Wire Electrical Discharge Machining Process Research Articles

Machinability study of Al and Mg-based metal matrix composites using wire-EDM

In this investigation, a machinability study of the fabricated aluminium (Al) and magnesium (Mg) based MMCs is done using the Wire-EDM process. Initially, Al and Mg-based MMCs are fabricated with Silicon Carbide (SiC) reinforcements particles by the bottom pouring type stir casting process. After that, successful machining of both Al and Mg-based MMCs is carried out using Wire-EDM. The lowest value of machining time and kerf width for both Al/SiC and Mg/SiC MMCs are observed (0.1732 min, 0.3270 mm) and (0.1980 min, 0.2970 mm) respectively. The highest value of material removal rate 71.6651 mm3/min and 53.1313 mm3/min are achieved correspondingly for the Al and Mg-based MMCs. Overall evaluation criteria (OEC) values are calculated for all machining conditions to find out the mean effect of all process parameters simultaneously. The highest calculated OEC value of 75.00 and 84.45 are observed intended for Al/SiC and Mg/SiC respectively.

Investigation on wire electrical discharge machining of AISI 304 stainless steel

This paper presents an experimental investigation of the machining characteristics of the AISI304 stainless steel in the wire electrical discharge machining (WEDM) process. During experiments, parameters such as peak current, pulse on time, pulse off time, wire feed, and wire tension are varied to explore their effects on the response variables such as material removal rate and surface roughness. All the experimental runs have been conducted using a brass wire electrode. Taguchi L16 orthogonal array has been selected for designing the experimentation, and the principal component analysis (PCA) method is used to optimize the responses parameter. This study found that pulse on time is the most crucial factor influencing machining characteristics. It was also revealed that peak current and pulse off time impact surface roughness.

Enhancing cell adhesion and corrosion performance of titanium alloy by surface and sub-surface engineering using WEDM

Ti-6Al-4V (grade 5 titanium alloy) is a widely used material for biomedical implant and prostheses. The objective of this study is to investigate the effect of surface and sub-surface characteristics (i.e., surface roughness, microstructure, phase transformation, and recast layer) of Ti-6Al-4V alloy on the cell attachment and corrosion performance after machined by Wire Electric Discharge Machining (WEDM) process. The biocompatibility of titanium alloy has been studied based on the cell adhesion and cell proliferation response of mouse osteoblastic cell MC3T3-E1 to the machined surface of different levels of surface roughness and sub-surface microstructural and phase composition. One conventionally machined surface and one tissue culture treated plastic surface were used for comparison with those four WEDM machined surfaces. It was found that cell attachment increased with increasing surface smoothness, and WEDMed Ti-6Al-4V alloy sample exhibited higher cell attachment compared to even smoother conventionally machined samples. It was found that β phase at the sub-surface favored the cell adhesion on the machined surfaces for EDMed samples. The corrosion rate of machined Ti-6Al-4V alloy samples under simulated body fluid decreases with decreasing surface roughness. The findings suggest that WEDM has the capability of producing implant surface that can promote cell adhesion with improved corrosion performance under body fluid, thus, has the capability to manufacture implants with improved biocompatibility.

Kerf width analysis of wire electrical discharge machining of titanium alloy (Ti-6Al-4 V ELI) using response surface method

Wire Electrical Discharge Machine (WEDM) is a non-conventional machining process for machining electrically conductive materials regardless of their hardness. Machining of titanium alloy has higher machining forces, tool wear, worse surface finish, and low material removal rate by conventional machining. The effects of WEDM process parameters such as gap voltage (GV), pulse on time (Ton), pulse off time (Toff), and wire feed rate (WF) on kerf width (KW) are investigated in this work. Experimental work was carried out using response surface methodology through the Box Behnken method. The analysis of variance (ANOVA) was carried out to investigate the effect of each process parameter on kerf width. A desirability approach was employed to find better machining conditions for KW. Based on ANOVA results, GV, Ton, and Toff have a significant effect, whereas WF has less effect on KW. The minimum kerf width was achieved 0.356 mm at GV (40 V), Ton (3 µs), Toff (10 µs) and WF (1 m/min). The confirmations test result shows that predicted values were well fitted with the 95% confident level of experimental values.

Experimental investigations on wire cut electric discharge machining on Monel 400 alloys

In this present work, the machinability effect of Monel alloy is studied by varying the parameters of Wire Electrical Discharge Machine (WEDM). Pulse on time (T on), Pulse off time (T off), Spark voltage (SV), Servo feed (SF) and Cutting Speed (CS) were the input parameters considered for the study. Material Removal rate (MRR) and Surface roughness were the responses that were measured and analysed. The experiments were conducted by using Taguchi’s L9 orthogonal array. Each experiment was conducted thrice under different conditions of input parameters. The influences of each independent parameter on the output measures were analyzed using Grey Relational Analysis (GRA) with the intension of improving the machinability. From the experiments, the best combination of input parameters was found that can increase the machinability. The experimental results confirm that the machining performance of WEDM process can be improved effectively through this approach.

Prediction of Geometrical Accuracy in Wire EDM by Analyzing Process Data

In order to digitalize the wire EDM process, data-driven models for the evaluation of the process performance have to be developed. The challenge is the huge amount of data and the stochastically process behavior. Such a model could be used to predict the geometrical accuracy of machined workpieces as well as for development of new machining technologies. In this paper, the produced geometrical accuracy is predicted by continuously recorded process data. For this purpose, electrical parameters are measured and processed by using a FPGA (Field Programmable Gate Array) system to detect spatially resolved single discharges during the process characterized as normal or abnormal discharges. Afterwards, the recorded data are systematically reduced by averaging the process data over defined time intervals. For this purpose, unsupervised machine learning methods are used to ensure that no relevant information is lost. Finally, the processed data is analyzed and statistical parameters are correlated with the machined geometrical accuracy.

Experimental studies and optimization of WEDM process in machining of Nitronic 60 using zinc coated copper wire

Nitronic 60 is an alloy steel that can be machined using an unconventional technique. Machining of Nitronic 60 is not an easy task as the surface roughness of the material should be very low and so is the Material Removal Rate. To Enhance the surface roughness and Material Removal Rate Wire EDM process is chosen as it reduces the time and complicity. For the present study Nitronic 60 of 20 mm diameter bar and zinc coated copper wire of 0.25 mm diameter was used for machining on Wire EDM. The experiment layout is based on Taguchi's L-9 orthogonal array, and the experiments will be carried out by considering the Machining parameters like current, voltage, Pulse ON and Pulse OFF, and Material Removal Rate (MRR) and Surface roughness (SR) are considered for evaluation and optimised. It was observed from the study that Optimum condition for Material Removal Rate is current at level 3 (200 A), voltage at level 3 (20 v), pulse ON at level 3 (120 µs), and pulse OFF at level 1 (50 µs) and for Surface roughness current at level 3 (200 A), voltage at level 1 (10 v), pulse ON at level 1 (100 µs), and pulse OFF at level 2 (55 µs). additionally, from ANOVA analysis it was observed that for roughness interaction of Current*Pulse ON time with 25.53% for MRR current with 29.66% is most contribution factor.

A Critical Review on Optimization of WEDM Process Using Taguchi Array

Abstract: Wire electrical release machining (WEDM) innovation has developed at special case rate since it was first applied over long term prior.WEDM is a widely recognized unconventional material cutting process used to manufacture components with complex shapes and profiles of hard materials. In this thermal erosion process, there is no physical contact between the wire tool and work materials. Wire Electrical Discharge Machining (WEDM) is getting more tasks in fields like dies, punches, aero and many more. It is the very difficult task to get optimum process parameters for higher cutting efficiency. In WEDM process rough machining gives lesser accuracy and finish machining gives fine surface finish, but it reduces the machining speed. This review involves process, principle, literature and applications of WEDM using Taguchi array. Keywords: WEDM; Materials; Machine; Cutting efficiency; Optimization process.

EFFECT OF WIRE ELECTRICAL DISCHARGE MACHINING ON THE SURFACE OF EBM-ADDITIVE MANUFACTURED NITI ALLOYS

Nickel-titanium (NiTi) shape memory alloys are used in varied engineering products, such as biomedical device and mechatronic actuator applications. The conventional machining technology are utilized in the limited fields due to their effects on the hardness and brittleness of the machined alloys. However, the wire electrical discharge machining (WEDM) technology is one of the most preferred post-processing tool to obtain a surface with high quality. The electrical current and voltage values with pulse on and pulse off time are the crucial parameters for WEDM. These parameters should be optimized before wire electrical discharge machining process. Electron beam melting (EBM)-based additive manufacturing of the nickel-titanium powders provides obtaining bulk NiTi shape memory alloys using high energy electron beams. In this study, the application of WEDM which is used as a post-processing tool is evaluated for the EBM-based additive manufactured NiTi samples. Additionally, the scanning electron microscopy results of the wire electrical discharge machined NiTi samples are carefully investigated.

Novel EDAS-Taguchi and EDAS-Taguchi-Pareto Methods for Wire EDM Process Parametric Selection of Ni55.8Ti (Nitinol) Shape Memory Alloy

The EDAS (evaluation based on distance from average solution) method is a broadly utilized tool for multi-criteria analysis with the ability to handle several conflicting criteria. The Taguchi method is an optimization tool with economic capability in experimentation. This article presents EDAS Taguchi (EDAS-T) method based on EDAS and the Taguchi method. It also presents EDAS Taguchi-Pareto (EDAS-TP) method framed from EDAS and Taguchi-Pareto methods. Furthermore, data from the literature to test the proposed methods are presented, which the results are compared. This research shows that the EDAS method produces the optimum combination of parameters at a run with a current of 4A, pulse on time of 50 µs, pulse off time of 14ms, and powder concentration of 1 g/L. Also, the EDAS-Taguchi method reveals a current of 4A, pulse on time of 60 µs, pulse off time of 14 µs, and powder concentration of 1 g/L. However, the principal result is that using the EDAS Taguchi-Pareto method, the optimal current is 3A, pulse on time is 60 µs, and powder concentration is 0.75g/L. The EDAS Taguchi-Pareto method eliminated the pulse off time and pulse on time, claiming that it is not significant to the system's optimum performance. The principal novelty of this article is that it introduces a mechanism of concurrently optimizing and selecting the wire EDM process parameters using the EDAS-Taguchi-Pareto method. The optimization is parallelly conducted as selection occurs, providing an initial notification to ascertain timely detection and control of local optimality of parameters to global optimization before final selection. This is unlike most evaluations, where optimization is done differently from the selection. This study is the first to develop and use EDAS methods for the WEDM process of Ni55.8Ti shape memory alloy.

A study of mechanical properties and WEDM machinability of spark plasma sintered ZrB2–B4C ceramic composites

Four different compositions of ZrB2-B4C composites (i.e., 5, 15, 20, 25 Wt. % of B4C) were fabricated by Spark Plasma Sintering Technique (SPS) at 2000 °C temperature. The composites were characterized by the evolution of physical and mechanical properties; X-Ray Diffraction (XRD) analysis was also done for phase analysis of the composites. The relative density values were obtained in the range of 96.14–97.78 % of all the composites. The addition of B4C in ZrB2 matrix led to an enhancement in hardness (15.38 GPa at 5 wt.% B4C to 20.49 GPa at 25 wt.% B4C measured at 1.0 kgf load) and fracture toughness (from 2.93 MPa-m0.5 at 5 wt.% B4C to 4.13 MPa-m0.5 at 25 wt.% B4C measured at 1.0 kgf load). The composite samples were processed by wire electrical discharge machining (WEDM) process with three different parameters set for the study of machining speed, surface roughness. The composite with 25 wt.% of B4C shows highest machining speed of 10.56 mm2/min. The average surface roughness (Ra) of the WEDM processed composite surfaces lies in the range of 1.26–5.64 μm.

Rotary Engine Rotor Side Seals Using New Machining Processes

Abstract This study has developed a new machining process for the side seal components of gray cast iron alloy of rotor engine, which is different from the traditional wire electrical discharge machining (WEDM) process. The new manufacturing process (milling + grinding process) will save 78% of the cost and 83% of the time for making each side seal component, and the accuracy of the average surface roughness of the component will be 2.1 times that of the traditional manufacturing method. If the components are polished with a self-made polishing rod, the accuracy will be increased by almost 20 times compared with the new manufacturing process.

Effect of process parameters for wire EDM of AISI H13 tool steel

Traditional machining processes struggle to machine materials with extremely high hardness. As a result, novel machining techniques such as ECM, USM and EDM have been developed for machining these materials. The Wire EDM process parameters of AISI H13 tool steel are optimized in this research using an effective approach. Gap Voltage, Pulse On Time, Pulse Off Time and wire feed are the input machining parameters used in the present work to achieve the highest MRR and lowest SR. The response table and response graphs were used to define the ideal levels of machining parameters. The significance of the machining parameters was decided by means of ANOVA. The greatest statistical effect on MRR is Gap Voltage (90.75%), other factors are not significant. The greatest statistical effect on SR is Gap Voltage (67.05%), followed by pulse off time (19.62). The confirmation experiments indicated that it is possible to increase the material removal rate and decrease the surface roughness by the proposed statistical technique.

Data-driven probabilistic performance of Wire EDM: A machine learning based approach

The wire electric discharge machining (WEDM) is a potential alternative over the conventional machining methods, in terms of accuracy and ease in producing intricate shapes. However, the WEDM process parameters are exposed to unavoidable and unknown sources of uncertainties, following their inevitable influence over the process performance features. Thus, in the present work, we quantified the role of parametric uncertainty on the performance of the WEDM process. To this end, we used the practically relevant noisy experimental dataset to construct the four different machine learning (ML) models (linear regression, regression trees, support vector machines, and Gaussian process regression) and compared their goodness of fit based on the corresponding R2 and RMSE values. We further validated the prediction capability of the tested models by performing the error analysis. The model with the highest computational efficiency among the tested models is then used to perform data-driven uncertainty quantification and sensitivity analysis. The findings of the present article suggest that the pulse on time ( Ton) and peak current (IP) are the most sensitive parameters that influence the performance measures of the WEDM process. In this way, the current study achieves two goals: first, it proposes a predictive framework for determining the performance features of WEDM for unknown design points, and second, it reports data-driven uncertainty analysis in the light of parametric perturbations. The observations reported in the present article provide comprehensive computational insights into the performance characteristics of the WEDM process.

Integration of Fuzzy AHP and Fuzzy TOPSIS Methods for Wire Electric Discharge Machining of Titanium (Ti6Al4V) Alloy Using RSM.

Titanium and its alloys exhibit numerous uses in aerospace, automobile, biomedical and marine industries because of their enhanced mechanical properties. However, the machinability of titanium alloys can be cumbersome due to their lower density, high hardness, low thermal conductivity, and low elastic modulus. The wire electrical discharge machining (WEDM) process is an effective choice for machining titanium and its alloys due to its unique machining characteristics. The present work proposes multi-objective optimization of WEDM on Ti6Al4V alloy using a fuzzy integrated multi-criteria decision-making (MCDM) approach. The use of MCDM has become an active area of research due to its proven ability to solve complex problems. The novelty of the present work is to use integrated fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal situation (TOPSIS) to optimize the WEDM process. The experiments were systematically conducted adapting the face-centered central composite design approach of response surface methodology. Three independent factors—pulse-on time (Ton), pulse-off time (Toff), and current—were chosen, each having three levels to monitor the process response in terms of cutting speed (VC), material removal rate (MRR), and surface roughness (SR). To assess the relevance and significance of the models, an analysis of variance was carried out. The optimal process parameters after integrating fuzzy AHP coupled with fuzzy TOPSIS approach found were Ton = 40 µs, Toff = 15 µs, and current = 2A.

Experimental investigation of angular error during taper cutting of titanium (ASTM Grade 2) using WEDM process

Today, mechanical industries are looking for processes that can produce high-precision products with fewer tools to get maximum accuracy. To achieve this, WEDM is so far more widely used, which had shown remarkable technological growth in the last decade. After the success of straight cutting, the wire EDM tapering process have taken it to the next level of taper generating surfaces by being able to machine complicated parts with inclined profiles. After the rigorous research in this field, it is found that wire breakage & wire deformation plays a very significant role while working with taper cutting in contrast to straight cutting which results in creating undesirable effects on the required taper angle. One of the ways to deal with such problems is to control the process parameters. After performing an in-depth literature review, it is found that for pure titanium the consequences of different process parameters on a variety of key performance measures are not sufficiently analyzed in wire EDM taper cutting. This research work makes every possible effort to investigate experimentally the machining performance by conducting the taper cutting of pure titanium while using the WEDM technology. The role of process parameters like taper angle, wire tension, wire feed on response parameters like angular error was studied. Experiments have been carried out on pure titanium by implementing Taguchi’s L9 orthogonal array which involves three variables with three levels. Analysis of variance (ANOVA) has been performed to analyze the effect of process parameters and the contribution of each parameter affecting the responses have been calculated. It can be concluded that taper angle is the major primary crucial control parameter that influences the angular error followed by wire tension. For minimizing the angular error, recommended parametric combination is taper angle at 4 degrees, wire feed at 7 m/min (117 mm/s), and wire tension at 7 units equals 1020 g (10 N) for taper cutting of Titanium (ASTM grade 2) using wire electrical discharge machining process.

Dynamic Control of Discharge Energy During WEDM for the Purpose of Eliminating Vibrations of the Wire Tool Electrode

Abstract Production in all industry fields is currently affected by new scientific and technical knowledge and the requirements for its rapid deployment. In many cases, the most modern and highly sophisticated technical systems are applied. Simultaneously, fully automated production systems are rather successfully used and progressive production technologies are implemented. In most cases, there is an integral part of a management system that operates the challenging technological processes. These processes would not be executable without the system’s precise control, which provides a suitable precondition for ensuring the high quality of manufactured products. However, the customer’s demanding requirements are not always met. These involve increased requests for the quality of the final product due to the reduction of the tolerance band and application of high-strength materials. This paper aims to describe one of the solutions by which it is possible to achieve a higher quality of the machined surface after wire electrical discharge machining (WEDM). The solution proposes that through dynamic management, the WEDM process eliminates the vibrations of the wire tool electrode and thereby achieves a substantial increase in the quality of the eroded area in terms of its geometric accuracy. With the support of an extensive database of information with precise exchange of information, the proposed system will allow to control the electro discharge process with regard to the optimal way of operation of the electro discharge machine on the basis of individually selected conditions.

Machine-vision-based electrode wear analysis for closed loop wire EDM process control

The purpose of this study was to develop a closed-loop machine vision system for wire electrical discharge machining (EDM) process control. Excessive wire wear leading to wire breakage is the primary cause of wire EDM process failures. Such process interruptions are undesirable because they affect cost efficiency, surface quality, and process sustainability. The developed system monitors wire wear using an image-processing algorithm and suggests parametric changes according to the severity of the wire wear. Microscopic images of the wire electrode coming out from the machining zone are fed to the system as raw images. In the proposed method, the images are pre-processed and enhanced to obtain a binary image that is used to compute the wire wear ratio (WWR). The input parameters that are adjusted to recover from the unstable conditions that cause excessive wire wear are pulse off time, servo voltage, and wire feed rate. The algorithm successfully predicted wire breakage events. In addition, the alternative parametric settings proposed by the control algorithm were successful in reducing the wire wear to safe limits, thereby preventing wire breakage interruptions.

Performance characterization of powder mixed wire electrical discharge machining technique for processing of Ti6Al4V alloy

Precision machining characteristics with high-dimensional accuracy make the material more adaptable towards the applications. The present study employs the powder mixed wire electrical discharge machining process to machine Ti6Al4V alloy material. In spite of limited drawbacks and enhanced output in the powder mixed wire electrical discharge machining process, the present problem has been formulated for improving the machining efficiency of Ti6Al4V. The impact of suspended powder characteristics on responses, that is, material removal rate and surface roughness, is examined throughout the process. The current investigation also focuses on the interaction effect of machining constraints along with Al2O3 abrasive mixed dielectric to achieve economical machining output for the Ti6Al4V material. An effort has been presented to obtain optimal solutions using the different methodologies, namely response surface methodology, grey relation analysis, and particle swarm optimization. The study reveals that discharge energy is deeply influenced by the peak current and pulse off time followed by powder concentration in the powder mixed wire electrical discharge machining process. The maximum material removal rate of 6.628 mm3/min and average surface finish of 1.386 μm are the outcome of the present study for a set of optimal machining settings, that is, pulse off time ( Toff) of 7.247 μs, pulse on time ( Ton) of 30 μs, peak current ( Ip) of 2 A, and powder concentration of 4 g/L. Finally, the proposed model has been verified that the hybrid particle swarm optimization technique has the highest adequate capability to achieve maximum output. Thus, the approach offered an enhancement on performance measures of Ti6Al4V alloy in the powder mixed wire electrical discharge machining process.

Effect of ultrasonic low - frequency vibration and its direction on machinability in WEDM process

ABSTRACT It is important to analyze and improve quality measures in such process. In this investigation, an analysis was made on finding the influence of vibrational direction with respect to cutting direction on quality measures while machining SKD 61 steel using wire EDM process. The material erosion rate, kerf width and surface roughness were considered as the response parameters to evaluate the machinability. Taguchi-DEAR-based optimization approach was utilized to further improve the quality measures in EDM process. The parallel direction vibration could produce higher material exclusion with lower surface roughness and kerf width in low-frequency-assisted wire electrical discharge machining process owing to efficient deionization and larger contact area. The optimal process factors in V-WEDM process were computed as F (500 Hz),GV (80 V), Ton (1 µs) and Toff (20 µs) among the chosen parameters. It was also inferred that vibration frequency could enhance the quality measures due to its importance on flushing process.