Effect of Wire Electric Discharge Machining Process Parameters on Surface Roughness of Monel 400 Alloy

2020 ◽  
pp. 161-172
Author(s):  
M. Mahalingam ◽  
A. Umesh Bala ◽  
R. Varahamoorthi
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Electric Discharge ◽  
Machining Process ◽  
Electric Discharge Machining ◽  
Wire Electric Discharge Machining ◽  
Monel 400

Optimization and Prediction of Machining Responses Using Response Surface Methodology and Adaptive Neural Network by Wire Electric Discharge Machining of Alloy-X

2021 ◽  
Vol 1026 ◽  
pp. 28-38
Author(s):  
I. Vishal Manoj ◽  
S. Narendranath ◽  
Alokesh Pramanik
Keyword(s):  
Neural Network ◽  
Surface Roughness ◽  
Artificial Neural Network ◽  
Response Surface ◽  
Electric Discharge ◽  
Cutting Speed ◽  
Electric Discharge Machining ◽  
Surface Method ◽  
Wire Electric Discharge Machining ◽  
Pulse On Time

Wire electric discharge machining non-contact machining process based on spark erosion technique. It can machine difficult-to-cut materials with excellent precision. In this paper Alloy-X, a nickel-based superalloy was machined at different machining parameters. Input parameters like pulse on time, pulse off time, servo voltage and wire feed were employed for the machining. Response parameters like cutting speed and surface roughness were analyzed from the L25 orthogonal experiments. It was noted that the pulse on time and servo voltage were the most influential parameters. Both cutting speed and surface roughness increased on increase in pulse on time and decrease in servo voltage. Grey relation analysis was performed to get the optimal parametric setting. Response surface method and artificial neural network predictors were used in the prediction of cutting speed and surface roughness. It was found that among the two predictors artificial neural network was accurate than response surface method.

Optimization of electric discharge machining process parameters on AA6351-Al2O3 composites

2020 ◽  
Vol 27 ◽  
pp. 1051-1054
Author(s):  
M. Meignanamoorthy ◽  
M. Ravichandran ◽  
S. Sakthivelu ◽  
S. Dinesh Kumar ◽  
C. Chanakyan ◽  
...  
Keyword(s):  
Process Parameters ◽  
Electric Discharge ◽  
Machining Process ◽  
Electric Discharge Machining

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.

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