examined experimentally for various discharge current and pulse‐time settings. The WB electrodes (WBEs) are proven to be satisfactory as electrodes for roughing operations in electric discharge machining.

The increase in number of wires and pulse energy result in decrease of relative wear for each wire in the electrode. The increase in number of wires in electrodes causes increase in machining area and in machining time in WBE method. With the increase of discharge current and pulse time, the electrode wear rate and material removal values increase and machining time decreases. By using the mathematical models obtained from the result of the experiments, the electrode wear rate, material removal rate, relative wear and the set length of wires for the desired cavity profile can be calculated. The labor cost of electrode manufacturing in the WBE method is lower compared to conventional solid electrodes. The use of WBE method for rough machining decreases machining cost and time. The use of WBE method decreases both the number of the electrodes required and the delay in starting machining due to the preparation of electrode in EDM.

This paper introduces the benefits of using WBE in electric discharge machining; wear and material removal characteristics of WBEs are introduced; the surface roughness characteristics of surfaces produced by WBEs are examined experimentally; and the effect of number of wires used in WBEs given (experimental findings).

Inconel 718 (IN718) is a high-performance nickel-based superalloy with high oxidation-corrosion-temperature resistance, high strength (tensile, fatigue, creep and rupture), durability, toughness, hardness and dimensional stability, which is difficult to machine with traditional fabrication methods. To overcome these difficulties, wire electrical discharge machining (WEDM), one of the modern manufacturing methods, is used.

Main performance criteria in WEDM; material removal rate (MRR), cutting speed, surface roughness, cutting width (kerf) and wire wear rate. In this study, the effect of processing parameters on kerf and MRR because of processing IN718 in WEDM was investigated. Machining parameters, voltage, wire feed rate and dielectric fluid pressure were determined. Deionized water was used as a dielectric fluid and 0.3 mm brass wire was used as wire in the experiments. Gray Relational Analysis (GRA), which is one of the multi-criteria decision-making methods, has been applied for the optimization of the machining parameters in the cutting process with the WEDM. Analysis of variance (ANOVA) was used to determine the effect percentages of the cut-off parameters.

The parameter with the highest effect was determined as tension with a rate of 76.95% for kerf and 91.21% for MRR.

The novel approach uses Taguchi-based GRA optimization as a result of cutting IN718 with WEDM, reducing cost and time consumption.

Wire electric discharge machining (WEDM) is a non-conventional machining process, which is used to provide difficult and intricate shapes. The purpose of this research work is to apply Taguchi’s technique to optimize the process parameters in WEDM. Alloy steel 20MnCr5 has been selected as base material for experimentation. The effects of the input process parameters such as wire type, pulse-on time, pulse-off time, peak current, wire feed rate and servo voltage have been calculated on the material removal rate (MRR) and surface roughness (Ra) in WEDM operation.

In the research work, Taguchi's technique is applied to optimize the process parameters in WEDM.

ANOVA indicated that pulse-off time was the most significant factor for the MRR, and servo voltage was the most significant factor for surface roughness (SR). As a part of the project, 20MnCr5 was machined in wire electric discharge machine, and the optimal control parameters were found to get higher MRR and better SR using Taguchi’s technique.

To the best of authors’ knowledge, after reviewing the literature, materials including alloys of metals such as 16MnCr5 and 20MnCr5 have not been investigated so far, and research regarding machining of these materials is limited. Therefore, 20MnCr5 material has been selected for this research work to generate WEDM data.

Tool steel (AISI D3) is a preferred material for industrial usage. Some of the typical applications of D3 tool steel are blanking and forming dies, forming rolls, press tools and punches bushes. It is used under conditions where high resistance to wear or to abrasion is required and also for resistance to heavy pressure rather than to sudden shock is desirable. It is a high carbon and high chromium steel. Therefore, wire electric discharge machining (WEDM) is used to machine this tool steel. The paper aims to discuss these issues.

The present experimental investigation evaluates the influence of cryogenically treated wires on material removal rate (MRR) and surface roughness (SR) for machining of AISI D3 steel using the WEDM process. Two important process responses MRR and SR have been studied as a function of four different control parameters, namely pulse width, time between two pulses, wire mechanical tension and wire feed rate.

It was found that pulse width was the most significant parameter which affects the MRR and SR. Better surface finish was obtained with cryogenically treated zinc coated wire than brass wire.

The review of the literature indicates that there is limited published work on the effect of machining parameters in WEDM in cryogenic treated wires. Therefore, in this research work, it was decided to evaluate the effect of cryogenically treated wires on WEDM.

The purpose of this paper is to investigate prediction and optimization of multiple performance characteristics in the wire electrical discharge machining (wire-EDM) process of SKD 61 (AISI H13) tool steel.

The experimental studies were conducted under varying wire-EDM process parameters, which were arc on time, on time, open voltage, off time and servo voltage. The optimized responses were recast layer thickness (RLT), surface roughness (SR) and surface crack density (SCD). Arc on time was set at two different levels, whereas the other four parameters were set at three different levels. Based on Taguchi method, an L18 mixed-orthogonal array was selected for the experiments. Further, three methods, namely grey relational analysis (GRA), backpropagation neural network (BPNN) and genetic algorithm (GA), were applied separately. GRA was performed to obtain a rough estimation of optimum drilling parameters. The influences of drilling parameters on multiple performance characteristics were determined by using percentage contributions. BPNN architecture was determined to predict the multiple performance characteristics. GA method was then applied to determine the optimum wire-EDM parameters.

The minimum RLT, SR and SCD could be obtained by setting arc on time, on time, open voltage, off time and servo voltage at 2 ms, 3 ms, 90 volt, 10 ms and 38 volt, respectively. The experimental confirmation results showed that BPNN-based GA optimization method could accurately predict and significantly improve all of the responses.

There were no publications regarding multi-response optimization using a combination of GRA and BPNN-based GA methods during wire-EDM process available.

The purpose of this paper is to investigate the surface integrity features, including surface roughness (SR), recast layer (RL), material migration, topography and wire wear pattern in rough and trim-cut wire electric discharge machine (WEDM) of hybrid composite (Al6061-90%/SiC-2.5%/TiB₂-7.5%).

Effects of four important factors, namely, rough-cut history (RCH), pulse on time (T_on), peak current (IP) and wire offset (WO) have been assessed on the responses of interest for trim-cut WEDM. Box–Behnken design (RSM) was used to formulate the experimentation plan. Quantitative indices of surface integrity, namely, SR and RL, and selected samples have been investigated for qualitative analysis, namely, surface topography, material migration and wire wear pattern.

T_on and IP are found to be most significant, whereas RCH and WO are found insignificant for SR. T_on and WO were found to be the most significant factors affecting RL. After trim cut, an RL of thickness 8.26 µm is observed if the initial rough cut has been accomplished at high discharge energy setting. Whereas the best value of RL thickness, i.e. 5.36 µm, can be realized with low level of RCH. A significant decrease in the presence of foreign materials is recorded, indicating its strong correlation with the discharge energy used during machining.

Investigation on surface integrity features for machining of hybrid composite through rough and trim-cut WEDM has been reported by only a limited number of researchers in the past. This study is attempted at fulfilling few vital gaps by addressing the issues such as evaluation of the efficacy of trim cutting under different discharge energy conditions (using RCH), analysis of wire wear pattern in both rough and trim-cut modes and investigation of the wire breakage phenomenon during machining.

This paper aims to present the performance of deionized water in electrical discharge machining (EDM) during machining of Inconel 718, copper tool electrode and deionized water as dielectric. Three parameters, namely, pulse-on-time, pulse-off-time and discharge current were taken as control parameters with individual parameter having three levels. Influence of these control parameters on response such as tool wear rate (TWR), material removal rate (MRR) and surface roughness (Ra) is evaluated at various combinations of parametric levels. The results reveal deionized water can be effectively used as a sustainable dielectric and may substitute the hydrocarbon-based dielectric in electrical discharge machining. Also, the control parameters considered show significant impact on the process criteria. Super ranking method was adopted to achieve optimal integration of EDM control factors for obtaining higher MRR, lower TWR and Ra. Further, by applying analysis of variance test, discharge current is established as the dominant parameter during the machining process.

The experimentation was performed on Inconel 718 in SPARKONIX MOS, 35 A, ZNC EDM using deionized water as dielectric and copper tool as electrode. The dielectric circulatory system was developed without disturbing the existing dielectric circulation system. Figure 1 shows the EDM with newly developed dielectric system. The existing system consists of hydrocarbon-based dielectric, which has a number of drawbacks during the machining such as carbide deposition on the work material, which reduces removal of material from work material; carbon particle adhesion on tool, which results in inefficient discharge between the electrode; and the work material and production of CO and CH4 during machining, which makes the machining environment toxic. To overcome these drawbacks, a sustainable dielectric was adopted in present work. Trial experiments were conducted to select the ranges of parameters, namely, discharge current, pulse-on-time and pulse-off-time. The process characteristics were evaluated at different parametric combinations and the experimentation was designed as per Taguchi L9 orthogonal array. Table 1 shows the properties of Inconel 718. Table 2 shows the parameters considered with its ranges. Table 3 shows the experimental values. The difference of weight of work piece before and after was taken and divided by the machining time used for calculating the MWR. Similarly, the difference of weight of tool material before and after was taken and divided by machining time and is used for calculating TWR. Measurement of surface roughness was done using Talysurf surface roughness meter.

The experimentation was conducted at different parametric combination on Inconel 718 taking copper as electrode and deionized water as dielectric. The performance criteria was evaluated at considered parametric combination. The result shows that the EDM parameters have significant contribution on the performance criteria and deionized water can be effectively used as dielectric medium in EDM. The use of deionized water as dielectric will improve the process and sustainable green machining can be performed. Super ranking method has been implemented to achieve the best combination of control factors and it is obtained that the combination A1B1C3 (i.e. discharge current = 3 A, pulse-on-time = 1 µs and pulse-off-time = 3 µs) is best combination for obtaining the higher MRR and lower TWR and Ra. The contributing factor in the proposed research work is discharge current. Further, ANOVA was implemented to check the adequacy of these result. It was established that discharge current is the most influential factor followed by pulse-on-time and the least contributing factor as pulse-off-time. The findings of this paper may open the guidelines for researcher for performing research in the field of sustainable machining of difficult to cut materials such as Inconel 718 with sustainable dielectrics in engineering applications.

The paper is original in nature. The findings of this paper may open the guidelines for researcher for performing research in the field of sustainable machining.

Ti_49.4Ni_50.6 (at. %) shape memory alloy (SMA) is a unique class of smart materials because of unbeatable property which given a wide variety of their applications across a broad range of fields including an orthopedic implant. It plays a very important role in the constructions of novel orthopedic implants application (like dynamic compression plate) because of lower Young’s modulus compared to other biomedical implant materials, high mechanical strength, excellent corrosion resistance and unique property like shape memory effect. Conventional machining of Ti-Ni yields poor surface finish and low dimensional accuracy of the machined components. Hence, wire electro-discharge machining (WDEM) of Ti-Ni has been performed. The purpose of this paper is to investigate the effect of variation of five process parameters, namely, a pulse-on time, pulse-off time, spark gap set voltage (SV), wire feed and wire tension on the material removal rate, surface roughness (SR), kerf width (KW) and dimensional deviation (DD), in the WDEM of Ti_49.5Ni_50.6 SMA.

The effect of machining parameters on Ti_49.4Ni_50.6 has been fully explored using WEDM with zinc coated brass wire as an electrode. In this work, L18 orthogonal array based on Taguchi method has been used to conduct a series of experiments and statically evaluate the experimental data by the use of the method of analysis of variance. Scanning electron microscope images of the machined surface, at the highest and lowest pulse-on time, have been taken to evaluate the quality of surface in terms of their SR values.

For the highest pulse-on time, it is observed that blow holes, cracks, melted droplets and craters have been formed on the machined surface with an SR of 2.744 µm, while for the lowest pulse-on time, these are not formed with an SR of 0.862 µm. It is seen that the pulse-on time is the most significant process parameter for MRR, SR and KW, while the DD is significantly affected by spark gap SV. The optimal values of the process parameters have been obtained by the method of analysis of mean and the confirmatory experiments have been carried out to validate results of optimization. Energy dispersive spectroscopy analysis of the machined surface of Ti_49.4Ni_50.6 has shown a certain amount of deposition of material on the machined surface.

This is an original paper.

To meet the requirements of high-dimensional accuracy and surface finish of various advanced engineering materials for generating intricate part geometries, non-traditional machining (NTM) processes have now become quite popular in manufacturing industries. To explore the fullest machining capability of these NTM processes, it is often required to operate them while setting their different controllable parameters at optimal levels. This paper aims to present a novel approach for selection of the optimal parametric mixes for different NTM processes in order to assist the concerned process engineers.

In this paper, design of experiments (DoE) and technique for order preference by similarity to ideal solution (TOPSIS) are combined to develop the corresponding meta-models for identifying the optimal parametric combinations of two NTM processes, i.e. electrical discharge machining (EDM) and wire electrical discharge machining (WEDM) processes with respect to the computed TOPSIS scores.

For EDM operation on Inconel 718 alloy, lower settings of open circuit voltage and pulse-on time and higher settings of peak current, duty factor and flushing pressure will simultaneously optimize all the six responses. On the other hand, for the WEDM process, the best machining performance can be expected to occur at a parametric combination of zinc-coated wire, lower settings of pulse-on time, wire feed rate and sensitivity and intermediate setting of pulse-off time.

As the development of these meta-models is based on the analysis of the experimental data, they are expected to be more practical, being immune to the introduction of additional parameters in the analysis. It is also observed that the derived optimal parametric settings would provide better values of the considered responses as compared to those already determined by past researchers.

This DoE–TOPSIS method-based approach can be applied to varieties of NTM as well as conventional machining processes to determine the optimal parametric combinations for having their improved machining performance.

The purpose of the study is to establish a predictive model for sustainable wire electrical discharge machining (WEDM) by using adaptive neuro fuzzy interface system (ANFIS). Machining was done on Titanium grade 2 alloy, which is also nicknamed as workhorse of commercially pure titanium industry. ANFIS, being a state-of-the-art technology, is a highly sophisticated and reliable technique used for the prediction and decision-making.

Keeping in the mind the complex nature of WEDM along with the goal of sustainable manufacturing process, ANFIS was chosen to construct predictive models for the material removal rate (MRR) and power consumption (Pc), which reflect environmental and economic aspects. The machining parameters chosen for the machining process are pulse on-time, wire feed, wire tension, servo voltage, servo feed and peak current.

The ANFIS predicted values were verified experimentally, which gave a root mean squared error (RMSE) of 0.329 for MRR and 0.805 for Pc. The significantly low RMSE verifies the accuracy of the process.

ANFIS has been there for quite a time, but it has not been used yet for its possible application in the field of sustainable WEDM of titanium grade-2 alloy with emphasis on MRR and Pc. The novelty of the work is that a predictive model for sustainable machining of titanium grade-2 alloy has been successfully developed using ANFIS, thereby showing the reliability of this technique for the development of predictive models and decision-making for sustainable manufacturing.