Grey relational analysis coupled with principal component analysis for optimisation design of the process parameters in in-feed centreless cylindrical grinding

2009 ◽  
Vol 46 (9-12) ◽  
pp. 983-992 ◽  
Author(s):  
Arshad Noor Siddiquee ◽  
Zahid A. Khan ◽  
Zulquernain Mallick
Keyword(s):  
Principal Component Analysis ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Cylindrical Grinding ◽  
Relational Analysis ◽  
Grey Relational

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.

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.

AUTOMOTIVE EXTERIOR NOISE OPTIMIZATION USING GREY RELATIONAL ANALYSIS COUPLED WITH PRINCIPAL COMPONENT ANALYSIS

2013 ◽  
Vol 12 (03) ◽  
pp. 1350017 ◽  
Author(s):  
SHUMING CHEN ◽  
DENGFENG WANG ◽  
BO LIU
Keyword(s):  
Principal Component Analysis ◽  
Grey Relational Analysis ◽  
Optimization Design ◽  
Principal Component ◽  
Aluminum Foil ◽  
Component Analysis ◽  
Optimal Combination ◽  
Relational Analysis ◽  
Noise Optimization ◽  
Grey Relational

This paper investigates optimization design of the thickness of the sound package performed on a passenger automobile. The major characteristics indexes for performance selected to evaluate the processes are the SPL of the exterior noise and the weight of the sound package, and the corresponding parameters of the sound package are the thickness of the glass wool with aluminum foil for the first layer, the thickness of the glass fiber for the second layer, and the thickness of the PE foam for the third layer. In this paper, the process is fundamentally with multiple performances, thus, the grey relational analysis that utilizes grey relational grade as performance index is especially employed to determine the optimal combination of the thickness of the different layers for the designed sound package. Additionally, in order to evaluate the weighting values corresponding to various performance characteristics, the principal component analysis is used to show their relative importance properly and objectively. The results of the confirmation experiments uncover that grey relational analysis coupled with principal analysis methods can successfully be applied to find the optimal combination of the thickness for each layer of the sound package material. Therefore, the presented method can be an effective tool to improve the vehicle exterior noise and lower the weight of the sound package. In addition, it will also be helpful for other applications in the automotive industry, such as the First Automobile Works in China, Changan Automobile in China, etc.

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