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.

Multi Response Optimization of Submerged Friction Stir Welding Process Parameters Using TOPSIS Approach

2015 ◽  
Author(s):  
Senthil Kumar Velukkudi Santhanam ◽  
Lokesh Rathinaraj ◽  
Rathinasuriyan Chandran ◽  
Shankar Ramaiyan
Keyword(s):  
Friction Stir Welding ◽  
Process Parameters ◽  
Welding Process ◽  
Fusion Welding ◽  
Friction Stir ◽  
Friction Stir Welding Process ◽  
Response Characteristics ◽  
Response Optimization ◽  
Topsis Approach ◽  
Tool Pin

Friction stir welding (FSW) is a solid-state welding process which is used to join high-strength aircraft aluminum alloys and other metallic alloys which are difficult to weld by conventional fusion welding. In this paper, AA6063-O alloy of 6mm thickness was taken and friction stir welded under the water in order to improve the joint properties. The process parameters considered as rotational speed, welding speed and tool pin profiles (cylindrical, threaded and tapered) are optimized with multi response characteristics including hardness, tensile strength and % elongation. In order to solve a multi response optimization problem, the traditional Taguchi approach is insufficient. To overcome this constraint, a multi criteria decision making approach, namely, techniques for order preference by similarity to ideal solution (TOPSIS) is applied in the present study [13]. The optimal result indicates that the multi response characteristics of the AA6063-O during the submerged friction stir welding process can be enhanced through the TOPSIS approach. The Analysis of Variance (ANOVA) was carried out to investigate the significant parameter for the submerged friction stir welding process. The mechanical properties of the submerged FSW are compared with normal FSW joints.

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 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
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Traverse Speed ◽  
Anova Analysis ◽  
Friction Stir ◽  
Relational Analysis ◽  
Significant Process ◽  
Grey Relational Grade ◽  
Response Optimization ◽  
Grey Relational

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.

Multi-response optimization of process parameters in friction stir welded aluminum 6061-T6 alloy using Taguchi grey relational analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nitesh Jain ◽  
Rajesh Kumar
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Al Alloy ◽  
Weld Quality ◽  
Content Type ◽  
Friction Stir ◽  
Relational Analysis ◽  
Optimization Of Process Parameters ◽  
Response Optimization ◽  
Grey Relational

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.

scholarly journals Effects of process parameters on mechanical and metallurgical properties of AA5083 weld bead and optimization by using Taguchi based grey relational analysis and ANOVA of submerged friction stir welding.

2021 ◽  
Author(s):  
Laxmanaraju salavaravu ◽  
◽  
Lingaraju Dumpala ◽  
Keyword(s):  
Friction Stir Welding ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Rotational Speed ◽  
Weld Zone ◽  
Process Conditions ◽  
Tool Rotational Speed ◽  
Friction Stir ◽  
Relational Analysis ◽  
Grey Relational

Friction stir welding (FSW) can be made to improve the mechanical properties in the weld zone. This article aims to obtain the optimum FSW process parameters used for two plates of AA5083 welded joints. The significant factors in the FSW process are tool rotational speed(TRS), tool transverse speed(TTS), and the weld process conditions are Submerged FSW and Normal FSW. For doing the investigation, the Taguchi method L18 orthogonal array design of experimentation is utilized. Using the Grey Relational Analysis(GRA) to calculate the grey relation grade, the response parameters are tensile strength, microhardness, and surface roughness. The Optimum process parameters contain been recognized, and ANOVA controls the significant contribution of process parameters. The optimal FSW process parameters are used to maximize the FSW joint strength. It is identified in the condition of Submerged FSW, high tool rotational speed, and low TTS.

Sign in / Sign up

Export Citation Format

Share Document