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.

scholarly journals Tribological Performance Optimization of Al-7.5% SiCp Composites Using the Taguchi Method and Grey Relational Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Shouvik Ghosh ◽  
Prasanta Sahoo ◽  
Goutam Sutradhar
Keyword(s):  
Taguchi Method ◽  
Metal Matrix Composite ◽  
Matrix Composite ◽  
Grey Relational Analysis ◽  
Metal Matrix ◽  
Friction And Wear ◽  
Tribological Performance ◽  
Relational Analysis ◽  
Test Parameters ◽  
Grey Relational

The present study considers an experimental study of tribological performance of Al-7.5% SiCp metal matrix composite and optimization of tribological testing parameters based on the Taguchi method coupled with grey relational analysis. A grey relational grade obtained from grey relational analysis is used as a performance index to study the behaviour of Al-7.5% SiCp MMC with respect to friction and wear characteristics. The tribological experiments are carried out by utilizing the combinations of tribological test parameters based on the L27 Taguchi orthogonal design with three test parameters, namely, load, speed, and time. The material Al-7.5% SiCp metal matrix composite is developed by reinforcing LM6 aluminium alloy with 7.5% (by weight) SiC particle of 400 mesh size (~37 μm) in an electric melting furnace. It is observed that sliding time has a significant contribution in controlling the friction and wear behaviour of Al-7.5% SiCp MMC. Furthermore, all the interactions between the parameters have significant influence on tribological performance. A confirmation test is also carried out to verify the accuracy of the results obtained through the optimization problem. In addition, a scanning electron microscopy (SEM) test is performed on the wear tracks to study the wear mechanism.

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.

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

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