scholarly journals A Simple Procedure for Searching Pareto Optimal Front in Machining Process: Electric Discharge Machining

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Ushasta Aich ◽  
Simul Banerjee
Keyword(s):  
Electric Discharge ◽  
Removal Rate ◽  
Simple Procedure ◽  
Operating Conditions ◽  
Machining Process ◽  
Optimum Process ◽  
Pareto Optimal ◽  
Electric Discharge Machining ◽  
Optimum Process Parameter ◽  
Pareto Optimal Front

Optimum control parameter setting in complex and stochastic type processes is one of the most challenging problems to the process engineers. As such, effective model development and determination of optimal operating conditions of electric discharge machining process (EDM) are reasonably difficult. In this apper, an easy to handle optimization procedure, weight-varying multiobjective simulated annealing, is proposed and is applied to optimize two conflicting type response parameters in EDM—material removal rate (MRR) and average surface roughness (Ra) simultaneously. A solution set is generated. The Pareto optimal front thus developed is further modeled. An inverse solution procedure is devised so that near-optimum process parameter settings can be determined for specific need based requirements of process engineers. The results are validated.

Experimental Investigation of Sunflower Oil as Dielectric Fluid in Die Sinking Electric Discharge Machining Process

2019 ◽  
Vol 969 ◽  
pp. 715-719
Author(s):  
G. Gowtham Reddy ◽  
Balasubramaniyan Singaravel ◽  
K. Chandra Shekar
Keyword(s):  
Electric Discharge ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Dielectric Fluid ◽  
Machining Performance ◽  
Electric Discharge Machining ◽  
Dielectric Fluids ◽  
Pulse On Time ◽  
Pulse Off Time

Electric Discharge Machining (EDM) is used to machine complex geometries of difficult to cut materials in the area of making dies, mould and tools. Currently, hydrocarbon based dielectric fluids are used in EDM and which plays major role for material removal and it emits harmful emission. In this work, vegetable oil is attempted as dielectric fluid and their performance are studied during processing of AISI P20 steel. The effect of pulse on time (Pon) , pulse off time (Poff), and current (A) on Material Removal Rate (MRR), Tool wear rate (TWR) and surface roughness (SR) are analyzed. The result showed that vegetable oils are given good machining performance than conventional dielectric fluids. These proposed dielectric fluids are biodegradable eco friendly and enhance sustainability in EDM process.

Multi Objective Optimization of Electro Discharge Machining of Resin Bonded Silicon Carbide

2011 ◽  
Vol 110-116 ◽  
pp. 1556-1560
Author(s):  
R. Venkataraman
Keyword(s):  
Silicon Carbide ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Machining Process ◽  
Pareto Optimal ◽  
Electrode Wear ◽  
Pareto Optimal Front ◽  
Multi Objective ◽  
Electro Discharge Machining ◽  
Pulse On Time

This work is aimed at optimizing the various parameters of the electro discharge machining process in order to Maximize material removal rate (MRR) and Minimize electrode wear rate (EWR) for machining silicon or resin bonded silicon carbide, which is widely used in various applications like high-temperature gas turbines, bearings, seals and linings of industrial furnaces. The five parameters being optimized are intensity supplied by the generator of the EDM machine, open voltage, pulse on time, duty cycle and pressure of flushing fluid. The polynomial models for MRR and EWR proposed by Luis, Puertas and Villa [1] in terms of the five input parameters was used for formation of the objective function. Optimization was carried out using the multi objective genetic algorithm, which is a heuristic search technique that mimics natural selection. A Pareto-optimal front was obtained using this technique, and the points lying on this front represent the set of optimal solutions for the optimization problem. The resultant Pareto– optimal front can be used to select the appropriate operating conditions depending on the specific MRR, EWR or combination requirements.

Electro-Thermal Modelling for Material Removal Study in Electric Discharge Machining Process

2015 ◽  
Author(s):  
Yash Pachaury ◽  
Puneet Tandon
Keyword(s):  
Material Removal Rate ◽  
Electric Discharge ◽  
Material Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Two Dimensional ◽  
Electric Discharge Machining ◽  
Element Analysis ◽  
Plasma Flushing Efficiency ◽  
Art Research

In the present study, an attempt has been made to model the electric discharge machining process using the numerical simulation technique. Realistic parameters are added in the model such as variable fraction of heat going to the electrodes, and variation in the plasma flushing efficiency with the process parameters. Gaussian distributed heat flux is applied at the spark location and the two-dimensional heat conduction equation is solved with the help of finite element analysis technique to determine the temperature distribution within the two-dimensional process continuum, using averaged thermo-physical properties of the work material. Melting isotherms are determined and the material removed during a single discharge is obtained from it. Material removal rate is determined using a regression model for the plasma flushing efficiency. Experimental validation is made with the help of highly precise AGIE SIT experimental data. The material removal rate is also compared with state of the art research of other researchers. It has been observed that, at low value of the discharge energies, the proposed model is able to predict the experimental material removal rate better than that of the model proposed by other researchers. However, as the discharge energy increases, the accuracy of prediction decreases. The model can be used for achieving process parameter optimization hence saving both the costs and large lead times associated with determining optimized parameters experimentally.

scholarly journals Optimization of Machining Variables in Electric Discharge Machining Using Stainless Steel 317 in Full Factorial Method

2020 ◽  
Vol 22 (1) ◽  
pp. 105-118 ◽  
Author(s):  
S. Nandhakumar ◽  
S. Sathish Kumar ◽  
K. Sakthivelu
Keyword(s):  
Wear Rate ◽  
Tool Wear ◽  
Electric Discharge ◽  
Metal Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Tool Wear Rate ◽  
Electric Discharge Machining ◽  
Machining Time ◽  
Input Variables

AbstractElectric Discharge Machining (EDM) is a non-conventional machining process and has a larger extent of application in manufacturing industry due to its accuracy. EDM simply uses electrical spark between the tool and workpiece in presence of dielectric medium to erode the workpiece in controlled manner. Improving the material removal rate and decreasing the tool wear rate (TWR), achieving higher surface finish, reducing machining time and enhancing dimensional accuracy are the major areas of focus in electrical discharge machining (EDM) process of SS 317 grade steel. In this research work effort to reduce the tool wear rate is concentrated by comparing the machining performance of two distinct electrodes namely copper and brass. Each electrode has their unique machining capabilities and the experimental results were compared in-terms of tool wear rate (TWR), Metal Removal Rate (MRR) and Machining Time (TM). Input variables were optimized based on the experimental output responses to achieve optimal level of input variables.

Optimization of Process Parameters in EDM Using Taguchi Method with Grey Relational Analysis and Topsis for Ceramic Composites

2016 ◽  
Vol 22 ◽  
pp. 83-93 ◽  
Author(s):  
M. Kalayarasan ◽  
M. Murali
Keyword(s):  
Electric Discharge ◽  
Material Removal ◽  
Removal Rate ◽  
Ceramic Composites ◽  
Machining Process ◽  
Electric Discharge Machining ◽  
Relational Analysis ◽  
Grey Relational ◽  
Machining Parameter ◽  
Conventional Machining

Silicon Nitride-Titanium Nitride ceramic composites are newly advanced material having the properties of high hardness, strength, toughness and low density. These kinds of materials are challenging to machine by conventional machining process because it causes severe tool wear due to its properties. Since the materials can be machined by non-conventional machining process like laser cutting and water jet, but these processes are limited. Electric discharge machining shows higher capability for cutting complex shapes with high accuracy. The present work focuses to optimize the process parameter for maximum material removal rate and minimum electrode wear rate. The experimental studies were conducted under varying pulse on time, pulse off time, dielectric pressure and discharge current. Taguchi L9 orthogonal array was used to design the experiments. Grey relational analysis and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to optimize the process parameter and the results were validated by the confirmation tests. Thus the machining parameter for electric discharge machine was optimized to achieve higher material removal rate and lower rate on electrode. The result shows that the proposed technique is being effective to optimize the machining parameter for electric discharge machining process.

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.

scholarly journals Modeling of Interelectrode Gap in Electric Discharge Machining and Minimum Variance Self-Tuning Control of Interelectrode Gap

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Bin Xin ◽  
Ming Gao ◽  
Shujuan Li ◽  
Bin Feng
Keyword(s):  
Electric Discharge ◽  
Removal Rate ◽  
Short Circuit ◽  
Minimum Variance ◽  
Machining Process ◽  
Electric Discharge Machining ◽  
Precise Control ◽  
Interelectrode Gap ◽  
Machining System ◽  
P Type

In the electric discharge machining system, the determination of the gap between the anode and the cathode is a difficult point of this kind of machining approach. An accurate mathematical model of interelectrode gap is obtained, and the precise control of the gap is achieved on this basis. In this paper, based on the example of discharge machining of P-type single crystal Si, the theoretical analysis proved that the discharge channel can be equivalent to pure resistance, and the physical model of the interelectrode gap and voltage and current was established. The order and parameters of the EDM system model were determined by adopting the system identification theory. We designed the minimum variance self-correcting controller to accurately control the interelectrode gap in combination with the actual machining process. Experimental results show that the interelectrode gap model can correctly reflect the interelectrode gap in the actual machining process; the minimum variance self-correcting controller eliminates the short circuit phenomenon during processing and can stably track different desired gaps; the material removal rate and the surface roughness decrease with the increase of the interelectrode gap.

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