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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.

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.

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.

Wire electric discharge machining (WEDM) is a non-conventional machining process, which is used for cutting parts of civil and military aircraft, rotorcraft, satellites and spacecraft. The cold work steel X153CrMoV12 is used in molds that are needed to produce plastic and metal parts used in these areas. It is only possible to produce parts with precise dimensions and quality with the use of mold steels with sensitive surfaces. The purpose of this study is to analyze X153CrMoV12 material by cutting it with WEDM method in precise dimensions.

The effects of varying cutting parameters on the size of the finished product, surface roughness (SR) and surface hardness were determined by making rough in one pass and precision cuts in different passes. Nikon SMZ745T, Mitutoyo micrometer, Mitutoyo SJ-210 and Insize ISHL-P100 were used for macro-analysis, dimensional control, SR and surface hardness, respectively, to determine the cut qualities.

According to the hardness measurement results obtained from the steel surface before cutting and from the cut surfaces after cutting, there was no significant change in the surface hardness owing to the use of heat-treated steel. Increasing the wire tension as a result of the increase in the number of cutting passes and the decrease in the amount of rough stock left for the final cut increased the cut quality. Cutting precision has increased by preventing vibration of the wire with zero upper and lower water pressure required for slag cleaning.

There are many studies on WEDM in the literature, but there is no similar study emphasizing the importance of the processing parameters such as the number of cutting passes and rough stock amount. In this study, cold work steel with a hardness of 56–60 HRC was machined as rough cut in one pass, rough and fine cut in double pass, double fine cut after one roughing in three passes. As a result of the cuts, 3 µm measurement precision and 0.998 Ra SR were obtained as well as there was no hardness change in the cut surfaces.

An experimental study has been conducted to model and optimize wire electric discharge machining (WEDM) process parameters such as pulse-on time, pulse-off time, servo voltage and peak current for response characteristics during machining of Nimonic 75 alloy.

The response surface methodology (RSM)-based Box–Behnken's design has been employed for experimental investigation. RSM is used for developing quadratic regression models for selected response variables i.e. material removal efficiency and kerf width. To validate the model, confirmation experiments have been performed. The multi-response optimization has been done using desirability function approach.

Through analysis of variation, the percent contribution of process parameters on the response characteristics has been found. Pulse-off time is the most significant parameter affecting the kerf width and material removal efficiency followed by pulse-on time. The quadratic regression models have been developed for prediction of selected response variables. An attempt has been made to optimize the WEDM parameters for material removal efficiency and kerf width. The recommended process parameter setting for maximum material removal efficiency and minimum kerf width have been found to be pulse-on time = 0.6 µs, pulse-off time = 14 µs, servo voltage = 25 V and peak current = 200 A.

The “kerf width” is an important response variable for maintaining dimensional accuracy of the machined component, but has not been given due attention by the researchers. In the present work, the developed regression model for “kerf width” can be used in estimating wire offset setting and thereby getting a dimensionally accurate product. The optimum process parameters obtained in WEDM of Nimonic 75 alloy will contribute in database of machining. The outcome of this study would be added to scare database of the machining of Nimonic 75 alloy and also would be extremely useful for making the technology charts for WEDM.

This study aims to investigate the influence of process parameters of wire electrical discharge machining (WEDM) of Nimonic75. Nimonic75 is a Nickel-based alloy mostly used in the aerospace industry for its strength at high temperature.

One factor at a time (OFAT) approach has been used to perform the experiments. Pulse on time, pulse off time, peak current and servo voltage were chosen as input process parameters. Cutting speed, material removal rate and surface roughness (Ra) were selected as output performance characteristics.

Through experimental work, the effect of process parameters on the response characteristics has been found. Results identified the most important parameters to maximize the cutting speed and material removal rate and minimize Ra.

Very limited research work has been done on WEDM of Nickel-based alloy Nimonic75. Therefore, the aim of this paper to conduct preliminary experimentation for identifying the parameters, which influence the response characteristics such as material removal rate, cutting speed, Ra, etc. during WEDM of Nickel-based alloy (Nimonic75) using OFAT approach and found the machinability of Nimonic75 for further exhaustive experimentation work.

This paper aims to investigate the influence of “BroncoCut-X” (copper core-ZnCu50 coating) electrode on the machining of Ti-3Al-2.5V in view of its extensive use in aerospace and medical applications. The machining parameters are selected as Spark-off Time (ST_off), Spark-on Time (ST_on), Wire-speed (S_w), Wire-Tension (WT) and Servo-Voltage (S_v) to explore the machining outcomes. The response characteristics are measured in terms of material removal rate (MRR), average kerf width (KW) and average-surface roughness (SA).

Taguchi’s approach is used to design the experiment. The “AC Progress V2 high precision CNC-WEDM” is used to conduct the experiments with ϕ 0.25 mm diameter wire electrode. The machining performance characteristics are examined using main effect plots and analysis of variance. The grey-relation analysis and fuzzy interference system techniques have been developed to combine (called grey-fuzzy reasoning grade) the experimental response while Rao-Algorithm is used to calculate the optimal performance.

The hybrid optimization result is obtained as ST_off = 50µs, ST_on = 105µs, S_w = 7 m/min, WT = 12N and S_v=20V. Additionally, the result is compared with the firefly algorithm and improved gray-wolf optimizer to check the efficacy of the intended approach. The confirmatory test has been further conducted to verify optimization results and recorded 8.14% overall machinability enhancement. Moreover, the scanning electron microscopy analysis further demonstrated effectiveness in the WEDMed surface with a maximum 4.32 µm recast layer.

The adopted methodology helped to attain the highest machinability level. To the best of the authors’ knowledge, this work is the first investigation within the considered parametric range and adopted optimization technique for Ti-3Al-2.5V using the wire-electro discharge machining.

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.