Analysis of process parameters in Wire Electric Discharge Machining of gear cutting process using Entropy Grey Relational Analysis approach

2017 ◽  
Vol 12 (4) ◽  
pp. 1
Author(s):  
Kasinath Das Mohapatra N.A.
Keyword(s):  
Process Parameters ◽  
Electric Discharge ◽  
Grey Relational Analysis ◽  
Cutting Process ◽  
Analysis Approach ◽  
Electric Discharge Machining ◽  
Relational Analysis ◽  
Gear Cutting ◽  
Wire Electric Discharge Machining ◽  
Grey Relational

Multi-objective optimization of micro wire electric discharge machining parameters using grey relational analysis with Taguchi method

2011 ◽  
Vol 225 (7) ◽  
pp. 1742-1753 ◽  
Author(s):  
K P Somashekhar ◽  
J Mathew ◽  
N Ramachandran
Keyword(s):  
Analysis Of Variance ◽  
Process Parameters ◽  
Electric Discharge ◽  
Grey Relational Analysis ◽  
Performance Characteristics ◽  
Electric Discharge Machining ◽  
Relational Analysis ◽  
Wire Electric Discharge Machining ◽  
Grey Relational ◽  
Wedm Process

Micro wire electric discharge machining (µ-WEDM) is an evolution of conventional wire EDM used for fabricating three-dimensional complex microcomponents, microstructures, and intricate profiles effectively with high-precision capabilities. Being a complex process, it is very difficult to determine optimal parameters for obtaining higher material removal rate (MRR) with minimum overcut (OC), and surface roughness (SR) is a challenging task in µ-WEDM for improving performance characteristics. In this study, a new approach for the optimization of the µ-WEDM process with multiple performance characteristics based on the statistical-based analysis of variance (ANOVA) and grey relational analysis (GRA) is attempted. Analysis of variance was used to study the significance of process parameters on grey relational grade (GRG) which showed capacitance to be the most significant factor. A GRG obtained from the GRA is used to optimize the µ-WEDM process. Optimum process parameters are determined by the GRG as the overall performance index. The process parameters, namely gap voltage, capacitance, and feed rate are optimized by considering multiple performance characteristics including MRR, OC, and SR. To validate the study, confirmation experiment has been carried out at optimal set of parameters, and predicted results have been found to be in good agreement with experimental findings. This approach showed improved machining performance in the µ-WEDM process.

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.

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.

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