An experimental investigation and optimization of friction stir welding process for AA6082 T6 (cryogenic treated and untreated) using an integrated approach of Taguchi, grey relational analysis and entropy method

2015 ◽  
Vol 230 (2) ◽  
pp. 454-469 ◽  
Author(s):  
Kamal K Jangra ◽  
Neeraj Sharma ◽  
Rajesh Khanna ◽  
Deepak Matta
Keyword(s):  
Experimental Investigation ◽  
Friction Stir Welding ◽  
Grey Relational Analysis ◽  
Welding Process ◽  
Integrated Approach ◽  
Entropy Method ◽  
Friction Stir ◽  
Friction Stir Welding Process ◽  
Relational Analysis ◽  
Grey Relational

Multi Response Optimization of Submerged Friction Stir Welding Process Parameters Using Grey Relational Analysis

2016 ◽  
Author(s):  
Senthil Kumar Velukkudi Santhanam ◽  
Sankar Ramaiyan ◽  
Lokesh Rathinaraj ◽  
Rathinasuriyan Chandran
Keyword(s):  
Friction Stir Welding ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Welding Process ◽  
Friction Stir ◽  
Friction Stir Welding Process ◽  
Response Characteristics ◽  
Relational Analysis ◽  
Response Optimization ◽  
Grey Relational

Friction stir welding (FSW) invented by TWI is a solid-state joining process, which is used to weld high-strength aluminum alloys and other metallic alloys which are non weldable by conventional fusion welding process. In this work, AA6063-O alloy of 150 mm in length, 75 mm in width and 6mm thickness is taken and friction stir welded in submerged condition in order to improve the joint properties. The chosen process parameters are tool pin profiles (cylindrical, threaded and tapered), rotational speed and welding speed. The process parameters are optimized with multi response characteristics including hardness and average grain size at the nugget zone. The traditional Taguchi approach is insufficient to solve a multi response optimization problem. Therefore, Grey Relational Analysis (GRA) is used in this current work. The optimal result indicates that the multi response characteristics of the AA6063-O during the submerged friction stir welding process can be enhanced through Grey Relational Analysis. In order to investigate the significance of process parameters, Analysis of Variance (ANOVA) is carried out. The mechanical properties and microstructure variation of both the normal FSW and submerged FSW joints are compared.

Multiple Response Optimization with Grey Relational Analysis of Friction Stir Welding Parameters in Joining Dissimilar Aluminium Alloys by Taguchi Method

2014 ◽  
Vol 592-594 ◽  
pp. 555-559 ◽  
Author(s):  
S. Ravikumar ◽  
V. Seshagiri Rao ◽  
V. Pranesh
Keyword(s):  
Grey Relational Analysis ◽  
Aluminium Alloys ◽  
Welding Process ◽  
Welding Parameters ◽  
Friction Stir ◽  
Relational Analysis ◽  
Novel Approach ◽  
Grey Relational Grade ◽  
Response Optimization ◽  
Grey Relational

This paper presents a novel approach for the optimization of welding parameters on dissimilar friction stir welded joints between AA6061T-651 and AA7075T-651 aluminium alloys with multiple responses based on orthogonal array by grey relational analysis. Experiments are conducted by varying the welding parameters related to three pin profiles. In this study, welding parameters namely rotational speed, welding speed and pin profiles are optimized with the considerations of multi responses such as ultimate tensile strength and hardness. A grey relational grade is obtained from the grey analysis. Based on the grey relational grade, optimum levels of parameters have been identified and significant contribution of parameters is determined by ANOVA (Analysis of Variance). Confirmation test is conducted to validate the test result. Experimental results have shown that the responses in welding process can be improved effectively through this novel approach.

Multi Response Optimization of Process Parameters using Taguchi based Grey Relational Method in FSW of AZ91B Magnesium Alloy

2021 ◽  
Vol 13 (4) ◽  
Author(s):  
M.A. Unnikrishnan ◽  
J. Edwin Raja Dhas
Keyword(s):  
Tensile Strength ◽  
Magnesium Alloy ◽  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Welding Process ◽  
Welding Parameters ◽  
Friction Stir ◽  
Relational Analysis ◽  
Optimization Of Process Parameters ◽  
Grey Relational

In this paper, the Taguchi method and grey relational analysis have been used to evaluate the weldability of AZ91B Magnesium alloy by friction stir welding process. Experiments were conducted using the L9 Taguchi design considering an orthogonal array consist of 3 factors and 3 levels. The rotational speed, transverse speed and angle of tilt of the tool are selected as welding parameters. Analysis of variance (ANOVA) is used to analyze the influence of the welding parameters on the responses namely, ultimate tensile strength (UTS) and hardness. The analysis results revealed that the transverse speed is the predominant parameter affecting tensile strength, hardness and quality of the weld. Confirmation test results showed that the Taguchi method coupled with grey relational analysis is very successful in the optimization of welding parameters for maximum strength and hardness in the FSW of AZ91B Magnesium alloy.

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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