Multi-objective optimization of powder mixed electric discharge machining parameters for fabrication of biocompatible layer on β-Ti alloy using NSGA-II coupled with Taguchi based response surface methodology

2016 ◽  
Vol 30 (9) ◽  
pp. 4195-4204 ◽  
Author(s):  
Chander Prakash ◽  
H. K. Kansal ◽  
B. S. Pabla ◽  
Sanjeev Puri
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Electric Discharge ◽  
Machining Parameters ◽  
Ti Alloy ◽  
Multi Objective Optimization ◽  
Electric Discharge Machining ◽  
Nsga Ii ◽  
Multi Objective

Modelling and multi-response optimization of wire electric discharge machining parameters using response surface methodology and grey–fuzzy algorithm

2015 ◽  
Vol 231 (10) ◽  
pp. 1760-1774 ◽  
Author(s):  
Bikash Choudhuri ◽  
Ruma Sen ◽  
Subrata Kumar Ghosh ◽  
Subhash Chandra Saha
Keyword(s):  
Stainless Steel ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Electric Discharge ◽  
Machining Parameters ◽  
Electric Discharge Machining ◽  
Wire Electric Discharge Machining ◽  
Grey Relational ◽  
Stainless Steel 316

Wire electric discharge machining is a non-conventional machining wherein the quality and cost of machining are influenced by the process parameters. This investigation focuses on finding the optimal level of process parameters, which is for better surface finish, material removal rate and lower wire consumption for machining stainless steel-316 using the grey–fuzzy algorithm. Grey relational technique is applied to find the grey coefficient of each performance, and fuzzy evaluates the multiple performance characteristics index according to the grey relational coefficient of each response. Response surface methodology and the analysis of variance were used for modelling and analysis of responses to predict and find the influence of machining parameters and their proportion of contribution on the individual and overall responses. The measured values from confirmation experiments were compared with the predicted values, which indicate that the proposed models can be effectively used to predict the responses in the wire electrical discharge machining of AISI stainless steel-316. It is found that servo gap set voltage is the most influential factor for this particular steel followed by pulse off time, pulse on time and wire feed rate.

Study on Wire Electric Discharge Machining Based on Response Surface Methodology and Genetic Algorithm

2012 ◽  
Vol 622-623 ◽  
pp. 1280-1284 ◽  
Author(s):  
Pragya Shandilya ◽  
P.K. Jain ◽  
N.K. Jain
Keyword(s):  
Genetic Algorithm ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Electric Discharge ◽  
Metal Matrix ◽  
Machining Parameters ◽  
Electric Discharge Machining ◽  
Response Parameter ◽  
Wire Electric Discharge Machining

Wire electric discharge machining (WEDM) is one of the most popular non-conventional machining processes for machining metal matrix composites (MMCs). The present research work deals the parametric optimization of the input process parameters for response parameter during WEDM of SiCp/6061 Al metal matrix composite (MMC). Response surface methodology (RSM) and genetic algorithm (GA) integrated with each other to optimize the process parameters. RSM has been used to plan and analyze the experiments. Four WEDM parameters namely servo voltage, pulse-on time, pulse-off time and wire feed rate were varied to study their effect on the quality of cut in SiCp/6061 Al MMC using cutting width (kerf) as response parameter. The relationship between kerf and machining parameters has been developed by using RSM. The mathematical model thus than developed was then employed on GA to optimized the process parameters.

scholarly journals Modeling and Analysis of Machining Parameters and Responses of Wirecut Electric Discharge Machining of Al2124/SiCp using Response Surface Methodology and Soft Computing Techniques

2019 ◽  
Vol 8 (2) ◽  
pp. 5429-5434
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Soft Computing ◽  
Electric Discharge ◽  
Optimization Techniques ◽  
Machining Parameters ◽  
Electric Discharge Machining ◽  
Soft Computing Techniques ◽  
Input Parameters ◽  
Single Objective

In this work, Wirecut Electric Discharge Machining (WEDM) of Al 2124/ SiCp metal matrix composite material is studied to evaluate the influence of input parameters on response characteristics namely, kerf, Material Removal Rate (MMR), Surface Roughness (SR), Recast Layer Thickness (RCT), and Surface Crack Density (SCD). Central composite design, a technique from design of experiments is used to conduct 31 experiments. The input parameters selected for estimation of machinability are pulse on time (Ton), pulse off time (Toff), current (IP), and Servo Voltage (SV). Analysis of variance (ANOVA) is carried out to know the effect of influence parameters on responses. The regression models are developed in Response Surface Methodology (RSM)and are used in soft computing techniques as input equations for optimizing the single and multi-response optimization of response parameters. Desirability approach is used in single and multi-objective optimization of response parameters. Single objective optimization is carried out by RSM, the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Firefly Algorithms (FA). Confirmation experiments are conducted on the adequacy of the mathematical models developed in RSM and it shows good agreement between experimental and predicted values. The variation of predicted responses from different optimization techniques for single objective optimization is found to be less than 1%. From the results it is also observed that for single objective optimization all evolutionary algorithms are found to be suitable for WEDM

Optimization of electric discharge machining parameters on surface roughness for Al/ZrO2 composite through response surface methodology

2020 ◽  
Vol 27 ◽  
pp. 1006-1012
Author(s):  
S.V. Alagarsamy ◽  
M. Ravichandran ◽  
S. Sakthivelu ◽  
S. Dinesh Kumar ◽  
C. Chanakyan ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Electric Discharge ◽  
Machining Parameters ◽  
Electric Discharge Machining

Multi-Objective Optimization of Die-Sinking Electric Discharge Machining

2011 ◽  
Vol 110-116 ◽  
pp. 1817-1824 ◽  
Author(s):  
Pushpendra S. Bharti ◽  
S. Maheshwari ◽  
C. Sharma
Keyword(s):  
Electric Discharge ◽  
Removal Rate ◽  
High Surface ◽  
Optimization Techniques ◽  
Work Piece ◽  
Tool Electrode ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Electric Discharge Machining ◽  
Multi Objective

— Parametric optimization of electric discharge machining (EDM) is a challenging task. Many researchers have employed different multi-objective optimization techniques for the same. This work employs multi-response signal-to-noise (MRSN) technique to find the optimum factor/level combination of input parameters. Experiments have been conducted on die-sinking EDM by taking heat treated D2 steel as work piece and copper as tool electrode. Experiments have been designed as per Taguchi’s L36 orthogonal array. Two cases v.i.z. high cutting efficiency and high surface finish have been taken. Analysis of variance (ANOVA) is employed to indicate the level of significance of machining parameters in both the cases. Finally, results have been verified experimentally and a significant improvement in material removal rate and surface roughness is observed.

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