scholarly journals Comparative Study of Optimization Models for Evaluation of EDM Process Parameters on Ti-6Al-4V

Modelling ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 555-566
Author(s):  
JagadeeswaraRao Maddu ◽  
Buschaiah Karrolla ◽  
Riyaaz Uddien Shaik ◽  
Srikanth Vuppala

In this paper, different optimization techniques such as multi-objective optimization based on ratio analysis, the -nD angle, information divergence and multi-angle optimization methods were considered for comparative study in order to check their variation in results. These four techniques were considered asthese techniques were made from completely different methodologies, such as MOORA, is one of the latest multi-criteria decision-making methods that cover the weakness of other older methods and the latter three (-nD angle, Information Divergence and MAOT) methods are based on trigonometric methodologies. These optimization techniques were carried out using the effect of EDM process parameters viz., material removal rate and surface roughness as output parameters and current, pulse on time, pulse off time and different electrode materials as input process parameters. These parameters were obtained from the experiments modelled according to the Taguchi experimental design procedure in which the L18 orthogonal array was used to perform experimentation with the material of titanium alloy (Ti-6Al-4V). All the optimization techniques have obtained similar results among which -nD angle and Information Divergence technique tend to be easier and understandable for any similar application. The latter two methods avoid complexity and can be used for optimizing any relevant manufacturing process parameters such as the parameters of EDM, additive manufacturing, etc.

Author(s):  
Uvaraja Ragavendran ◽  
Ranjan Kumar Ghadai ◽  
Akash Kumar Bhoi ◽  
Manickam Ramachandran ◽  
Kanak Kalita

Electrical discharge machining (EDM) is a broadly used nonconventional material removal process for the machining of conductive work material irrespective of their hardness. In this article, empirical models for material removal rate (MRR) and surface roughness (Ra) of the workpiece are developed based on the extensive experiments performed on a special steel (WP7V) workpiece using a copper electrode. To account for the various parameters, an experimental design based on response surface methodology (RSM) is conducted considering three different factors namely — current, pulse-on-time, and pulse-off-time, each having three different levels. Analysis of variance (ANOVA) is conducted to test the statistical significance of the proposed empirical models. It is essential to determine the relationship and significance of input–output variation. Thus a sensitivity analysis is conducted. The interaction effect of input variables is also studied. Two different state-of-art optimization techniques, namely genetic algorithm (GA) and particle swarm optimization (PSO), are applied to predict the optimal combination of process parameters. Finally, multi-objective optimization is also carried out to simultaneously maximize MRR while minimizing Ra.


2015 ◽  
Vol 813-814 ◽  
pp. 368-375
Author(s):  
Suddala Chandramouli ◽  
Kesha Eswaraiah

Electrical Discharge Machining is a thermo-electric process and 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 Electric Discharge machining (REDM) was determined. The important process parameters that have been selected are peak current, pulse on time, pulse off time and rotational speed of tool with output response as Material Removal Rate (MRR).Taguchi experimental design (L27 orthogonal array) was used to formulate the experimental layout and experiments were conducted on Hardened stainless steel machined with copper tungsten electrode. ANOVA method was used with the help of MINITAB 17 software to analysis the influence of input process parameters on the MRR using Rotary Electric Discharge Machining. The input parameters were optimized in order to obtain maximum MRR, The results of the present work revealed that proper selection of input parameters will play a significant role on MRR.


Author(s):  
Duraisivam Saminatharaja ◽  
Suresh Periyakgounder ◽  
Mahalingam Selvaraj ◽  
Jamuna Elangandhi

Electrical discharge machines (EDM) are widely employed in machining components containing complex profiles of hard-to-cut and machining materials. However, the fabrication-of-tool time for the EDM process is excessively high in the traditional machining method, which significantly affects the machining rate. Therefore, in this paper, a powder metallurgy (PM) technique is employed to fabricate the tool electrode using copper (Cu), titanium carbide (TiC), and zirconium silicate (ZrSiO4) for different combinations. An L18 orthogonal array (OA) is planned using the following input parameters: three types of tools (Cu, Cu90, Cu80), peak current (PC) [A], pulse on time (PT) [µs], and gap voltage (GV) [V]. The performance of EDM is evaluated through the material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR). The process parameters are optimized using two different techniques: the technique for order of preference by similarity to the ideal solution (TOPSIS) and grey relational analysis (GRA). TOPSIS and GRA optimization techniques produce the same optimal parametric solution for less TWR, SR, and higher MRR with the combination of the Cu90 tool, E8 APC, 15 µs pulse PT, and 75 V GV. Based on the ANOVA table of TOPSIS, pulse on time plays a major role, contributing 46.8 % of the machining performance; peak current shows the most significant contribution of 39.3 % of the machining performance using GRA values. Furthermore, the scanning electron microscope (SEM) image analyses are carried out on the machined workpiece surface to understand the effect of tools on machining quality.


2014 ◽  
Vol 590 ◽  
pp. 202-206
Author(s):  
Pichai Janmanee ◽  
Suppawat Chuvaree ◽  
Jamkamon Kamonpong

In this study, experiments were performed to study the effects of electrode materials mixed with nickel in electrical discharge machining (EDM) of SUS 304 material. Experiments were constructed using parameters consisting of pulse-on time, pulse-off time, discharge current and electrode polarity, respectively. The analysis of structural features of the surface was accomplished using a scanning electron microscope (SEM) as well as an element analysis created on the surface, after the EDM process, by using Energy-dispersive x-ray spectroscopy (EDS). The results of the experiments found that nickel elements in the electrode material have an effect on the working performance of material removal rate and electrode wear ratio. The electrode wear ratio reduces when nickel elements increase. Moreover, the surface roughness had the lowest level at electrode 15 % nickel element. Thus, electrode wear during the EDM process of nickel element from electrodes and other elements, combined with surface metalworking, becomes a recast layer of nickel.


2015 ◽  
Vol 772 ◽  
pp. 245-249
Author(s):  
A. Ramamurthy ◽  
R. Sivaramakrishnan ◽  
S. Venugopal ◽  
T. Muthuramalingam

It is very important and complexity to find the optimum values of wire EDM process parameters and contribution of each parameter to attain the better performance characteristics. In this study, an attempt has been made to optimize those parameters while machining the titanium alloy. Since the process involves more one than one response parameter, it is essential to carry out the multi-response optimization methodology .The experiments have been conducted with different levels of input factors such as pulse on time,pulse off time and wire tension based on Taguchi L9 orthogonal table.Wire EDM optimal process parameter has been identified using grey relational analysis and significant parameter has been determined by analysis of variance. Experimental results have indicated that the multi-response characteristic such as material removal rate and surface roughness can be improved effectively through grey relational analysis.


Author(s):  
Balbir Singh ◽  
Jatinder Kumar ◽  
Sudhir Kumar

This paper presents the experimental investigation on the electro-discharge machining of aluminum alloy 6061 reinforced with SiC particles using sintered Cu–W electrode. Experiments have been designed as per central composite rotatable design, using response surface methodology. Machining characteristics such as material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR) have been investigated under the influence of four electrical process parameters; namely peak current, pulse on time, pulse off time, and gap voltage. The process parameters have been optimized to obtain optimal combination of MRR, EWR, and SR. Further, the influence of sintered Cu–W electrode on surface characteristics has been analyzed with scanning electron microscopy, energy dispersive spectroscopy, and Vicker microhardness tests. The results revealed that all the process parameters significantly affect MRR, EWR, and SR. The machined surface properties are modified as a result of material transfer from the electrode. The recast layer thickness is increased at higher setting of electrical parameters. The hardness across the machined surface is also increased by the use of sintered Cu–W electrode.


2018 ◽  
Vol 7 (2.8) ◽  
pp. 10
Author(s):  
A VS Ram Prasad ◽  
Koona Ramji ◽  
B Raghu Kumar

Machining of Titanium alloys is difficult due to their chemical and physical properties namely excellent strength, chemical reactivity and low thermal conductivity. Traditional machining of such materials leads to formation of continuous chips and tool bits are subjected to chatter which leads to formation of poor surface on machined surface. In this study, Wire-EDM one of the most popular unconventional machining process which was used to machine such difficult-to-cut materials. Effect of Wire-EDM process parameters namely peak current, pulse-on- time, pulse-off-time, servo voltage on MRRand SR was investigated by Taguchi method. 0.25 mm brass wire was used in this process as electrode material. A surface roughness tester (Surftest 301) was used to measure surface roughness value of the machined work surface. A multi-response optimization technique was then utilized to optimize Wire-EDM process parameters for achieving maximum MRR and minimum SR simultaneously.


2021 ◽  
Vol 71 (1) ◽  
pp. 1-18
Author(s):  
Basha Shaik Khadar ◽  
Raju M. V. Jagannadha ◽  
Kolli Murahari

Abstract The paper investigates the influence of boron carbide powder (B4C) mixed in dielectric fluid on EDM of Inconel X-750 alloy. The process parameters selected as discharge current (Ip), pulse on time(Ton), pulse off time(Toff), boron carbide(B4C) powder concentration to examine their performance responses on Material Removal Rate (MRR), Surface Roughness(Ra) and Recast Layer Thickness (RLT).In this study, o examine the process parameters which influence the EDM process during machining of Inconel X-750 alloy using combined techniques of Taguchi and similarity to ideal solutions (TOPSIS).Analysis of variance (ANOVA) was conducted on multi-optimization technique of Taguchi-TOPSIS. ANOVA results identified the best process parameters and their percentages. It developed the mathematical equation on Taguchi-TOPSIS performance characteristics results. The multi optimization results indicated that Ip and Toff are more significant parameters; V, and Ton parameters are less significant. Finally, surface structures were studied at optimized EDM conditions by using scanning electron microscope (SEM).


2020 ◽  
Vol 17 (3) ◽  
pp. 389-397
Author(s):  
Harvinder Singh ◽  
Vinod Kumar ◽  
Jatinder Kapoor

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.


2018 ◽  
Vol 63 (1) ◽  
pp. 16-25 ◽  
Author(s):  
Partha Protim Das ◽  
Sunny Diyaley ◽  
Shankar Chakraborty ◽  
Ranjan Kumar Ghadai

Wire electro discharge machining (WEDM) is a versatile non-traditional machining process that is extensively in use to machine the components having intricate profiles and shapes. In WEDM, it is very important to select the optimal process parameters so as to enhance the machine performance. This paper emphasizes the selection of optimal parametric combination of WEDM process while machining on EN31 steel, using grey-fuzzy logic technique. Process parameters such as servo voltage, wire tension, pulse-on-time and pulse-off-time were considered while taking into account several multi-responses such as material removal rate (MRR) and surface roughness (SR). It was found that pulse-on-time of 115 µs, pulse-off-time of 35 µs, servo voltage of 40 V and wire tension of 5 kgf results in a larger value of grey fuzzy reasoning grade (GFRG) which tends to maximize MRR and improve SR. Finally, analysis of variance (ANOVA) is applied to check the influence of each process parameters in the estimation of GFRG.


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