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.

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.

Nature-Inspired Metaheuristic Approach for Multi-Objective Optimization During WEDM Process

2018 ◽  
pp. 91-122
Author(s):  
Goutam Kumar Bose ◽  
Pritam Pain
Keyword(s):  
Removal Rate ◽  
Experimental Result ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
The Individual ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Grey Relation ◽  
Off Time

In this research paper Wire-Electric Discharge Machining (WEDM) is applied to machine AISI-D3 material in order to measure the performance of multi-objective responses like high material removal rate and low roughness. This contradictory objective is accomplished by the control parameters like Pulse on Time (Ton), Pulse off Time (Toff), Wire Feed (W/Feed) and Wire Tension (W/Ten) employing brass wire. Here the orthogonal array is used to developed 625 parametric combinations. The optimization of the contradictory responses is carried out in a metaheuristic environment. Artificial Neural Network is employed to train and validate the experimental result. Primarily the individual responses are optimized by employing Firefly algorithm (FA). This is followed by a multi-objective optimization through Genetic algorithm (GA) approach. As the results obtained through GA infer a domain of solutions, therefore Grey Relation Analysis (GRA) is applied where the weights are considered through Fuzzy set theory to ascertain the best parametric combination amongst the set of feasible alternatives.

scholarly journals Multi-Objective Optimization of Wire Electrical Discharge Machining of AL 2124/SIC Composite

2019 ◽  
Vol 9 (1) ◽  
pp. 2155-2163
Keyword(s):  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
High Strength ◽  
Wire Electrical Discharge Machining ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Predicted Values ◽  
Pulse On Time ◽  
Pulse Off Time

The growing demand for the use of high strength to weight alloys in industries for manufacturing complex structures challenges the machinability of such advanced materials. In the present investigation, the machinability of SiC particle reinforced Al 2124 composite was studied on Wire electrical discharge machining (WEDM). The process parameters namely pulse on-time (Ton), pulse off time (Toff), peak current (IP), and servo voltage (SV) were optimized by utilizing the central composite design layout. The output responses such as kerf and material removal rate (MRR) were studied in detail. The single and multi-objective optimization was studied for a combination effect using Derringer’s desirability approach and Genetic Algorithm (GA). The experimental and predicted values for each response were validated at the optimized condition. The experimental results were found in line with the predicted values. Multi objective optimization of kerf and MRR by GA showing better result compared to RSM.

Multiple Performance Optimization in WEDM Parameters Using Grey Relational Analysis

2015 ◽  
Vol 813-814 ◽  
pp. 357-361
Author(s):  
T. Rajmohan ◽  
Gopi Krishna ◽  
Ankit Kumar Singh ◽  
A.P.V. Swamy Naidu
Keyword(s):  
Grey Relational Analysis ◽  
Performance Characteristics ◽  
304L Stainless Steel ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Grey Relational ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Off Time

In this investigation, a new approach is based on Grey Relational Analysis and Taguchi method to optimize the machining parameters with multi performance characteristics in WEDM of 304L SS. Experiments are conducted using Taguchi Quality Concept, L9,3-level orthogonal array was chosen for experiments .The WEDM parameters namely pulse-on time (TON), pulse-off time (TOFF), and wire feed (WF) on material removal rate (MRR) .The Grey Relational Analysis with multiple performance characteristics indicates that the pulse-on time (TON), pulse-off time (TOFF) are the most significant factors . The optimum machining parameters have been identified by Grey relational analysis and significant contribution of parameters can be determined by analysis of variance (ANOVA). The confirmation test is also conducted to validate the test result. The results from this study will be useful for manufacturing engineers to select appropriate WEDM process parameters to machine 304L Stainless Steel.

scholarly journals Multi-Objective Optimization of Wire Electro Discharge Machining (WEDM) Process Parameters Using Grey-Fuzzy Approach

2018 ◽  
Vol 63 (1) ◽  
pp. 16-25 ◽  
Author(s):  
Partha Protim Das ◽  
Sunny Diyaley ◽  
Shankar Chakraborty ◽  
Ranjan Kumar Ghadai
Keyword(s):  
Process Parameters ◽  
Removal Rate ◽  
Machining Process ◽  
Wire Tension ◽  
Electro Discharge Machining ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Fuzzy Logic Technique ◽  
Off Time

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.

Multi-objective optimization of turning titanium-based alloy Ti-6Al-4V under dry, wet, and cryogenic conditions using gray relational analysis (GRA)

2020 ◽  
Vol 106 (9-10) ◽  
pp. 3897-3911 ◽  
Author(s):  
Muhammad Ali Khan ◽  
Syed Husain Imran Jaffery ◽  
Mushtaq Khan ◽  
Muhammad Younas ◽  
Shahid Ikramullah Butt ◽  
...  
Keyword(s):  
Gray Relational Analysis ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Relational Analysis ◽  
Cryogenic Conditions

scholarly journals A Study On Machining Characteristics of Al7075-NiCr-Gr Metal Matrix Composites Through Wire – Cut Electro Discharge Machining

2021 ◽  
Author(s):  
R. Palani ◽  
M. Sakthivel ◽  
V. Chithambaram ◽  
Geetha Palani
Keyword(s):  
Removal Rate ◽  
Energy Dispersive Spectrometer ◽  
Stir Casting ◽  
Vital Role ◽  
Matrix Composites ◽  
Practical Applications ◽  
Electro Discharge Machining ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time

Abstract The aluminium and its alloys play a vital role in industry for their wide practical applications. In the present work, Al7075 was reinforced with Ni-Cr and graphite by Stir casting method. Further the optimization of the machined composite was done by Taguchi method. It was inferred that the MRR value of 0.056435 g/min was obtained with input parameters of 8 amps current, 52 Volt, 4 µs pulse on time, 17 µs pulse off time by machining with WEDM and SR value of 3.3 µm showing smooth surface. The material removal rate of the composite was found and the morphology of the material was analysed by SEM with associated elemental analysis by energy dispersive spectrometer (EDS). The reinforcements present in the composite were also verified. The outcome of this micro structural investigation revealed that a non-uniform distribution of graphite particles takes place at all weight percentages of graphite reinforcement.

scholarly journals Response Surface Grey Relational Analysis On The Manufacturing of High Grade Biomedical Ti-13Zr-13Nb

2022 ◽  
Author(s):  
Johnson Kehinde Abifarin ◽  
Fredah Batale Fidelis ◽  
Moshood Yemi Abdulrahim ◽  
Elijah Oyewusi Oyedeji ◽  
Tochukwu Nkwuo ◽  
...  
Keyword(s):  
Response Surface ◽  
Grey Relational Analysis ◽  
Residual Error ◽  
Relational Analysis ◽  
Rsm Optimization ◽  
Grey Relational ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
The Mathematical Model ◽  
Off Time

Abstract Optimization of the manufacturing conditions with more than one performance characteristics have been a thing of concern, especially for Response Surface Method (RSM) optimization. Hence, this study addressed this challenge by reanalyzing a data presented in a previous study using grey relational analysis (GRA) and regression analysis. Central Composite Design (CCD) of RSM with high and low values of manufacturing conditions; voltage (50, 70) V, current (8, 16) A, pulse ON time (6, 10) μs, and pulse OFF time (7, 11) μs. The manufacturing conditions for optimal biomedical Ti-13Zr-13Nb alloy were obtained to be 50V voltage, 8A current, 6 μs pulse ON time, and 11 μs pulse OFF time. It was also revealed that the mathematical model was very efficient because the modeled GRG was in consonant with the experimental one. In addition, it was also established that current was the most significant manufacturing condition with a contribution of 47.27%. Voltage, factors interactions and residual error were insignificant on the GRG value of the titanium alloy. In conclusion, it can be deduced that the a small value of voltage within the considered settings could be used to manufacture better grade Ti-13Zr-13Nb alloy and also the small value of residual error showed the high manufacturability of the material.

Optimization of WEDM process parameters in machining Nimonic 75 alloy using brass wire

2020 ◽  
Vol 16 (5) ◽  
pp. 1189-1202 ◽  
Author(s):  
Harvinder Singh ◽  
Vinod Kumar ◽  
Jathinder Kapoor
Keyword(s):  
Removal Efficiency ◽  
Process Parameters ◽  
Material Removal ◽  
Kerf Width ◽  
Content Type ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Nimonic 75 ◽  
Off Time

PurposeAn experimental study has been conducted to model and optimize wire electric discharge machining (WEDM) process parameters such as pulse-on time, pulse-off time, servo voltage and peak current for response characteristics during machining of Nimonic 75 alloy.Design/methodology/approachThe response surface methodology (RSM)-based Box–Behnken's design has been employed for experimental investigation. RSM is used for developing quadratic regression models for selected response variables i.e. material removal efficiency and kerf width. To validate the model, confirmation experiments have been performed. The multi-response optimization has been done using desirability function approach.FindingsThrough analysis of variation, the percent contribution of process parameters on the response characteristics has been found. Pulse-off time is the most significant parameter affecting the kerf width and material removal efficiency followed by pulse-on time. The quadratic regression models have been developed for prediction of selected response variables. An attempt has been made to optimize the WEDM parameters for material removal efficiency and kerf width. The recommended process parameter setting for maximum material removal efficiency and minimum kerf width have been found to be pulse-on time = 0.6 µs, pulse-off time = 14 µs, servo voltage = 25 V and peak current = 200 A.Originality/valueThe “kerf width” is an important response variable for maintaining dimensional accuracy of the machined component, but has not been given due attention by the researchers. In the present work, the developed regression model for “kerf width” can be used in estimating wire offset setting and thereby getting a dimensionally accurate product. The optimum process parameters obtained in WEDM of Nimonic 75 alloy will contribute in database of machining. The outcome of this study would be added to scare database of the machining of Nimonic 75 alloy and also would be extremely useful for making the technology charts for WEDM.

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