Machining Parameters Optimization for WEDM Based on Grey Relational Analysis

2013 ◽  
Vol 401-403 ◽  
pp. 1385-1392 ◽  
Author(s):  
Shi Ping Zhang ◽  
Yi Chao Ding ◽  
Wen Li Zhang
Keyword(s):  
Grey Relational Analysis ◽  
Parameters Optimization ◽  
Performance Characteristics ◽  
Pulse Interval ◽  
Machining Parameters ◽  
Machining Time ◽  
Relational Analysis ◽  
Machining Parameters Optimization ◽  
Grey Relational ◽  
Wedm Process

This paper presents an effective approach for the optimization of the wire electric discharge machining (WEDM) process with multiple performance characteristics based on the grey relational analysis. Twenty five experimental runs based on the Taguchi method of orthogonal arrays were performed to determine the best factor level condition. The response table and response graph for each level of the machining parameters were obtained from the grey relational grade. In this study, the machining parameters such as the machining voltage, the number of power amplifier tube, pulse width and pulse interval are optimized with consideration of multiple-performance characteristics, such as machining time and surface roughness. It is clearly shown that the above performance characteristics in WEDM process can be improved effectively through this approach. keywords: WEDM; grey relational analysis; parameter optimization; performance characteristics

Multiple Performance Optimization in WEDM Parameters Using Grey Relational Analysis

2015 ◽  
Vol 813-814 ◽  
pp. 357-361
Author(s):  
T. Rajmohan ◽  
Gopi Krishna ◽  
Ankit Kumar Singh ◽  
A.P.V. Swamy Naidu
Keyword(s):  
Grey Relational Analysis ◽  
Performance Characteristics ◽  
304L Stainless Steel ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Grey Relational ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Off Time

In this investigation, a new approach is based on Grey Relational Analysis and Taguchi method to optimize the machining parameters with multi performance characteristics in WEDM of 304L SS. Experiments are conducted using Taguchi Quality Concept, L9,3-level orthogonal array was chosen for experiments .The WEDM parameters namely pulse-on time (TON), pulse-off time (TOFF), and wire feed (WF) on material removal rate (MRR) .The Grey Relational Analysis with multiple performance characteristics indicates that the pulse-on time (TON), pulse-off time (TOFF) are the most significant factors . The optimum machining parameters have been identified by Grey relational analysis and significant contribution of parameters can be determined by analysis of variance (ANOVA). The confirmation test is also conducted to validate the test result. The results from this study will be useful for manufacturing engineers to select appropriate WEDM process parameters to machine 304L Stainless Steel.

Optimization of Multiple Performances for EDM in Gas Media Using Grey Relational Analysis

2014 ◽  
Vol 620 ◽  
pp. 173-178
Author(s):  
Fang Pin Chuang ◽  
Yan Cherng Lin ◽  
Han Ming Chow ◽  
A. Cheng Wang
Keyword(s):  
Grey Relational Analysis ◽  
Electrical Discharge Machining ◽  
Design Method ◽  
Removal Rate ◽  
Performance Characteristics ◽  
Electrode Wear ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Grey Relational ◽  
Machining Parameter

The aim of this investigation is to optimize the multiple performance characteristics of electrical discharge machining (EDM) for SKD 61 tool steel in gas media using grey relational analysis. The three most important machining characteristics namely material removal rate (MRR), electrode wear rate (EWR), and surface roughness (SR) were considered as the measures of the performance characteristics. A series of experiments were conducted according to an L18 orthogonal array based on the Taguchi experimental design method. The observed data obtained from the experiments were evaluated to determine the optimization of machining parameters correlated with multiple performance characteristics through grey relational analysis. Moreover, analysis of variance (ANOVA) was conducted to explore the significant machining parameters crucially affecting the multiple performance characteristics. In addition, the optimal combination levels of machining parameters were also determined from the response graph of grey relational grades for each level of machining parameter.

Multiple Performance Optimization in the Wire EDM Process of SKD61 Tool Steel Using Taguchi Grey Relational Analysis and Fuzzy Logic

2014 ◽  
Vol 493 ◽  
pp. 523-528 ◽  
Author(s):  
Nuraini Lusi ◽  
Bobby Oedy Pramoedyo Soepangkat ◽  
Bambang Pramujati ◽  
H.C. Kis Agustin
Keyword(s):  
Fuzzy Logic ◽  
Taguchi Method ◽  
Tool Steel ◽  
Grey Relational Analysis ◽  
Performance Characteristics ◽  
Relational Analysis ◽  
The Wire ◽  
Grey Relational ◽  
Wedm Process ◽  
Different Levels

This paper propose the optimization of the wire electrical discharge machining (WEDM) process of SKD61 tool steel (AISI H13). The use of the Taguchi method combined with grey relational analysis and fuzzy logic has been applied for optimization of multiple quality characteristics. The WEDM machining parameters (arc on time, on time, open voltage, off time and servo voltage) were optimized with considerations of multiple performance characteristics, i.e., MRR, SR and kerf. Arc on time was set at two different levels while the other four were set at three different levels. Based on Taguchi method, an L18mixed-orthogonal array was chosen for the experiments. Experimental results have shown that machining performance characteristics of WEDM process can be improved effectively through the combination of Taguchi method and grey-fuzzy logic.

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.

Determination of Optimum Parameters for Multi-Performance Characteristic in Turning of Al 6061-6% ZrB2 in-situ Metal Matrix Composite Using Grey Relational Analysis

2012 ◽  
Vol 2 (1) ◽  
pp. 11-29 ◽  
Author(s):  
A. Mahamani ◽  
N. Muthukrishnan ◽  
V. Anandakrishnan
Keyword(s):  
Metal Matrix Composite ◽  
Matrix Composite ◽  
Grey Relational Analysis ◽  
Feed Rate ◽  
Metal Matrix ◽  
Performance Characteristics ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Grey Relational

In-situ aluminum matrix composite is the innovation of high performance material technology and it has superior interfacial integrity and thermodynamic stability between the matrix and reinforcement. During synthesis, the ZrB2 particle is formed by exothermic reaction within the aluminum melt. As a result, small, fine and oxide free reinforcements are formed. Excessive temperature released from in-situ chemical reaction will facilitate the homogeneous distribution of particles in entire shape of the composites. Making the engineering components from this composite material require machining operations. Therefore, addressing the machinability issues of the composite is very important. This paper proposes an approach to optimize the machining parameters in turning of Al 6061-6% ZrB2 in-situ Metal Matrix Composite (MMC) with multiple performance characteristics by using grey relational analysis. The effect of in-situ ZrB2 reinforcement particles on machinability behavior need to be studied. The machining parameters, namely cutting speed, feed rate and depth of cut are optimized with considerations of multiple performance characteristics including surface roughness, tool wear and cutting force. It is concluded that the feed rate has the strongest effect. The confirmation experiment indicates that there is a good agreement between the estimated value and experimental value of the Grey relational grade.

Optimization of Thermal Friction Drilling Using Grey Relational Analysis

2010 ◽  
Vol 154-155 ◽  
pp. 1726-1738
Author(s):  
Wei Liang Ku ◽  
Han Ming Chow ◽  
Yao Jang Lin ◽  
Der An Wang ◽  
Lieh Dai Yang
Keyword(s):  
Stainless Steel ◽  
Grey Relational Analysis ◽  
Friction Angle ◽  
Performance Characteristics ◽  
304 Stainless Steel ◽  
Machining Parameters ◽  
Beneficial Effects ◽  
Relational Analysis ◽  
Friction Drilling ◽  
Grey Relational

The main purpose of this research is to study the optimal machining parameters for a novel process of thermal friction drilling on SUS 304 stainless steel. The experiments were conducted according to an L9 orthogonal array based on Taguchi experimental designs method, and the multiple performance characteristics correlated with surface roughness (SR) and bush length (BL) was investigated by grey relational analysis systematically and comprehensively. Moreover, the significant machining parameters that most intensively affected the multiple performance characteristic and the optimal combination levels of machining parameters associated with the thermal friction drilling on SUS 304 stainless steel were determined through the analysis of variance (ANOVA) and the response graph of grey relational grade. The main machining parameters of the thermal friction drilling such as friction angle, friction contact area ratio, feed rate, and drilling speed were selected to evaluate the effects on SR and BL. The experimental results show that the thermal friction drilling revealed beneficial effects on SR and BL for drilling processes. Moreover, the optimal machining parameters for multiple performance characteristics associated with SR and BL were attained. The developed thermal friction drilling avoids serious tool wears, enhances the surface quality of the machined hole, and prolongs the tool life significantly.

Empirical Modeling of Turning Parameters Using Grey Relational Analysis

2011 ◽  
Vol 110-116 ◽  
pp. 2596-2603 ◽  
Author(s):  
L.B. Abhang ◽  
M. Hameedullah
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Grey Relational Analysis ◽  
Performance Characteristics ◽  
Empirical Modeling ◽  
Interface Temperature ◽  
Machining Parameters ◽  
Turning Process ◽  
Relational Analysis ◽  
Grey Relational

-Optimization of multi-criteria problem is a great need of producers to produce precision parts with low costs. Many methods such as Taguchi and Response surface methodology have been employed for optimization of turning operation. However there are few researches involve the optimization of multi-response problem in turning process. The attempt of this paper is to optimize multi-performance characteristics of turning process using grey relational analysis based on factorial design with response surface methodology. The response table and response graph for each level of the machining parameters is obtained and optimal levels of turning parameters including cutting velocity, feed rate, depth of cut, tool nose radius and concentration of lubricants are found. The multiple performance characteristics including tool wear rate, cutting force and chip-tool interface temperature is considered.

Sign in / Sign up

Export Citation Format

Share Document