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).     

Application of Taguchi,ANFIS and grey relational analysis for studying,modeling and optimization of wire EDM process while using gaseous media

In the dry wire electrical discharge machining (WEDM) process, the liquid dielectric is replaced with gaseous medium to enhance the machining environment safety. Also, this modification improves the surface quality of machined specimen but decreases the material removal rate of the process. In the present work, experimental study of dry WEDM process has been performed while machining of Al/SiC metal matrix composite. At first, a series of exploratory experiments has been conducted to identify appropriate gas and wire material based on their cutting velocity. After selection of the best gas and best wire, they were used for later stage of experiments. At the next stage, experiment were designed and conducted based on L₂₇ Taguchi's orthogonal array to study the effect of pulse on time, pulse off time, gap voltage, discharge current, wire tension and wire feed on cutting velocity (CV) and surface roughness (SR). Analysis of variances (ANOVA) has been performed to identify significant factors. In order to correlate relationship between process inputs and responses, adaptive neuro-fuzzy inference system has been utilized. At the end, a grey relational analysis has been used to maximize CV and minimize SR simultaneously. Results indicated that oxygen gas and brass wire guarantee superior cutting velocity. Also according to ANOVA, pulse on time and current were found to have significant effect on CV and SR.     

Optimization of WEDM process of pure titanium with multiple performance characteristics using Taguchi’s DOE approach and utility concept

This paper describes the development of multi response optimization technique using utility method to predict and select the optimal setting of machining parameters in wire electro-discharge machining (WEDM) process. The experimental studies in WEDM process were conducted under varying experimental conditions of process parameters, such as pulse on time(T_on), pulse off time(T_off), peak current (IP), wire feed (WF), wire tension (WT) and servo voltage (SV) using pure titanium as work material. Experiments were planned using Taguchi’s L27 orthogonal array. Multi response optimization was performed for both cutting speed (CS) and surface roughness (SR) using utility concept to find out the optimal process parameter setting. The level of significance of the machining parameters for their effect on the CS and SR was determined by using analysis of variance (ANOVA). Finally, confirmation experiment was performed to validate the effectiveness of the proposed optimal condition.     

EXPERIMENTAL INVESTIGATIONS INTO THE INFLUENCE OF MAJOR OPERATING PARAMETERS DURING MICRO-ELECTRO DISCHARGE DRILLING OF CEMENTED CARBIDE

Present study investigates the influence of major operating parameters on the performance of micro-EDM drilling of cemented carbide (WC-10wt%Co) and identifies the ideal values for improved performance. The operating parameters studied were electrode polarity, gap voltage, resistance, peak current, pulse duration, pulse interval, duty ratio, electrode rotational speed and EDM speed. The performance of micro-EDM drilling process was evaluated by machining time, material removal rate (MRR), relative electrode wear ratio (RWR), spark gap, surface finish and dimensional accuracy of micro-holes. It has been found that there are two major conflicting issues in the micro-EDM of carbide. If the primary objective is to obtain better surface finish, it can be obtained by the sacrifice of high machining time, low MRR and high RWR. However, for faster micro-EDM, the surface roughness is higher and electrode wear is again much higher. It is concluded that negative electrode polarity, gap voltage of 120 V, resistance of 33 Ω, peak current of 8 A, pulse duration of 21 μs, pulse interval of 30 μs, duty cycle of 0.47, electrode rotational speed of 700 rpm and EDM speed of 10 μm/s can be considered as ideal parameters to provide improved performances during the micro-EDM of WC-Co.     

Optimization of machining parameters for EDM operations based on central composite design and desirability approach

A novel aluminium metal matrix composite reinforced with SiC particles were prepared by liquid metallurgy route. Recent developments in composites are not only focused on the improvement of mechanical properties, but also on machinability for difficult-to-machine shapes. Electrical discharge machining (EDM) was employed to machine MMC with copper electrode. using EDM. Experiments were conducted using pulse current, gap voltage, pulse on time and pulse off time as typical process parameters. The experiment plan adopts face centered central composite design of response surface methodology. Analysis of variance was applied to investigate the influence of process parameters and their interactions viz., pulse current, gap voltage, pulse on time and pulse off time on material removal rate (MRR), electrode wear ratio (EWR) and surface roughness (SR). The objective was to identify the significant process parameters that affect the output characteristics. Further a mathematical model has been formulated by applying response surface method in order to estimate the machining characteristics such as MRR, EWR and SR.     

Optimizing machining parameters of silicon carbide ceramics with ED milling and mechanical grinding combined process

A novel combined process of machining silicon carbide (SiC) ceramics with electrical discharge milling and mechanical grinding is presented. The process is able to effectively machine a large surface area on SiC ceramics with a good surface quality. The effect of tool polarity on the process performance has been investigated. The effects of peak current, peak voltage, pulse on-time and pulse off-time on the material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR) have been investigated with Taguchi experimental design. The mathematical models for the MRR, EWR, and SR have been established with the stepwise regression method. The experiment results show that the MRR, EWR, and SR can reach 46.2543 mm³/min, 20.7176%, and 0.0340 µm, respectively, with each optimal combination level of machining parameters.     

气体放电加工基础工艺试验研究

采用单因素法进行了基本的工艺参数(电参数、伺服参考电压等)对气体介质放电加工性能影响的试验研究。试验结果表明:气体介质的放电加工适于采用正极性加工。在试验加工的范围内,工件的蚀除速度和表面粗糙度值随脉冲宽度和峰值电流的增加而增加,随脉冲间隔的增加而减小。极间并联合适的电容能够使加工速度和加工表面粗糙度有所改善,并对此现象进行了分析。对于某一确定的加工参数,存在一个较佳的伺服参考电压值,使加工性能较为稳定。工具电极具有较高的旋转速度能够使气体放电加工性能得到提高。使用氧气介质能够实现快速电火花加工,并根据不同气体的物理性能对不同气体介质的加工性能进行了分析。工件表面显微硬度测试结果表明:空气中放电加工的工件的表面硬度比基体硬度高,比煤油中加工的工件表面硬度低。     

Study of the EDM performance to produce a stable process and surface modification

In this work, the effect of pulse current and pulse duration in die-sinking electrical discharge machining (EDM) on the machining characteristics of Ti-6Al-4V alloy is studied. The EDM characteristics, including the electrode wear ratio (EWR), the material removal rate (MRR), and the surface roughness (SR), are used to measure the effect of machining. An increase in the intensity of the pulse current from 2.5 to 5 A produces a slow increase in EWR, MRR, and SR. An increase in the intensity of the pulse current from 5 to 7 A produces a rapid increase in EWR, MRR, and SR. Control charts are basic and powerful tools for controlling statistical processes and are widely used to monitor manufacturing processes and ensure good EDM quality. EWR, MRR, and SR are normal distributions, and the regression curves for the data are straight lines. All of the data points vary randomly around the centerline, which follows the Shewhart criteria and shows that the EDM process and product performance are under control and stable over time. After EDM, the surface exhibits an irregular fused structure, with pinholes, micro voids, globule debris, and many damaged surfaces. Oxygen plasma etching and surface modification after EDM reduce these surface defects, so finer and flatter surfaces can be achieved. Moreover, fatigue life can be enhanced.     

Optimization of wire electrical discharge machining (WEDM) process parameters using Taguchi method

Wire electrical discharge machining (WEDM) is extensively used in machining of conductive materials when precision is of prime importance. Rough cutting operation in WEDM is treated as a challenging one because improvement of more than one machining performance measures viz. metal removal rate (MRR), surface finish (SF) and cutting width (kerf) are sought to obtain a precision work. Using Taguchi’s parameter design, significant machining parameters affecting the performance measures are identified as discharge current, pulse duration, pulse frequency, wire speed, wire tension, and dielectric flow. It has been observed that a combination of factors for optimization of each performance measure is different. In this study, the relationship between control factors and responses like MRR, SF and kerf are established by means of nonlinear regression analysis, resulting in a valid mathematical model. Finally, genetic algorithm, a popular evolutionary approach, is employed to optimize the wire electrical discharge machining process with multiple objectives. The study demonstrates that the WEDM process parameters can be adjusted to achieve better metal removal rate, surface finish and cutting width simultaneously.     

Parametric optimization for surface roughness, kerf and MRR in wire electrical discharge machining (WEDM) using Taguchi design of experiment

This paper reports the effect and optimization of eight control factors on material removal rate (MRR), surface roughness and kerf in wire electrical discharge machining (WEDM) process for tool steel D2. The experimentation is performed under different cutting conditions of wire feed velocity, dielectric pressure, pulse on-time, pulse off-time, open voltage, wire tension and servo voltage by varying the material thickness. Taguchi’s L18 orthogonal array is employed for experimental design. Analysis of variance (ANOVA) and signal-tonoise (S/N) ratio are used as statistical analyses to identify the significant control factors and to achieve optimum levels respectively. Additionally, linear regression and additive models are developed for surface roughness, kerf and material removal rate (MRR). Results of the confirmatory experiments are found to be in good agreement with those predicted. It has been found that pulse on-time is the most significant factor affecting the surface roughness, kerf and material removal rate.     

Effect of electrode material in wire electro discharge machining characteristics of Ti50Ni50−xCux shape memory alloy

TiNiCu alloy belongs to new class of shape memory alloy (SMA), which exhibits superior properties like shape memory effect, super elasticity and reversible martensitic transformation phase and thus find broad applications in actuators, micro tools and stents in biomedical components. Even though, SMA demonstrates outstanding property profile, traditional machining of SMAs is fairly complex and hence non-traditional machining like wire electric discharge machining (WEDM) has been performed. Hence, there is a need to investigate the WEDM performance characteristics of shape memory alloys due to excellent property profile and potential applications. In the present investigation, various machining characteristics like material removal rate (MRR), surface roughness, surface topography and metallographic changes have been studied and the influence of wire material on TiNiCu alloy machining characteristics has also been evaluated through ANOVA. Ti₅₀Ni_50−xCu_{x=10, 20} was prepared by vacuum arc melting process. The proposed alloy as-cast material exhibits austenite property (B2 phase) and having higher hardness when compared to TiNi alloy. The investigation on WEDM of Ti₅₀Ni_50−xCu_x alloy reveals that the machining parameters such as servo voltage, pulse on time and pulse off time are the most significant parameters affecting MRR as well as surface roughness using both brass and zinc coated brass wires. However, machining with zinc coated brass wire yields reduced surface roughness and better MRR and also produces less surface defects on the machined surface of Ti₅₀Ni_50−xCu_x alloys.     

Multi-response optimization of process parameters based on response surface methodology for pure titanium using WEDM process

This paper presents an investigation on WEDM of pure titanium (grade-2). An attempt has been made to model the four response variables, i.e., machining rate, surface roughness, dimensional deviation and wire wear ratio in WEDM process using response surface methodology. The experimental plan is based on Box–Behnken design. The six parameters, i.e., pulse on time, pulse off time, peak current, spark gap voltage, wire feed and wire tension have been varied to investigate their effect on output responses. These responses have been optimized using multiresponse optimization through desirability. The ANOVA has been applied to identify the significance of developed model. The test results confirm the validity and adequacy of the developed RSM model. Finally, the optimum parametric setting has been designed for the optimization of process.     

Application of response surface method on machining of Al–SiC nano-composites

The newly fabricated metal matrix nano-composite (MMNC) of Al 7075 reinforced with 1.5 wt% SiC nano-particles was prepared by a novel ultrasonic cavitation method. The high resolution scanning electron micrograph (SEM) and field emission scanning electron micrograph (FESEM) shows uniform distribution and good dispersion of the SiC nanoparticles within the aluminum metal matrix. Electrical discharge machining (EDM) was employed to machine MMNC with copper electrode by adopting face centered central composite design of response surface methodology. Analysis of variance was applied to investigate the influence of process parameters and their interactions. Further a mathematical model has been formulated in order to estimate the machining characteristics. It has been observed that pulse current was found to be the most important factor affecting all the three output parameters such as material removal rate (MRR), electrode wear rate (EWR) and surface roughness (SR). The optimum parameter of combination setting has been identified for the MMNC are voltage 50.00 V, pulse current 8.00 A, Pulse on time 8.00 μs and pulse off time 9.00 μs. Finally the parameters were optimized for maximizing MRR, minimizing EWR and SR using desirability function approach.     

PARAMETRIC INFLUENCE AND OPTIMIZATION OF WIRE EDM OF HOT DIE STEEL

Wire-cut Electro Discharge Machining (WEDM) is a special form of conventional EDM process in which the electrode is a continuously moving conductive wire. The present study aims at determining parametric influence and optimum process parameters of Wire-EDM using Taguchi's technique and a Genetic algorithm. The variation of the performance parameters with machining parameters was mathematically modeled by Regression analysis method. The objective functions are defined as Dimensional Error (DE), Surface Roughness (SR) and Volumetric Material Removal Rate (VMRR). Experiments were designed as per Taguchi's L₁₆ Orthogonal Array (OA) wherein Pulse-on duration, Current, Pulse-off duration, Bed-speed and Flushing rate have been considered as the important input parameters. The matrix experiments were conducted for the material Hot Die Steel (HDS) having the thickness of 40 mm. The Heat Affected Zone (HAZ) characteristics of the eroded materials were assessed by Scanning Electron Microscope (SEM) and the microhardness of the material was tested using Vickers microhardness tester. The results of the study reveal that among the machining parameters, it is preferable to go for smaller pulse-off duration for achieving overall good performance. Regarding pulse-on duration, higher values are recommended for error constrained machining with higher MRR and constrained/limited values for attaining good surface texture. Smaller current is suggested for better surface finish/texture control, medium range for error control and high value for MRR. Finally, the validation exercise was performed with the optimum levels of the process parameters. The results confirm the efficiency of the approach employed for optimization of process parameters in this study.     

Fabricating micromilling tool using wire electrodischarge grinding and focused ion beam sputtering

In the present research, wire electrical discharge machining (WEDM) of γ titanium aluminide is studied. Selection of optimum machining parameter combinations for obtaining higher cutting efficiency and accuracy is a challenging task in WEDM due to the presence of a large number of process variables and complicated stochastic process mechanisms. In general, no perfect combination exists that can simultaneously result in both the best cutting speed and the best surface finish quality. This paper presents an attempt to develop an appropriate machining strategy for a maximum process criteria yield. A feed-forward back-propagation neural network is developed to model the machining process. The three most important parameters – cutting speed, surface roughness and wire offset – have been considered as measures of the process performance. The model is capable of predicting the response parameters as a function of six different control parameters, i.e. pulse on time, pulse off time, peak current, wire tension, dielectric flow rate and servo reference voltage. Experimental results demonstrate that the machining model is suitable and the optimisation strategy satisfies practical requirements.     

Investigation of wire electrical discharge machining characteristics of Al6063/SiCp composites

In this investigation, the effect of wire electrical discharge machining (WEDM) parameters such as pulse-on time (T _ON), pulse-off time (T _OFF), gap voltage (V) and wire feed (F) on material removal rate (MRR) and surface roughness (R _a) in metal matrix composites (MMCs) consisting of aluminium alloy (Al6063) and silicon carbide (SiC_p) is discussed. The Al6063 is reinforced with SiC_p in the form of particles with 5%, 10% and 15% volume fractions. The experiments are carried out as per design of experiments approach using L₉ orthogonal array. The results were analysed using analysis of variance and response graphs. The results are also compared with the results obtained for unreinforced Al6063. From this study, it is found that different combinations of WEDM process parameters are required to achieve higher MRR and lower R _a for Al6063 and composites. Generally, it is found that the increase in volume percentage of SiC resulted in decreased MRR and increased R _a. Regression equations are developed based on the experimental data for the prediction of output parameters for Al6063 and composites. The results from this study will be useful for manufacturing engineers to select appropriate WEDM process parameters to machine MMCs of Al6063 reinforced with SiC_p at various proportions.     

Optimization of cutting conditions of YG15 on rough and finish cutting in WEDM based on statistical analyses

In this paper, the effects and the optimization of cutting parameters on surface roughness (Ra) and material removal rate (MRR) in the wire electrical discharge machining (WEDM) of high hardness tool steel YG15 are analyzed. In the WEDM process, the key process parameters, such as pulse-on time, pulse-off time, power, cutting feed rate, wire tension, wire speed, and water pressure, are optimized. Experimental data were initially collected based on the Taguchi method of experimental design, which are $L_{18}\left (2^1\times 3^5\right )$ and $L_{18}\left (2^1\times 3^4\right )$ Taguchi standard orthogonal array on rough and finish cutting experiments, respectively. The level of importance of the cutting parameters on the Ra and MRR was determined on both finish and rough cutting by using statistical analyses; average gap voltage is discussed in order to balance cutting efficiency and stability on both finish and rough cutting. In addition, comparative analysis of finish and rough cutting is drawn to analyze the difference between rough cutting and finish cutting. Then, regression models and signal-to-noise ratio are used to obtain the optimum cutting parameter combination. Finally, the results present the optimized MRR and Ra of the rough and finish process, respectively, and confirm the efficiency and abilities of the model.     

Electrical discharge precision machining parameters optimization investigation on S-03 special stainless steel

S-03 is a novel special stainless steel, which is widely used in precision aerospace parts and electrical discharge machining technology has the merit of high-accuracy machining. This paper aims to combine gray relational analysis and orthogonal experimental to optimize electrical discharge high-accuracy machining parameters. The four process parameters of gap voltage, peak discharge current, pulse width, and pulse interval are required to optimize in the fewest experiment times. The material removal rate and surface roughness are the objective parameters. The experiment were carried out based on Taguchi L9 orthogonal array, then we carried out the gray relational analysis to optimize the multi-objective machining parameter, finally, we verified the results through a confirmation experiment. The sequence of machining parameters from primary to secondary are as follows: discharge current 7A, pulse interval 100 μs, pulse width 50 μs, and gap voltage 70 V. Using the above machining parameters, we can obtain good surface roughness Ra1.7 μm, and material removal rate 13.3 mm³/min. The machined work piece almost has no surface modification layer. The results show that combining orthogonal experiment and gray relational analysis can further optimize machining parameters, the material removal rate increased by 23.8 %, and the surface roughness almost has no change.     

Surface crack density and recast layer thickness analysis in WEDM process through response surface methodology

In this work, quantitative assessment of surface damage in terms of parameters like surface crack density and recast layer thickness in wire electrical discharge machining (WEDM) process has been undertaken. The effect of processing conditions on crack formation is studied using scanning electron microscope. Surface crack density and recast layer thickness analysis in terms of machining parameters such as pulse on time, pulse off time, peak current, spark gap voltage significantly deteriorate the microstructure of machined samples, which produces the deeper, wider overlapping craters, pock marks, globules of debris and micro cracks. The microstructure analysis of WEDM surface was based upon the theory of electrical discharge phase and metallurgical physics. It is found that the pulse on time, pulse off time and peak current are the most dominating parameters for both surface crack density and recast layer thickness.     

Experimental investigation on the electrochemical machining of 00Cr12Ni9Mo4Cu2 material and multi-objective parameters optimization

Special stainless steel 00Cr12Ni9Mo4Cu2 has multiple composition and inhomogeneous tissues; short circuiting will frequently occur when using conventional electrolyte processing. This article analyzes the reason why the process of machining is difficult from the material composition and structure. We used the NaNO₃ and NaClO₃ electrolyte composite to select the appropriate concentration, and then by using the orthogonal experiment and gray relational analysis method, we discussed how the voltage, feed speed, and electrolyte pressure solved the problem of the material removal rate (MRR), surface roughness (SR), and side gap. Under optimal conditions of 20 V, an electrolyte composite concentration of 178 g/l NaNO₃ and 41 g/l NaClO₃, a feed rate of 0.7 mm/min, and an electrolyte pressure of 0.8 MPa, a material removal rate of 100.8 mm3/min, a surface roughness of Ra 0.8 μm, and a side gap of 0.16 mm were produced. Given the same voltage, with an increasing cathode feed rate, the MRR was shown to increase while the surface roughness value and the side gap decreased. Under the same cathode feed rate, the MRR decreases, while the side gap and the surface roughness increase as the electrochemical machining application voltage increases. This study proves that using a certain concentration of electrolyte composite is a simple, low-cost, and feasible approach in improving efficiency and quality.