ANFIS for predicting surface roughness in wire electric discharge machining of aerospace material

2020 ◽  
Vol 28 ◽  
pp. 2579-2584
Author(s):  
Thakur Singh ◽  
Pawan Kumar ◽  
J.P. Misra
Keyword(s):  
Surface Roughness ◽  
Electric Discharge ◽  
Electric Discharge Machining ◽  
Aerospace Material ◽  
Wire Electric Discharge Machining

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 Material Removal Rate and Surface Roughness for Wire Electric Discharge Machining of AA7075 Composites using Grey Relational Analysis

2018 ◽  
Vol 9 (5) ◽  
Author(s):  
G. Ramanan ◽  
J. Edwin Raja Dhas ◽  
M. Ramachandran
Keyword(s):  
Surface Roughness ◽  
Electric Discharge ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Electric Discharge Machining ◽  
Relational Analysis ◽  
Wire Electric Discharge Machining ◽  
Grey Relational ◽  
Pulse On Time ◽  
The Impact

In automobile industries, usage of unconventional machining is increased due to their precision and accuracy. This research work is planned to upgrade the Wire Electric Discharge Machining (WEDM) process parameters by considering the impact of discharge current, pulse on time, pulse off time and servo speed rate. Tests have been led with these parameters for the measurement of metal removal rate and surface roughness for each of the trial run. This information has been used to fit a quadratic numerical model. Predicted information has been used as a graphical representation for demonstrating the impact of the parameters on chose reactions. Predicted information given by the models has been utilized as a part of an ideal parametric mix to accomplish the unrealistic yield of the procedure. Response surface method with grey relational analysis has been utilized for enhancement. The ideal value has been checked to the predicted value from the confirmation tests.

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