scholarly journals Optimization of Scanning Parameters in Coordinate Metrology Using Grey Relational Analysis and Fuzzy Logic

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Syed Hammad Mian ◽  
Usama Umer ◽  
Hisham Alkhalefah
Keyword(s):  
Fuzzy Logic ◽  
Data Acquisition ◽  
Grey Relational Analysis ◽  
Principal Component ◽  
Coordinate Measuring Machines ◽  
Relational Analysis ◽  
Scanning Time ◽  
Coordinate Metrology ◽  
Grey Relational ◽  
Touch Probe

The phenomenon of coordinate measuring machines has led to a significant improvement in accuracy, adaptability, and reliability for measurement jobs. The coordinate measuring machines with scanning capabilities provide the alternative to output precise acquisition at a faster rate. However, they are less accurate as compared to discrete probing systems and slower than the noncontact techniques. Therefore, the data acquisition using a scanning touch probe needs improvement, so that it can provide commendable performance both in terms of accuracy and scanning time. The determination of appropriate scanning parameters is crucial to minimize the inaccuracy and time associated with the scanning process. However, it can be demanding as well as unreliable owing to the presence of uncertainty from a multitude of factors that may influence the measurement process. The optimization of data acquisition using a scanning touch probe is a multiresponse process which involves definite uncertainties from various sources. Therefore, multioptimization tools based on grey relational analysis coupled with principal component analysis and fuzzy logic were employed to enhance the utilization of the scanning touch probe. The work described here has the objective to identify the appropriate combination of scanning factors which can simultaneously boost the accuracy and lessen the scanning time. This study demonstrates the capability and effectiveness of the uncertainty theory based optimization methods in coordinate metrology. It also suggests that the uncertainty associated with the parameter optimization can be significantly reduced using these techniques. It has also been noticed that the results from the two techniques are in accord, which corroborates their application in coordinate metrology. The result from this study can be applied to other probing systems and can be broadened to include more experiments and parameters in various scenarios as needed by the specific application.

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.

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.

Optimization of Surface Roughness and Recast Layer Thickness in the Wire-EDM Process of AISI D2 Tool Steel Using Taguchi-Grey-Fuzzy

2013 ◽  
Vol 393 ◽  
pp. 21-28 ◽  
Author(s):  
Bobby Oedy Pramoedyo Soepangkat ◽  
Bambang Pramujati
Keyword(s):  
Surface Roughness ◽  
Fuzzy Logic ◽  
Grey Relational Analysis ◽  
Recast Layer ◽  
Relational Analysis ◽  
Recast Layer Thickness ◽  
Aisi D2 ◽  
Grey Relational ◽  
Wedm Process ◽  
D2 Steel

In this paper, the optimization of surface roughness and recast layer thickness of a WEDM process of AISI D2 steel was investigated by using Taguchi method, grey relational analysis and fuzzy logic. The experiments were conducted under varying flushing pressure, on time, open voltage, off time and servo voltage. An orthogonal array, signal-to-noise (S/N) ratio, grey relational analysis, grey-fuzzy reasoning grade and analysis of variance were employed to the study of the multiple performance characteristics. Experimental results have shown that machining performance characteristics in WEDM process of AISI D2 steel can be improved effectively through the combination of Taguchi method, grey relational analysis and fuzzy logic.

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.

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