Multi-Response Optimization of Dissimilar Al-Ti Alloy FSW Using Taguchi - Grey Relational Analysis

2020 ◽  
Vol 833 ◽  
pp. 35-39 ◽  
Author(s):  
Shival Patel ◽  
Kishan Fuse ◽  
Khushboo Gangvekar ◽  
Vishvesh Badheka

This article presents multi-response optimization of friction stir welding of dissimilar Al 6061-Titanium alloy using Taguchi based grey relational analysis. Taguchi’s L9 orthogonal array was used for designing the experiments. Process parameters considered for the experiments were rotational speed, traverse speed and tilt angle. Ultimate tensile strength, yield strength, and % elongation were the responses measured which all are larger-the-better characteristics. Based on grey relational grade, optimum levels of process parameters were identified and further ANOVA analysis was carried out to find most significant process parameter.

2014 ◽  
Vol 592-594 ◽  
pp. 555-559 ◽  
Author(s):  
S. Ravikumar ◽  
V. Seshagiri Rao ◽  
V. Pranesh

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nitesh Jain ◽  
Rajesh Kumar

Purpose Friction stir welding (FSW) is considered an environmentally sound process compared to traditional fusion welding processes. It is a complex process in which various parameters influence weld strength. Therefore, it is essential to identify the best parameter settings for achieving the desired weld quality. This paper aims to investigate the multi-response optimization of process parameters of the FSWed 6061-T6 aluminum (Al) alloy. Design/methodology/approach The input process parameters related to FSW have been sorted out from a detailed literature survey. The properties of weldments such as yield strength, ultimate tensile strength, percentage elongation and microhardness have been used to evaluate weld quality. The process parameters have been optimized using the Taguchi-based grey relational analysis (GRA) methodology. Taguchi L16 orthogonal array has been considered to design the experiments. The effect of input parameters on output responses was also determined by the analysis of variance (ANOVA) method. Finally, to corroborate the results, a confirmatory experiment was carried out using the optimized parameters from the study. Findings The ANOVA result indicates that the tool rotation speed was the most significant parameter followed by tool pin profile and welding speed. From the confirmation test, it was observed that the optimum FSW process parameters predicted by the Taguchi method improved the grey relational grade by 13.52%. The experimental result also revealed that the Taguchi-based GRA method is feasible in finding solutions to multi-response optimization problems in the FSW process. Originality/value The present study is unique in the multi-response optimization of FSWed 6061-T6 Al alloy using the Taguchi and GRA methodology. The weld material having better mechanical properties is essential for the material industry.


Author(s):  
Senthil Kumar Velukkudi Santhanam ◽  
Sankar Ramaiyan ◽  
Lokesh Rathinaraj ◽  
Rathinasuriyan Chandran

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.


2015 ◽  
Vol 772 ◽  
pp. 245-249
Author(s):  
A. Ramamurthy ◽  
R. Sivaramakrishnan ◽  
S. Venugopal ◽  
T. Muthuramalingam

It is very important and complexity to find the optimum values of wire EDM process parameters and contribution of each parameter to attain the better performance characteristics. In this study, an attempt has been made to optimize those parameters while machining the titanium alloy. Since the process involves more one than one response parameter, it is essential to carry out the multi-response optimization methodology .The experiments have been conducted with different levels of input factors such as pulse on time,pulse off time and wire tension based on Taguchi L9 orthogonal table.Wire EDM optimal process parameter has been identified using grey relational analysis and significant parameter has been determined by analysis of variance. Experimental results have indicated that the multi-response characteristic such as material removal rate and surface roughness can be improved effectively through grey relational analysis.


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.


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