scholarly journals Modeling and Optimization of Fractal Dimension in Wire Electrical Discharge Machining of EN 31 Steel Using the ANN-GA Approach

Materials ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 454 ◽  
Author(s):  
Arkadeb Mukhopadhyay ◽  
Tapan Barman ◽  
Prasanta Sahoo ◽  
J. Davim
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Fractal Dimension ◽  
Process Parameters ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Wire Electrical Discharge Machining ◽  
Machining Parameters ◽  
Machined Surface ◽  
Wedm Process

To achieve enhanced surface characteristics in wire electrical discharge machining (WEDM), the present work reports the use of an artificial neural network (ANN) combined with a genetic algorithm (GA) for the correlation and optimization of WEDM process parameters. The parameters considered are the discharge current, voltage, pulse-on time, and pulse-off time, while the response is fractal dimension. The usefulness of fractal dimension to characterize a machined surface lies in the fact that it is independent of the resolution of the instrument or length scales. Experiments were carried out based on a rotatable central composite design. A feed-forward ANN architecture trained using the Levenberg-Marquardt (L-M) back-propagation algorithm has been used to model the complex relationship between WEDM process parameters and fractal dimension. After several trials, 4-3-3-1 neural network architecture has been found to predict the fractal dimension with reasonable accuracy, having an overall R-value of 0.97. Furthermore, the genetic algorithm (GA) has been used to predict the optimal combination of machining parameters to achieve a higher fractal dimension. The predicted optimal condition is seen to be in close agreement with experimental results. Scanning electron micrography of the machined surface reveals that the combined ANN-GA method can significantly improve the surface texture produced from WEDM by reducing the formation of re-solidified globules.

Optimization of Wire Electrical Discharge Machining Parameters of Activated Carbon Reinforced Aluminium Composite

2020 ◽  
Vol 979 ◽  
pp. 3-9
Author(s):  
G. Ramanan ◽  
M.Madhu Kiran Reddy ◽  
V. Manishankar
Keyword(s):  
Activated Carbon ◽  
Process Parameters ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Influential Factors ◽  
Wire Electrical Discharge Machining ◽  
Machining Parameters ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process

The quality of machining through process parameters on the responses in wire electrical discharge machining (WEDM) is studied. This paper discusses the optimization of parameters of a process in WEDM machining with the application of the desirability approach on the basis of response surface methodology (RSM). Pulse on time, servo speed rate, discharge current, and pulse off time have been considered as influential factors. The established experimental data of AA7075 aluminium reinforced with 9% of activated carbon composite to analyze the process parameter effects on responses, like material removal rate (MRR) and surface roughness (SR). After machining multiple regression analysis is used to find the interaction among the process parameters is obtained. The optimal parameters were found using the desirability optimization methodologies as 10.43mm3/min and 3.32μm respectively. The performance of the optimization test confirmed that the proposed method in this study effectively improves the performance of the WEDM process.

Multi-Objective Optimization of Wire Electrical Discharge Machining (WEDM) Process Parameters Using Weighted Sum Genetic Algorithm Approach

2016 ◽  
Vol 15 (02) ◽  
pp. 85-100 ◽  
Author(s):  
P. C. Padhi ◽  
S. S. Mahapatra ◽  
S. N. Yadav ◽  
D. K. Tripathy
Keyword(s):  
Genetic Algorithm ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Wire Electrical Discharge Machining ◽  
Weighted Sum ◽  
Multi Objective ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Machining Parameter ◽  
Wedm Process

The present work is aimed at optimizing the cutting rate (CR), surface roughness (Ra) and dimensional deviation (DD) in wire electrical discharge machining (WEDM) of EN-31 steel considering various input parameters such as pulse-on-time, pulse-off-time, wire tension, spark gap set voltage and servo feed. A face centered central composite design of response surface methodology (RSM) has been adopted to develop the empirical model for the responses. It is often desired to obtain a single parameter setting that can decrease Ra and DD and increase CR simultaneously. Since the responses are conflicting in nature, it is difficult to obtain a single combination of cutting parameters satisfying all the objectives in any one solution. The optimum search of the machining parameter values for maximization of CR and minimization of Ra and DD are formulated as a multi-objective, multi-variable, nonlinear optimization problem using genetic algorithm weighted sum method to evaluate the performance.

scholarly journals Experimental investigation of Wire Electrical Discharge Machining (WEDM) Process Parameters on SS304 using Taguchi method

2018 ◽  
Author(s):  
T Vijaya Babu ◽  
B Subbaratnam
Keyword(s):  
Process Parameters ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Wire Electrical Discharge Machining ◽  
Taguchi’S Method ◽  
Input Parameters ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process

WEDM (Wire Electrical discharge machining) is a nonconventional machining processes used in complicated shapes with high accuracy which are not possible with other conventional methods .Stainless steel 304 is used in present experimental work. Experiments are completed using Taguchi’s method with L9 orthogonal array .The aim of this work is to optimize the WEDM process parameters by considering input parameters are pulse on time , pulse off time ,peak current and wire feed and experiments are conducted with help of input parameters at three levels and response output parameters are MRR (Material removal Rate) and Surface Roughness (SR).Setting of parameters using by Taguchi’s method.

An integrated evolutionary approach for modelling and optimization of wire electrical discharge machining

2011 ◽  
Vol 225 (4) ◽  
pp. 549-567
Author(s):  
D Kondayya ◽  
A Gopala Krishna
Keyword(s):  
Electrical Discharge ◽  
Metal Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Evolutionary Approach ◽  
Wire Electrical Discharge Machining ◽  
Machining Parameters ◽  
Machining Performance ◽  
Wedm Process ◽  
Modelling And Optimization

This paper presents an application of an integrated evolutionary approach for modelling and optimization of a wire electrical discharge machining (WEDM) process. The proposed methodology consists of two parts. In the first part, a novel application of genetic programming (GP) is proposed. GP is an evolutionary modelling algorithm which uses principles similar to genetic algorithms to model highly non-linear and complex processes, resulting in accurate and reliable models. Two important aspects of machining performance of WEDM, namely metal removal rate and surface roughness, are modelled based on experimental data using GP in terms of four prominent input variables. The effect of machining parameters on the performance measures is also reported. In the second part, as the chosen machining performances are opposite in nature, the problem under consideration is formulated as a multi-objective optimization problem and solved using an efficient evolutionary optimization algorithm, non-dominated sorting genetic algorithm-II (NSGA-II). The outcome of Pareto optimal solutions is presented. The work presents a fully fledged evolutionary approach for optimization of the process.

Experimental Investigation of Machining Parameters on Surface Roughness in Dry and Wet Wire-Electrical Discharge Machining

2011 ◽  
Vol 264-265 ◽  
pp. 831-836 ◽  
Author(s):  
Suleiman Abdulkareem ◽  
Ahsan Ali Khan ◽  
Zakaria Mohd Zain
Keyword(s):  
Surface Roughness ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Local Heating ◽  
Wire Electrical Discharge Machining ◽  
Machining Parameters ◽  
Good Surface ◽  
Good Surface Finish ◽  
Wedm Process

Wire electrical discharge machining (WEDM) is a thermal process in which the workpiece and the wire (tool) experience an intense local heating in the discharge channel. The high power density results in the erosion of a part of the material from both electrodes by local melting and vaporization. Whilst good surface finish and high material removal rate of the workpiece is a major requirement, the effect of EDM machining factors on these requirements cannot be overlooked. This study investigate the effect of two different machining methods of dry and wet WEDM process as well as the effect of on-time and voltage on the surface roughness of the workpiece. The machining factors used for this study are the pulse current, on-time and voltage. The results of the effect of the two machining methods on the responses are investigated and reported in this paper.

Application of Desirability Analysis for Optimizing the Micro Wire Electrical Discharge Machining (μWEDM) Parameters

2014 ◽  
Vol 592-594 ◽  
pp. 77-81 ◽  
Author(s):  
M. Santhanakumar ◽  
R. Adalarasan ◽  
M. Rajmohan
Keyword(s):  
Process Parameters ◽  
Feed Rate ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Quality Characteristics ◽  
Wire Electrical Discharge Machining ◽  
Machining Parameters ◽  
Desirability Analysis ◽  
Machining Parameter ◽  
Wire Feed

Close tolerance and precision requirements of biomedical components and miniaturization of sensors has given micro wire electrical discharge machining (μWEDM) a substantial amount of research attention. The process parameters like gap voltage, capacitance, wire feed rate and wire tension play an important role in influencing the quality characteristics of the machined parts. The challenge lies in selecting the optimal machining parameter combination to achieve the desired surface finish and metal removal rate in a multi input multi output process like μWEDM. The process parameters were varied at three levels and Taguchi’s L9 orthogonal array was used to design and conduct the experiments. Desirability analysis was applied for predicting the optimal setting of machining parameters and ANOVA results had revealed the significant role of wire feed rate and gap voltage in affecting the quality characteristics of the process

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