Use of Taguchi Method and Grey Relational Analysis for Optimizing a Ram Electrical Discharge Machining Process

2015 ◽  
Vol 760 ◽  
pp. 533-538 ◽  
Author(s):  
Laurenţiu Slătineanu ◽  
Oana Dodun ◽  
Margareta Coteaţă ◽  
Ciprian Mircescu ◽  
Irina Beşliu ◽  
...  
Keyword(s):  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Machining Process ◽  
Electrode Wear ◽  
Relational Analysis ◽  
Output Factors ◽  
Grey Relational ◽  
Pulse On Time

There are various factors able to exert influence on the results of electrical discharge machining process. If there are many output factors of the machining process, one can formulate a problem of multicriterial optimization. It is necessary to find adequate values for the input factors so that the output factors have optimized values. The paper presents the results of a research aiming to optimize the material removal rate and the tool electrode wear rate, in the case of ram electrical discharge machining process. As input factors, one used the pulse on time, pulse off time and average peak current intensity. The Taguchi method was applied, in association with the Grey relational analysis. In this way, combinations of values corresponding to the input factors were determined, in order to obtain optimal results for the process output factors.

Optimization of the Wire Electrical Discharge Machining Process Using Grey Relational Analysis and Taguchi Method

2015 ◽  
Vol 651-653 ◽  
pp. 738-743
Author(s):  
Oana Dodun ◽  
Vasile Merticaru ◽  
Laurenţiu Slatineanu ◽  
Margareta Coteaţă
Keyword(s):  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Machining Process ◽  
Tool Electrode ◽  
Wire Electrical Discharge Machining ◽  
Relational Analysis ◽  
The Wire ◽  
Grey Relational

The wire electrical discharge machining is a machining method able to allow detaching parts from plates type workpieces as a consequence of electrical discharges developed between workpiece and wire tool electrode found in a motion along its axis; there is also a work motion along the contour to be obtained. There are many factors able to exert influence on the sizes of parameters of technological interest. On the other hand, there are various methods that can be used in order to establish the optimal combination of the input factors, so that obtaining of machining best results is possible. When there are many process output factors, a problem of multiobjective optimization could be formulated. The Grey relational analysis method and the Taguchi method could be applied in order to optimize the wire electrical discharge machining process, when various criteria having distinct significances are considered. An experimental research was designed and developed in order to optimize the wire electrical discharge cutting of parts made of an alloyed steel, by considering six input factors: test piece thickness, pulse on time, pulse off time, wire axial tensile, current intensity and travelling wire electrode speed. As output parameters, one took into consideration surface roughness, wire tool electrode massic wear, cutting speed along the contour to be obtained. 16 experiments were developed in accordance with the requirements specific to a Taguchi table L16. The results of experiments were processed by means of Grey relational analysis method and Taguchi method.

Optimization of EDM Parameters in Machining AISI D3 Tool Steel by Grey Relational Analysis

2013 ◽  
Vol 330 ◽  
pp. 747-753
Author(s):  
Othman Belgassim ◽  
Abdurahman Abu-Saada
Keyword(s):  
Taguchi Method ◽  
Tool Steel ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Pulse Current ◽  
Machining Process ◽  
Relational Analysis ◽  
Grey Relational ◽  
Pulse On Time ◽  
D3 Tool Steel

This study presents optimization of multiple performance characteristics [material removal rate (MRR), surface roughness (Ra), and overcut (OC)] of hardened AISI D3 tool steel in electrical discharge machining (EDM) using Taguchi method and Grey relational analysis. Machining process parameters selected were pulse current Ip, pulse-on time Ton, pulse-off time Toff and gap voltage Vg . Based on ANOVA, pulse current is found to be the most significant factor affecting EDM process. Optimized process parameters simultaneously leading to a higher MRR, lower Ra, and lower OC are then verified through a confirmation experiment. Validation experiment shows an improved MRR, Ra and OC when Taguchi method and grey relational analysis were used.

Optimization of Wire Cut Electrical Discharge Machining of Inconel 800 Using Grey Relational Analysis

2012 ◽  
Vol 576 ◽  
pp. 552-555 ◽  
Author(s):  
M. Durairaj ◽  
S. Gowri ◽  
M.H. Gauthamkumar ◽  
M. Ashok Kumar ◽  
R. Aishwarya
Keyword(s):  
Surface Roughness ◽  
Grey Relational Analysis ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Kerf Width ◽  
Performance Criteria ◽  
Relational Analysis ◽  
Grey Relational ◽  
Pulse On Time ◽  
Inconel 800

Wire Electrical Discharge Machining is one of the important non-traditional machining processes, which is used for machining difficult to machine materials and intricate profiles. In this present study, machining is done using Wire-Cut EDM and experimentation is planned according to Taguchi’s design of experiments [2]. Each experiment has been performed under different cutting conditions of gap voltage, pulse ON time, and pulse OFF time and Wire feed. Inconel 800 was selected as a work material and Brass wire of 0.25mm diameter as the tool to conduct the experiments. From experimental results, the surface roughness and Kerf Width was determined for each machining performance criteria. Grey Relational Analysis [1] is used for optimization of Surface Roughness and Kerf width.

Analysis and Optimization of Wire EDM Process of Titanium by Using GRA Methodology

2019 ◽  
Vol 969 ◽  
pp. 678-684 ◽  
Author(s):  
Sarat Kumar Sahoo ◽  
A. Bara ◽  
A.K. Sahu ◽  
S.S. Mahapatra ◽  
D.S. Kiran ◽  
...  
Keyword(s):  
Grey Relational Analysis ◽  
Orthogonal Array ◽  
Electrical Discharge Machining ◽  
Input Parameter ◽  
Optimization Technique ◽  
Research Work ◽  
Cutting Speed ◽  
Machining Process ◽  
Relational Analysis ◽  
Grey Relational

In this research work, an efficient optimization technique, grey relational analysis (GRA) has been used to for optimization of wire electrical discharge machining process of Titanium (grade 2) by considering multiple output parameters. This technique combines Taguchi’s orthogonal array with grey relational analysis for the design of the experiment. The central focus of this research is to achieve improved Kerf width, surface roughness and cutting speed. GRA method is implemented to decide the best input parameter that optimizes the output parameters. This study has been conducted by applying Taguchi’s L9 orthogonal array. Each experiment has been conducted in altered conditions of input variables. For the optimization of multiple criteria, GRA is suggested as a suitable technique for the optimization of complex interrelationships between multi-performance characteristics. By analysis of variance (ANOVA) it is found that the percentage of contribution of peak current on overall performance is maximum i.e.73.1%.

scholarly journals Optimization of Process Parameters of Wire Cut Electrical Discharge Machining on Titanium Grade-5 Material using Design of Experiments

2019 ◽  
Vol 8 (11) ◽  
pp. 3937-3946 ◽  
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Orthogonal Array ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Relational Theory ◽  
Relational Analysis ◽  
Grade 5 ◽  
Titanium Grade ◽  
Grey Relational

In this paper, a compelling methodology, Taguchi grey relational analysis, was employed to the test results of wire-cut electrical discharge machining on Titanium Grade - 5 material with the consideration of multiple performance characteristics of the output response variables. The methodology merges the orthogonal array design of experiment with grey relational analysis. The primary target of this examination is to accomplish the maximization of material removal rate, minimization of both Surface roughness and kerf width. Grey relational theory is implemented to assess the optimal process parameters that improve the response measures. The test was finished by utilizing Taguchi's orthogonal array L18. Each test has been performed under various states of input parameters. The response table and grey relational grade for each level of the machining parameters have been established. From 18 tests, the best mix of parameters was identified. The results of test verify that the suggested technique in this investigation adequately develops the machining performance of Wire cut EDM process.

Multi-Objective Optimization of EDM Process Parameters using Taguchi Method, Principal Component Analysis and Grey Relational Analysis

2014 ◽  
Vol 4 (2) ◽  
pp. 29-46 ◽  
Author(s):  
U. Shrinivas Balraj ◽  
A. Gopala Krishna
Keyword(s):  
Principal Component Analysis ◽  
Taguchi Method ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Electrical Discharge Machining ◽  
Principal Component ◽  
Component Analysis ◽  
Optimum Process ◽  
Relational Analysis ◽  
Grey Relational

This paper investigates multi-objective optimization of electrical discharge machining process parameters using a new combination of Taguchi method and principal component analysis based grey relational analysis. In this study, three conflicting performance characteristics related to surface integrity such as surface roughness, white layer thickness and surface crack density are considered in electrical discharge machining of RENE80 nickel super alloy. The process parameters considered are peak current, pulse on time and pulse off time. The experiments are conducted based on Taguchi method and these experimental results are used in grey relational analysis and weights of the corresponding performance characteristics are determined by principal component analysis. The weighted grey relational grade is used as a performance index to determine optimum process parameters and results of the confirmation experiments indicate that the combined approach is effective in determining optimum process parameters.

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