Multi-objective optimization in wire electric discharge machining of Ti–6AL–4v using grey relational analysis for square and circular profiles

2021 ◽  
pp. 2250003
Author(s):  
P. Bharathi ◽  
G. Srinivasarao ◽  
P. Gopalakrishnaiah
Keyword(s):  
Process Parameters ◽  
Electric Discharge ◽  
Optimization Technique ◽  
Multi Objective Optimization ◽  
Electric Discharge Machining ◽  
Multi Objective ◽  
Relational Analysis ◽  
Wire Electric Discharge Machining ◽  
Pulse On Time ◽  
Pulse Off Time

In this work, an attempt has been made for optimization of process parameters in Wire Electric Discharge Machining (WEDM) of Ti–6Al–4V while producing square and circular profiles. The input parameters, namely pulse on time, pulse off time, peak current and servo voltage, were considered to study the responses cutting speed (CS) and surface roughness (SR). Each input parameter was set at three levels. Experiments were conducted as per central composite face (CCF) centered design. Based upon the experimental data, Gray relational analysis (GRA), a multi-objective optimization technique has been employed to find the best level of process parameters to optimize the machining profiles. Analysis of variance (ANOVA) has been conducted for investigating the effect of process parameters on overall machining performance. Finally, it was identified that the process parameters such as pulse on time, current and voltage have more impact on the square and circular profiles.

scholarly journals Determination of Multi-performance Characteristics in Electric Discharge Machining of DIN 1.2767 Steel Using Grey Relational Analysis

2021 ◽  
Vol 9 (1) ◽  
pp. 1-7
Author(s):  
Abubaker Y. Fatatit ◽  
Ali Kalyon
Keyword(s):  
Process Parameters ◽  
Electric Discharge ◽  
Removal Rate ◽  
Machining Process ◽  
Gray Relational Analysis ◽  
Machining Processes ◽  
Electric Discharge Machining ◽  
Relational Analysis ◽  
Pulse On Time ◽  
Pulse Off Time

   Electric discharge machining (EDM) is one of the most important unconventional machining processes, which can cut hard materials and complex shapes that are difficult to machine by conventional machining processes easily and with high accuracy. In this study, L18 orthogonal array combined with gray relational analysis (GRA) is implemented to investigate the multiple performances characteristics in EDM of DIN 1.2767 Tool Steel. Machining process parameters selected were discharge current (Ip), pulse-on time (Ton), pulse-off time (Toff), and electrode material (copper alloys [NSS and B2]). The investigated performances characteristics were tool wear rate (TWR) and material removal rate (MRR). Analysis of variance (ANOVA) and Taguchi’s signal-to-noise ratio with the help of Minitab-17 software were used to analysis the effect of the process parameters on TWR and MRR. The experimental results and data analysis reveal that TWR and MRR are more affected by Ip and Ton. The minimum TWR was obtained at parametric combination Ip (6A), Ton (800 μs), and Toff (800 μs) and the maximum MRR attained at Ip (25A), Ton (800 μs), Toff (200 μs), and NSS electrode. After applying GRA, the optimal parametric combination for MRR and TWR was determined as Ip (25A), Ton (800 μs), Toff (200 μs), and NSS electrode. The study also exhibited the occurrence of an interaction between the variables on the responses. In addition, scanning electron microscopy images showed that the metal surface was affected with the increase in Ton and Toff.

Optimization of Machining Parameters in Rotary EDM Process Using Copper Tungsten Electrode

2015 ◽  
Vol 813-814 ◽  
pp. 368-375
Author(s):  
Suddala Chandramouli ◽  
Kesha Eswaraiah
Keyword(s):  
Process Parameters ◽  
Electric Discharge ◽  
Removal Rate ◽  
Machining Parameters ◽  
Tungsten Electrode ◽  
Electric Discharge Machining ◽  
Input Parameters ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Edm Process

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.

Multi-objective optimization of micro wire electric discharge machining parameters using grey relational analysis with Taguchi method

2011 ◽  
Vol 225 (7) ◽  
pp. 1742-1753 ◽  
Author(s):  
K P Somashekhar ◽  
J Mathew ◽  
N Ramachandran
Keyword(s):  
Analysis Of Variance ◽  
Process Parameters ◽  
Electric Discharge ◽  
Grey Relational Analysis ◽  
Performance Characteristics ◽  
Electric Discharge Machining ◽  
Relational Analysis ◽  
Wire Electric Discharge Machining ◽  
Grey Relational ◽  
Wedm Process

Micro wire electric discharge machining (µ-WEDM) is an evolution of conventional wire EDM used for fabricating three-dimensional complex microcomponents, microstructures, and intricate profiles effectively with high-precision capabilities. Being a complex process, it is very difficult to determine optimal parameters for obtaining higher material removal rate (MRR) with minimum overcut (OC), and surface roughness (SR) is a challenging task in µ-WEDM for improving performance characteristics. In this study, a new approach for the optimization of the µ-WEDM process with multiple performance characteristics based on the statistical-based analysis of variance (ANOVA) and grey relational analysis (GRA) is attempted. Analysis of variance was used to study the significance of process parameters on grey relational grade (GRG) which showed capacitance to be the most significant factor. A GRG obtained from the GRA is used to optimize the µ-WEDM process. Optimum process parameters are determined by the GRG as the overall performance index. The process parameters, namely gap voltage, capacitance, and feed rate are optimized by considering multiple performance characteristics including MRR, OC, and SR. To validate the study, confirmation experiment has been carried out at optimal set of parameters, and predicted results have been found to be in good agreement with experimental findings. This approach showed improved machining performance in the µ-WEDM process.

Multi-Objective Optimization of Electro Discharge Machining of NIMONIC 75 Using Taguchi-Based Gray Relational Analysis

2020 ◽  
pp. 1-16
Author(s):  
Maninder Singh ◽  
Shankar Singh
Keyword(s):  
Tool Material ◽  
Gray Relational Analysis ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Relational Analysis ◽  
Electro Discharge Machining ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Nimonic 75 ◽  
Off Time

New superalloys are potential materials in aircraft and power plant industries because of their properties like high-temperature strength, creep life and resistance to corrosion and oxidation at elevated temperatures. Because of the superior properties of superalloys, machining them using the conventional processes is a difficult task that is associated with high cost and poor accuracy. In this study, an attempt has been made to machine NIMONIC 75 superalloy by the electro discharge machining (EDM) process, using the Taguchi-based Gray Relational Analysis method for multi-objective optimization of material removal rate (MRR), tool electrode wear rate (TEWR) and surface finish (SF). The experiments conducted were based on [Formula: see text] (2[Formula: see text]) orthogonal array. Six input parameters namely tool material, peak current, gap voltage, pulse on-time, pulse off-time and tool lift time were considered in this study. The validation results proved that the parametric setting of tool material as copper, peak current as 12[Formula: see text]A, gap voltage as 50[Formula: see text]V, pulse on-time as 200[Formula: see text][Formula: see text]s, pulse off-time as 15[Formula: see text][Formula: see text]s and tool lift time as 2[Formula: see text]s, yields optimized values of the performance characteristics. SEM images indicate the presence of numerous surface irregularities, whereas the XRD test shows the formation of various carbides on the EDMed surface.

Optimization of Material Removal Rate and Surface Roughness for Wire Electric Discharge Machining of AA7075 Composites using Grey Relational Analysis

2018 ◽  
Vol 9 (5) ◽  
Author(s):  
G. Ramanan ◽  
J. Edwin Raja Dhas ◽  
M. Ramachandran
Keyword(s):  
Surface Roughness ◽  
Electric Discharge ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Electric Discharge Machining ◽  
Relational Analysis ◽  
Wire Electric Discharge Machining ◽  
Grey Relational ◽  
Pulse On Time ◽  
The Impact

In automobile industries, usage of unconventional machining is increased due to their precision and accuracy. This research work is planned to upgrade the Wire Electric Discharge Machining (WEDM) process parameters by considering the impact of discharge current, pulse on time, pulse off time and servo speed rate. Tests have been led with these parameters for the measurement of metal removal rate and surface roughness for each of the trial run. This information has been used to fit a quadratic numerical model. Predicted information has been used as a graphical representation for demonstrating the impact of the parameters on chose reactions. Predicted information given by the models has been utilized as a part of an ideal parametric mix to accomplish the unrealistic yield of the procedure. Response surface method with grey relational analysis has been utilized for enhancement. The ideal value has been checked to the predicted value from the confirmation tests.

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