Application of non-dominated sorting genetic algorithm for multi-objective optimization of electrical discharge diamond face grinding process

Hybrid machining processes (HMPs), having potential for machining of difficult to machine materials but the complexity and high manufacturing cost, always need to optimize the process parameters. Our objective was to optimize the process parameters of electrical discharge diamond face grinding (EDDFG), considering the simultaneous effect of wheel speed, pulse current, pulse on-time and duty factor on material removal rate (MRR) and average surface roughness (Ra). The experiments were performed on a high speed steel (HSS) workpiece at a self developed face grinding setup on an EDM machine. All the experimental results were used to develop the mathematical model using response surface methodology (RSM). The developed model was used to generate the initial population for a genetic algorithm (GA) during optimization, non-dominated sorting genetic algorithm (NSGA-II) was used to optimize the process parameters of EDDFG process. Finally, optimal solutions obtained from pareto front are presented and compared with experimental data.     

Influence of parameters and optimization of EDM performance measures on MDN 300 steel using Taguchi method

Maraging steel (MDN 300) exhibits high levels of strength and hardness. Optimization of performance measures is essential for effective machining. In this paper, Taguchi method, used to determine the influence of process parameters and optimization of electrical discharge machining (EDM) performance measures on MDN 300 steel, has been discussed. The process performance criteria such as material removal rate (MRR), tool wear rate (TWR), relative wear ratio (RWR), and surface roughness (SR) were evaluated. Discharge current, pulse on time, and pulse off time have been considered the main factors affecting EDM performance. The results of the present work reveal that the optimal level of the factors for SR and TWR are same but differs from the optimum levels of the factors for MRR and RWR. Further, discharge current, pulse on time, and pulse off time have been found to play a significant role in EDM operations. Detailed analysis of structural features of machined surface was done by using scanning electron microscope (SEM) to understand the influence of parameters. SEM of electrical discharge machining surface indicates that at higher discharge current and longer pulse on duration give rougher surface with more craters, globules of debris, pockmarks or chimneys, and microcracks than that of lower discharge current and lower pulse on duration.     

激光微涂敷层的电火花后处理及其加工性能

分析、测量了不同加工条件下的材料去除率、相对电极损耗和电火花加工表面粗糙度,并研究了表面微裂纹和微硬度分布。实验结果表明,不同的材料具有类似的电火花加工性能,材料去除率随脉冲电流的增加而增加,峰值电流比脉冲宽度对表面粗糙度的影响更显著。研究结果对于选择合适参数进行电火花后处理具有重要意义。     

利用神经网络建立电火花加工工艺模型

以峰值电流、脉冲宽度、脉冲间隔、抬刀时间和加工时间为输入参数,以加工速度和表面粗糙度为输出参数,利用人工神经网络技术建立了电火花加工工艺模型。经过与实验数据的比较,认为该模型能精确地预测出给定条件下的加工速度和表面粗糙度,真实反映了机床的加工工艺规律。     

Multi-objective optimization of electric-discharge machining process using controlled elitist NSGA-II

Parametric optimization of electric discharge machining (EDM) process is a multi-objective optimization task. In general, no single combination of input parameters can provide the best cutting speed and the best surface finish simultaneously. Genetic algorithm has been proven as one of the most popular multi-objective optimization techniques for the parametric optimization of EDM process. In this work, controlled elitist non-dominated sorting genetic algorithm has been used to optimize the process. Experiments have been carried out on die-sinking EDM by taking Inconel 718 as work piece and copper as tool electrode. Artificial neural network (ANN) with back propagation algorithm has been used to model EDM process. ANN has been trained with the experimental data set. Controlled elitist non-dominated sorting genetic algorithm has been employed in the trained network and a set of pareto-optimal solutions is obtained.

     

Experimental investigation and prediction of optimum process parameters of micro-wire-cut EDM of 2205 DSS

Micro-wire-cut electrode discharge machining (EDM) is an emerging manufacturing process in the field of micro-manufacturing to fabricate the complex profiles of micro-components. It is a complex process involving various process parameters such as pulse on time, pulse off time, wire speed, wire tension and current. In addition to micro-fabrication, this process can also be extended in the field of tool design and developments such as dies, moulds, precision manufacturing, contour cutting, etc., where complex shapes need to be generated with high-grade dimensional accuracy and surface finish. In this research work, an attempt is made to investigate the effect of process parameters on the output variables such as material removal rate (MRR), surface finish and the cutting width (kerf) of wire-cut EDM for duplex stainless steel (DSS). Scanning electron microscopy (SEM) has been used to capture the images of the kerf width, and the measurements are taken with the help of the welding expert system and software. An optimization technique (Taguchi method) has been employed to identify the optimum parameters of the micro-wire-cut EDM process for cutting 2205 grade duplex stainless steel. The effect of each control parameter on the performance measure is studied individually using the plots of signal to noise ratio.     

Diamond face grinding of WC-Co composite with spark assistance: Experimental study and parameter optimization

Electro-discharge machining (EDM) characteristics of tungsten carbide-cobalt composite are accompanied by a number of problems such as the presence of resolidified layer, large tool wear rate and thermal cracks. Use of combination of conventional grinding and EDM (a new hybrid feature) has potential to overcome these problems. This article presents the face grinding of tungsten carbide-cobalt composite (WC-Co) with electrical spark discharge incorporated within face of wheel and flat surface of cylindrical workpiece. A face grinding setup for electro- discharge diamond grinding (EDDG) process is developed. The effect of input parameters such as wheel speed, current, pulse on-time and duty factor on output parameters such as material removal rate (MRR), wheel wear rate (WWR) and average surface roughness (ASR), are investigated. The present study shows that MRR increases with increase in current and wheel speed while it decreases with increase in pulse on-time for higher pulse on-time (above 100 μs). The most significant factor has been found as wheel speed affecting the robustness of electro- discharge diamond face grinding (EDDFG) process.     

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.     

Effect of low-frequency vibration on workpiece in EDM processes

High-frequency vibration aided EDM has become one of the ways to increase material removal rate in EDM process, due to the flushing effect caused by vibration. However, utilizing high-frequency vibration, especially in ultrasonic range consumes a lot of setup cost. This work presents an attempt to use a low-frequency vibration on workpiece of stainless steel (SS 304) during EDM process. The workpiece was vibrated with variations of low-frequency and low-amplitude. The results show that the application of low-frequency vibration in EDM process can be used to increase the material removal rate, and decrease the surface roughness and tool wear rate.     

INVESTIGATING THE EFFECTS OF EDM PARAMETERS ON SURFACE INTEGRITY,MRR AND TWR IN MACHINING OF Ti–6Al–4V

Ti–6Al–4V is a kind of difficult-to-cut material with poor machinability by traditional machining methods, while electrical discharge machining (EDM) is suitable for machining titanium alloys. In this paper, three input machining parameters including pulse current, pulse on time and open circuit voltage were changed during EDM tests. To investigate the output characteristics; material removal rate (MRR), tool wear ratio (TWR) and different aspects of surface integrity for Ti–6Al–4V samples such as topography of machined surface, crack formation, white layer (recast layer) thickness and microhardness were considered as performance criteria. The variations of MRR and TWR versus input machining parameters were investigated by means of main and interaction effect plots and also verified by ANOVA results. The effect of pulse energy based on pulse on time and pulse current variations against recast layer thickness and microhardness was studied. The possibility of forming different chemical elements and compounds on the work surface after EDM process was investigated by EDS and XRD analyses. The experimental results revealed that general aspects of surface integrity for machined samples are mostly affected by pulse current and pulse on time. The approximate density of cracks, micro holes and pits on the work surface is intensively dependent on pulse energy variations. Although increase of pulse energy improves the material removal efficiency but leads to increase of average thickness and microhardness of recast layer.     

Optimization of machining parameters in rotary EDM process by using the Taguchi method

Electrical discharge machining (EDM) is one of the advanced methods of machining. Most publications on the EDM process are directed towards non-rotational tools. But rotation of the tool provides a good flushing in the machining zone. In this study, the optimal setting of the process parameters on rotary EDM was determined. A total of three variables of peak current, pulse on time, and rotational speed of the tool with three types of electrode were considered as machining parameters. Then some experiments have been performed by using Taguchi's method to evaluate the effects of input parameters on material removal rate, electrode wear rate, surface roughness, and overcut. Moreover, the optimal setting of the parameters was determined through experiments planned, conducted, and analyzed using the Taguchi method. Results indicate that the model has an acceptable performance to optimize the rotary EDM process.     

Investigation of EDM characteristics of nickel-based heat resistant alloy

The EDM processing characteristics of one of the nickel-based heat resistant alloys, Hast-elloy-X, were investigated under the various EDM conditions and analyzed in terms of surface integrity. This alloy is commonly used as a material for the hot gas path component of gas turbines and it is difficult to machine by conventional machining methods. The primary EDM parameter which was varied in this study were the pulse-on time. Since the pulse-on time is one of the main factors that determines the intensity of the electrical discharge energy, it was expected that the machining ratio and the surface integrity of the specimens would be proportionally dependent on the pulse-on duration. However, experimental results showed that MRR (material removal rate) and EWR (electrode wear rate) behaved nonlinearly with respect to the pulse duration, whereas the morphological and metallurgical features showed rather a constant trend of change by the pulse duration. In addition the heat treating process affected the recast layer and HAZ to be recrystallized but softening occurred in recast layer only. A metallurgical evaluation of the microstructure for the altered material zone was also conducted.     

Multi-response optimization of machining process parameters for powder mixed electro-discharge machining of H-11 die steel using grey relational analysis and topsis

Electro-discharge machining (EDM) is an enormously used nonconventional process for removing material in die making, aerospace, and automobile industries. It consists of limitations like poor volumetric material removal rate (MRR) and reduced surface quality. Powder mixed EDM (PMEDM) is a new development in EDM to enhance its machining capabilities. The present work investigates the effect of powder concentration (C_p), peak current (I_p), pulse on time (T_on), duty cycle (DC) and gap voltage (V_g) on MRR, tool wear rate (TWR), electrode wear ratio (EWR), and surface roughness (SR) simultaneously for H-11 die steel using SiC powder. Taguchi's L₂₇ orthogonal array has been used to conduct the experiments. Multiobjective optimization using grey relational analysis (GRA) and technique for order of preference by similarity to ideal solution (TOPSIS) has been used to maximize the MRR and minimize the TWR, EWR, and SR and determine the optimal set of process parameters. Analysis of variance (ANOVA) has been performed to understand the significance of each process parameter. Results were verified by conducting confirmatory tests. GRA and TOPSIS exhibit an improvement of 0.1843 and 0.14308 in the preference values, respectively. Microstructure analysis has been done using scanning electron microscope (SEM) for the optimum set of parameters.     

An experimental study for determination of the effects of machining parameters on surface roughness in electrical discharge machining (EDM)

Electrical discharge machining (EDM) is a non-traditional production method that has been widely used in the production of dies throughout the world in recent years. The most important performance measure in EDM is the surface roughness; among other measures material removal and tool wear rates could be listed. In this study, experiments were performed to determine parameters effecting surface roughness. The data obtained for performance measures have been analyzed using the design of experiments methods. A considerably profound equation is obtained for the surface roughness using power, pulse time, and spark time parameters. The results are discussed.     

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.     

Experimental and finite element analysis of EDM process and investigation of material removal rate by response surface methodology

In this study, thermal modeling and finite element simulation of electrical discharge machining (EDM) has been done, taking into account several important aspects such as temperature-dependent material properties, shape and size of the heated zone (Gaussian heat distribution), energy distribution factor, plasma flushing efficiency, and phase change to predict thermal behavior and material removal mechanism in EDM process. Temperature distribution on the cathode has been calculated using ANSYS finite element code, and the effect of EDM parameters on heat distribution along the radius and depth of the workpiece has been obtained. Temperature profiles have been used to calculate theoretical material removal rate (MRR) from the cathode. Theoretically calculated MRRs are compared with the experimental results, making it possible to precisely determine the portion of energy that enters the cathode for AISI H13 tool steel. Also in this paper, the effect of EDM parameters on MRR has been investigated by using the technique of design of experiments and response surface methodology. Finally, a quadratic polynomial regression model has been proposed for MRR, and the accuracy of this model has been checked by means of analysis of residuals.     

Development of an intelligent process model for EDM

This paper reports the development of an intelligent model for the electric discharge machining (EDM) process using finite-element method (FEM) and artificial neural network (ANN). A two-dimensional axisymmetric thermal (FEM) model of single-spark EDM process has been developed based on more realistic assumptions such as Gaussian distribution of heat flux, time- and energy-dependent spark radius, etc. to predict the shape of crater cavity, material removal rate, and tool wear rate. The model is validated using the reported analytical and experimental results. A neural-network-based process model is proposed to establish relation between input process conditions (discharge power, spark on time, and duty factor) and the process responses (crater geometry, material removal rate, and tool wear rate) for various work—tool work materials. The ANN model was trained, tested, and tuned using the data generated from the numerical (FEM) simulations. The ANN model was found to accurately predict EDM process responses for chosen process conditions. It can be used for the selection of optimum process conditions for EDM process.     

Optimisation of the EDM Process Based on the Orthogonal Array with Fuzzy Logic and Grey Relational Analysis Method

In this paper, the use of the grey relational analysis based on an orthogonal array and fuzzy-based Taguchi method for optimising the multi-response process is reported. Both the grey relational analysis method without using the S/N ratio and fuzzy logic analysis are used in an orthogonal array table in carrying out experiments for solving the multiple responses in the electrical discharge machining (EDM) process. Experimental results have shown that both approaches can optimise the machining parameters (pulse on time, duty factor, and discharge current) with considerations of the multiple responses (electrode wear ratio, material removal rate, and surface roughness) effectively. It seems that the grey relational analysis is more straightforward than the fuzzy-based Taguchi method for optimising the EDM process with multiple process responses.     

Thermal modeling of the material removal rate and surface roughness for die-sinking EDM

The die-sinking electrical discharge machining (EDM) process is characterized by slow processing speeds. Research effort has been focused on optimizing the process parameters so as for the productivity of the process to be increased. In this paper a simple, thermal based model has been developed for the determination of the material removal rate and the average surface roughness achieved as a function of the process parameters. The model predicts that the increase of the discharge current, the arc voltage or the spark duration results in higher material removal rates and coarser workpiece surfaces. On the other hand the decrease of the idling time increases the material removal rate with the additional advantage of achieving slightly better surface roughness values. The model’s predictions are compared with experimental results for verifying the approach and present good agreement with them.     

Investigation of emulsion for die sinking EDM

Machining fluid is a primary factor that affects the material removal rate, surface quality, and electrode wear of electrical discharge machining (EDM). Kerosene is the most commonly used working fluid in die sinking EDM, but it shows low ignition temperature and high volatility; if the improper operations are undertaken, it can cause conflagration. Using distilled water or pure water as the machining fluid in EDM, no fire hazard occurs, and the working environment is well; however, using distilled water or pure water as the machining fluid in EDM, the material removal rate of machining large surface is low, and the machine tool is easily eroded. Emulsion-1 and emulsion-2 used as working fluid in die sinking EDM are developed. The compositions of emulsion-1 and emulsion-2 are introduced. In comparison with kerosene, emulsion-1 and emulsion-2 used in EDM show high material removal rate, low surface roughness, high discharge gap, and good working environment. The electrode wear ratio in emulsion-1 is lower than that in kerosene. The electrode wear ratio in emulsion-2 is higher than that in kerosene. The effects of composition and concentration of emulsifier on the emulsion property and EDM performance have been investigated. The comparative tests of EDM performance with kerosene, emulsion-1, and emulsion-2 have been done.