scholarly journals Multiobjective Optimization of ELID Grinding Process Using Grey Relational Analysis Coupled with Principal Component Analysis

2014 ◽  
Vol 6 ◽  
pp. 878510 ◽  
Author(s):  
S. Prabhu ◽  
B. K. Vinayagam
Keyword(s):  
Principal Component Analysis ◽  
Multiobjective Optimization ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Principal Component ◽  
Grinding Wheel ◽  
Grinding Process ◽  
Elid Grinding ◽  
Relational Analysis ◽  
Grey Relational

Carbon nanotube (CNT) mixed grinding wheel has been used in the electrolytic in-process dressing (ELID) grinding process to analyze the surface characteristics of AISI D2 Tool steel material. CNT grinding wheel is having an excellent thermal conductivity and good mechanical property which is used to improve the surface finish of the work piece. The multiobjective optimization of grey relational analysis coupled with principal component analysis has been used to optimize the process parameters of ELID grinding process. Based on the Taguchi design of experiments, an L9 orthogonal array table was chosen for the experiments. The confirmation experiment verifies the proposed that grey-based Taguchi method has the ability to find out the optimal process parameters with multiple quality characteristics of surface roughness and metal removal rate. Analysis of variance (ANOVA) has been used to verify and validate the model. Empirical model for the prediction of output parameters has been developed using regression analysis and the results were compared for with and without using CNT grinding wheel in ELID grinding 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.

Assessment of Water Quality Using Grey Relational Analysis and Principal Component Analysis

2011 ◽  
Vol 255-260 ◽  
pp. 2829-2835 ◽  
Author(s):  
Yong Qian Cheng ◽  
Hong Mei Ma ◽  
Qian Wu Song ◽  
Yue Zhang
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
Grey Relational Analysis ◽  
Principal Component ◽  
Water Quality Assessment ◽  
Component Analysis ◽  
Comprehensive Assessment ◽  
Relative Importance ◽  
Relational Analysis ◽  
Grey Relational

This paper investigates the comprehensive assessment of water quality, which is generally a multi-attribute assessment problem. In this context, the grey relational analysis is adopted to settle the no uniformity problem of water quality attributes. The principal component analysis is applied to calculate the weighting values corresponding to various attributes of water quality so that their relative importance can be properly and objectively described. Results of study reveal that grey relational analysis coupled with principal component analysis can effectively solve the multi-attribute water quality assessment. The method is universal and can be a useful tool to improve the comprehensive assessment of water quality.

Friction Stir Welding of Aluminum and Magnesium Alloys—Experimental Investigation and Optimization Using Hybrid Grey Relational Analysis and Principal Component Analysis

2018 ◽  
Vol 15 (2) ◽  
pp. 509-520
Author(s):  
D. Raguraman ◽  
D. Muruganandam ◽  
L. A. Kumaraswamidhas
Keyword(s):  
Principal Component Analysis ◽  
Tensile Strength ◽  
Friction Stir Welding ◽  
Grey Relational Analysis ◽  
Rotational Speed ◽  
Axial Load ◽  
Principal Component ◽  
Friction Stir ◽  
Relational Analysis ◽  
Grey Relational

Friction stir welding of dissimilar materials is investigated experimentally in this work and optimization is performed by applying a hybrid Taguchi-Grey relational analysis-Principal component analysis to maximize the tensile strength and hardness of the weld bead. Two dissimilar metals AA6061 and AZ61 is friction stir welded and considered for the experimentation. Experimental matrix is designed using Taguchi's Design of Experiment (DOE). Optimum inputs rotational speed, axial load and transverse speed is obtained by applying the hybrid optimization technique. Statistical analysis of Multi Response Performance Index (MRPI) through Analysis of Variance (ANOVA) shows that axial load is the significant parameter that contributes by 75.67% towards MRPI, followed by transverse speed and rotational speed. Confirmation experiment with optimum condition produces a better friction stir welding joint with higher tensile strength and hardness.

Optimization of EDM Process with Magnetic Field Using Grey Relational Analysis Coupled with Principal Component Analysis

2015 ◽  
Vol 799-800 ◽  
pp. 388-392 ◽  
Author(s):  
G. Anand ◽  
M. Manzoor Hussian ◽  
S. Satyanarayana
Keyword(s):  
Principal Component Analysis ◽  
Grey Relational Analysis ◽  
Metal Removal ◽  
Removal Rate ◽  
Principal Component ◽  
Component Analysis ◽  
Optimal Combination ◽  
Relational Analysis ◽  
Grey Relational ◽  
Edm Process

This paper investigates optimized design of Electro Discharge Machining process parameters on HCHCr i.e. DIN 17350-1.2080 Die steel. This process is one of the most widely applied non-traditional machining processes. To determine the optimal EDM conditions in several industrial fields. Taguchi method has been utilized to optimize only a single performance characteristic. To overcome this limitation, the Grey Relational Analysis theory has been used to determine grey relational grade as performance index to determine the optimal combination of the parameters such as peak current (I), pulse duration (Ton), voltage (V) to evaluate multiple performance characteristic such as metal removal rate and surface roughness simultaneously. Moreover, the Principal Component Analysis is applied to evaluate the weighting values corresponding to metal removal rate and surface roughness performance characteristics so that their relative importance can be properly defined. The analysis reveal that Grey Relational Analysis coupled with Principal Component Analysis can effectively be used to obtain the optimal combination of EDM process parameters. The obtained optimal machining conditions were Peak current at 15A, pulse on time at 250μs, Voltage at 85V. It is also observed that magnetic field in spark zone have improved metal removed rate and surface finish.

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