Response Surface Modeling and Grey Relational Analysis to Optimize Turning Parameters with Multiple Performance Characteristics

2012 ◽  
Vol 2 (2) ◽  
pp. 12-45 ◽  
Author(s):  
L. B. Abhang ◽  
M. Hameedullah
Keyword(s):  
Response Surface ◽  
Grey Relational Analysis ◽  
Cutting Parameters ◽  
Interface Temperature ◽  
Nose Radius ◽  
Turning Operations ◽  
Relational Analysis ◽  
Feed Force ◽  
Grey Relational Grade ◽  
Grey Relational

Optimization of process parameters is the key step in response surface methods to achieve high quality without cost inflation. The multi-response optimization of the machining parameters viz, chip-tool interface temperature, main cutting force and feed force on lathe turning of En-31 steel as alloy steel using RSM with grey relational analysis is reported. A grey relational grade obtained from the grey relational analysis is used to solve the turning operations with multiple performance characteristics. The models were developed using response surface methodology. Optimal cutting parameters can be determined by RSM method using the grey relational grade as the performance index. Chip-tool interface temperature, main cutting force, and feed force are important characteristics in turning operations. Using these characteristics, the cutting operations, including cutting velocity, feed rate, depth of cut, and effective tool nose radius, are optimized. A model is developed to correlate the multiple performance characteristic called grey relational grade and turning parameters and a new combination of RSM and grey relational analysis is proposed. The grey relational grades were significantly affected by cutting parameters and tool nose radius. Optimal parameter setting is determined for the multi-performance characteristic.

scholarly journals Investigation of Drilling Parameters Using Grey Relational Analysis and Response Surface Methodology of Biaxial Glass Fibre Reinforced with Modified Epoxy Resin Composite

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
I Infanta Mary Priya ◽  
B. K. Vinayagam
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Glass Fibre ◽  
Grey Relational Analysis ◽  
Cutting Parameters ◽  
Image Processing Technique ◽  
Tool Materials ◽  
Relational Analysis ◽  
Glass Fibre Reinforced ◽  
Grey Relational

This research work attempts to study the most prominent factor of the drilling operations performed on different thicknesses of biaxial glass fibre reinforced with graphene platelet nanopowder and epoxy composite using three different drills. Damages are induced in the workpieces to analyse the effect of changed cutting parameters and different tool materials for varied thicknesses of the plates during the drilling process. The resultant drilled hole exhibited surface irregularities that are measured using SURFCOM 1400G. The circularity deviations of the holes are measured using a coordinate measuring machine. Image-processing technique is used to calculate the area of maximum diameter of the damaged zone. Using these data, delamination at entry and exit is calculated. Utilizing response surface methodology and grey relational analysis, the varied operations are carried out and analysed with different tool materials for common cutting parameters. It is found that the lesser thickness workpiece with selected HSS drill under high speed and low feed rate is the best variable option.

Optimization of CNC Turning Operations with Multiple Performance Characteristics using Taguchi based Grey Relational Analysis

2017 ◽  
Vol 9 (4) ◽  
Author(s):  
P. Lakshmikanthan ◽  
B. Prabu
Keyword(s):  
Analysis Of Variance ◽  
Grey Relational Analysis ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Performance ◽  
Turning Operations ◽  
Cnc Turning ◽  
Relational Analysis ◽  
Grey Relational

This study investigates the optimization of CNC turning operation parameters for Al6061 nickel coated graphite (NCG) metal matrix composite using the Taguchi based grey relational analysis method. The turning operations are carried out with carbide cutting tool inserts. According to the Taguchi quality concept, 3-level orthogonal array was chosen for the experiments. The experiments are conducted at three different cutting speeds (125, 175, 225m/min) with feed rates (0.1, 0.15, 0.2mm/rev) and depth of cut (0.5, 1, 1.5mm) and different % of reinforcement (2.5%, 5%, 7.5%), signal to noise ratio and the analysis of variance are used to optimize cutting parameters. The effects of cutting speed, feed rate and depth of cut on surface roughness and MRR are analyzed. Mathematical models are developed by using the response surface method to formulate the cutting parameters experimental results shown that machining performance can be improved effectively by using this approach, the analysis of variance (ANOVA) is applied to identify the most significant factor for the turning operations according to the weighted sum grade of the GRG. The predict responses shows the models have more than 95% of confident level of R2 value, from the obtained confirmation experiment result, it is observed, there is a good agreement between the estimated value and the experimental value of the grey relational grade. This experimental study reveals that the grey-Taguchi and RSM can be applied successfully for multi response characteristic performances.

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.

Optimization of Cutting Parameters of Multiple Performance Characteristics in End Milling of AlSi/AIN MMC – Taguchi Method and Grey Relational Analysis

2014 ◽  
Vol 68 (4) ◽  
Author(s):  
S. H. Tomadi ◽  
J. A. Ghani ◽  
C. H. Che Haron ◽  
M. S. Kasim ◽  
A. R. Daud
Keyword(s):  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Volume Fraction ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Relational Analysis ◽  
Grey Relational

The main objective of this paper is to investigate and optimize the cutting parameters on multiple performance characteristics in end milling of Aluminium Silicon alloy reinforced with Aluminium Nitride (AlSi/AlN MMC) using Taguchi method and Grey relational analysis (GRA). The fabrication of AlSi/AlN MMC was made via stir casting with various volume fraction of particles reinforcement (10%, 15% and 20%). End milling machining was done under dry cutting condition by using two types of cutting tool (uncoated & PVD TiAlN coated carbide). Eighteen experiments (L18) orthogonal array with five factors (type of tool, cutting speed, feed rate, depth of cut, and volume fraction of particles reinforcement) were implemented. The analysis of optimization using GRA concludes that the better results for the combination of lower surface roughness, longer tool life, lower cutting force and higher material removal could be achieved when using uncoated carbide with cutting speed 240m/min, feed 0.4mm/tooth, depth of cut 0.3mm and 15% volume fraction of AlN particles reinforcement. The study confirmed that with a minimum number of experiments, Taguchi method is capable to design the experiments and optimized the cutting parameters for these performance characteristics using GRA for this newly develop material under investigation.

scholarly journals Multi Performance Optimizationof Shoulder Milling Process Parameters of AA6063 T6 Aluminium Alloy by Taguchi Based GRA

2019 ◽  
Vol 8 (10S) ◽  
pp. 420-425
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Analysis Data ◽  
Milling Process ◽  
Depth Of Cut ◽  
Analysis Method ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational

In this paper, a grey relational analysis method based on Taguchi is proposed to improve the multi-performance characteristics of VMC shoulder milling process parameters in the processing of AA6063 T6. Taking into account four process parameters such as coolant, depth of cut,speed and feed, there are three level of each process parameter in addition to two levels of coolant. 18 experiments were used by L18 orthogonal array using the taguchi method. Multi-performance features like surface roughness and material removal rate are used. Grey Relational Analysis method is used to obtain the Grey Relational Grade, and the multiperformance characteristics of the process are pointed out. Then, the Taguchi response table method and ANOVA are used to analysis data. In order to ensure the validity of the test results, a confirmation test was conducted. The study also shows that this method can effectively improve the multi-function characteristics of shoulder milling process.In his work microstructure and mechanical properties of AA6063 T6before and after shoulder milling have been investigated.

Design optimization of micromixer with circular mixing chambers (M-CMC) using Taguchi-based grey relational analysis

2020 ◽  
Vol 18 (9) ◽  
Author(s):  
Ranjitsinha R. Gidde
Keyword(s):  
Grey Relational Analysis ◽  
Design Parameters ◽  
Relational Analysis ◽  
Mixing Dynamics ◽  
Depth Study ◽  
Grey Relational Grade ◽  
Grey Relational ◽  
Mixing Chambers ◽  
Optimal Set ◽  
Level Analysis

AbstractThe aim of the present study is to optimize the micromixer with circular mixing chambers (M-CMC) using Taguchi-based grey relational analysis approach. Simulations are performed to investigate the effect of design parameters viz. chamber diameter, transverse offset and width of constriction channel on performance characteristics for parameter sets corresponding to Orthogonal Array (OA) L9. Further, grey relational grade is used to identify the optimal set of design parameters. In depth study of flow and mixing dynamics are carried out to visualize the mixing mechanism for optimal and other two cases of proposed micromixer design configuration for Re in the range from 0.1 to 50. In order to assess the response of each design variable at each level, analysis of variance (ANOVA) is also performed to analyse influence of design parameters on mixing index and pressure drop.

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