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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 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.

Machining of curved channels using electrical discharge machining (EDM) is a novel approach. In this study, an experimental setup was designed, developed and mounted on die-sinking EDM to manufacture curve channels in AISI P20 mold steel.

The effect of specific machining parameters such as peak current, pulse on time, duty factor and lift over material removal rate (MRR) and tool wear rate (TWR) were studied. Multi-objective optimization was performed using Taguchi technique and Jaya algorithm.

The experimental results revealed current and pulse on time to have the predominant effect over material removal and tool wear diagnostic parameters with contributions of 39.67, 32.04% and 43.05, 36.52%, respectively. The improvements in material removal and tool wear as per the various optimization techniques were 35.48 and 10.91%, respectively.

Thus, Taguchi method was used for effective optimization of the machining parameters. Further, nature-based Jaya algorithm was implemented for obtaining the optimum values of TWR and MRR.

The electric discharge machining (EDM) involves electrons discharged from the electrode and machining progresses due to the removal of the material from the component. This a thermal-based machining process primarily used for hard to machine components with conventional methods. This process is used to make intricate cavities and contours. The fabricated part is the replica of the tool material with high surface finish and good dimensional accuracy. This study aims to evaluate the comprehensive effect of process parameters on electric discharge machining of maraging steel.

Multiple criteria Decision making (MCDM) techniques are used to select the best parameters by comparing several responses to achieve the desired goal. There are different MCDM techniques available for optimization of machining parameters. In the current investigation, multi-objective optimization by data envelopment analysis based ranking (DEAR) approach was used for machining Maraging C300 grade steel.

The Taguchi L9 runs were planned with process parameters such as current (Amp), Tool diameter (mm) and Dielectric pressure (MPa). The effect of process parameters on the responses, namely, material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR) were evaluated. High MRR is found at 15 A current, 14 mm tool diameter and dielectric pressure of 0.2 MPa. Optimum process parameters experiment showed reduced crack density.

An effort was made successfully to enhance the responses using the DEAR method and establish the decision making of selecting the optimal parameters by comparing the results obtained by machining maraging steel C300 grade.

This study aims to apply an electrochemical grinding (ECG) technology to improve the material removal rate (MRR) under the premise of certain surface roughness in machining U71Mn alloy.

The effects of machining parameters (electrolyte type, grinding wheel granularity, applied voltage, grinding wheel speed and machining time) on the MRR and surface roughness are investigated with experiments.

The experiment results show that an electroplated diamond grinding wheel of 46# and 15 Wt.% NaNO₃ + 10 Wt.% NaCl electrolyte is more suitable to be applied in U71Mn ECG. And the MRR and surface roughness are affected by machining parameters such as applied voltage, grinding wheel speed and machining time. In addition, the maximum MRR of 0.194 g/min is obtained with the 15 Wt.% NaCl electrolyte, 17 V applied voltage, 1,500 rpm grinding wheel speed and 60 s machining time. The minimum surface roughness of Ra 0.312 µm is obtained by the 15 Wt.% NaNO₃ + 10 Wt.% NaCl electrolyte, 13 V applied voltage, 2,000 rpm grinding wheel speed and 60 s machining time.

Under the electrolyte scouring effect, the products and the heat generated in the machining can be better discharged. ECG has the potential to improve MRR and reduce surface roughness in machining U71Mn.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2023-0341/

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.

This paper consolidates and presents the results of a work conducted to fabricate micro-channels on titanium grade-2 material by ultrasonic machining process (USM). In this research, the effects of important USM parameters, namely, kind of abrasives and its size, concentration of slurry, USM power rating and feed rate, have been probed on micro-channels quality for average surface roughness and process throughput in the form of material removal rate.

Multiple micro-channels on commercially pure titanium (i.e. Ti grade-2) have been fabricated in a single pass by employing micro-tool based USM process. Taguchi-based L18 (mixed level) OA has been selected for experimental design. Analysis of variance (ANOVA) study and regression modeling have also been done. Non-Dominated Sorting Genetic Algorithm (NSGA-II) has been used for process optimization to get optimum values of material removal rate (MRR) and surface roughness (SR).

The influence of important USM variables on SR and MRR have been investigated, and NSGA-II-based multi-response optimization has been done. The best surface roughness values obtained via NSGA-II solution for SiC and B₄C are 0.354 µm and 1.303 µm, respectively. Scanned electron microscopic investigation proves the fabrication of micro-channels with smooth surfaces, and minimum burrs and other defects. The material removed from the surface was due to ductile fractures.

Miniaturization is a modern trend these days to solve many precision, scientific and industrial problems. To manufacture precise micro-products, shapes and features, advanced and micro-machining processes can play a very prominent role. Micro-channels are typical micro-features required in micro-fluidic applications like micro heat exchangers and micro-pumps. Exhaustive review of existing research work indicated that precision micromachining of various materials can be effectively performed using USM, though not much work has been undertaken to explore the feasibility of multiple micro-channels in a single run using USM. The current work fulfills the gap, where multiple micro-channels on commercially pure titanium (i.e. Ti grade-2) have been fabricated in a single pass by employing micro-tool-based USM process.

The purpose of this paper is to adopt the multi-objective optimization technique for identifying a set of optimum abrasive water jet machining (AWJM) parameters to achieve maximum material removal rate (MRR) and minimum surface roughness.

Data of a few experiments as per the Taguchi’s orthogonal array are considered for achieving maximum MRR and minimum surface roughness (Ra) of the Inconel718. Analysis of variance is performed to understand the statistical significance of AWJM input process parameters.

Empirical relations are developed for MRR and Ra in terms of the AWJM process parameters and demonstrated their adequacy through comparison of test results.

The signal-to-noise ratio transformation should be applied to take in to account the scatter in the repetition of tests in each test run. But, many researchers have adopted this transformation on a single output response of each test run, which has no added advantage other than additional computational task. This paper explains the impact of insignificant process parameter in selection of optimal process parameters. This paper demands drawbacks and complexity in existing theories prior to use new algorithms.

Taguchi approach is quite simple and easy to handle optimization problems, which has no practical implications (if it handles properly). There is no necessity to hunt for new algorithms for obtaining solution for multi-objective optimization AWJM process.

This paper deals with a case study, which demonstrates the simplicity of the Taguchi approach in solving multi-objective optimization problems with a few number of experiments.

In the current exploration, the machining of a Nimonic 90 superalloy material was carried out in a die-sinking electric discharge machine. Experimentation was performed to investigate the impact of three input machining factors – current (I), pulse on time (T_on) and pulse off time (T_off) – on various response characteristics such as material removal rate (MRR), surface roughness (R_a) and electrode wear rate (EWR).

A Taguchi L9 design and ANOVA were used to assess machine response characteristics. The study also involved a grey relational analysis (GRA) multi-objective technique of optimization.

For single-objective performance, the most appropriate machining factors for achieving the best performance were attained as: MRR (I = 20 A, T_on = 200 µs and T_off = 45 µs), R_a (I = 14 A, T_on = 100 µs and T_off = 25 µs) and EWR (I = 17 A, T_on = 150 µs and T_off = 45 µs). The proposed grey relational approach provided the optimal settings (i.e. 14 A I, 100 µs T_on and 25 µs T_off) for the variables used to calculate the predicted and experimental results. Also, a confirmation test indicated that the final experimental grey relational grade value was enhanced when the experimentation was performed at optimal setting.

To the best of the authors’ knowledge, the present work is the first to examine the proposed machining variables (i.e. current, pulse on time and pulse off time) in relation to the optimization technique of GRA for a Nimonic 90 alloy using a die-sinking electric discharge machining method.

The purpose of this study is to realize the multi-objective optimization for MRR and surface roughness in micro-milling of Inconel 718.

Taguchi method has been applied to conduct experiments, and the cutting parameters are spindle speed, feed per tooth and depth of cut. The first-order models used to predict surface roughness and MRR for micro-milling of Inconel 718 have been developed by regression analysis. Genetic algorithm has been utilized to implement multi-objective optimization between surface roughness and MRR for micro-milling of Inconel 718.

This paper implemented the multi-objective optimization between surface roughness and MRR for micro-milling of Inconel 718. And some conclusions can be summarized. Depth of cut is the major cutting parameter influencing surface roughness. Feed per tooth is the major cutting parameter influencing MRR. A number of cutting parameters have been obtained along with the set of pareto optimal solu-tions of MRR and surface roughness in micro-milling of Inconel 718.

There are a lot of cutting parameters affecting surface roughness and MRR in micro-milling, such as tool diameter, depth of cut, feed per tooth, spindle speed and workpiece material, etc. However, to the best our knowledge, there are no published literatures about the multi-objective optimization of surface roughness and MRR in micro-milling of Inconel 718.