Multi Response Optimization of Friction Stir Welding Process Variables using TOPSIS approach

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.

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Multi response Optimization of Friction stir welding process parameters in dissimilar alloys using Grey relational analysis

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/390/1/012061 ◽

2018 ◽

Vol 390 ◽

pp. 012061 ◽

Cited By ~ 1

Author(s):

K Palani ◽

C Elanchezhian

Keyword(s):

Friction Stir Welding ◽

Process Parameters ◽

Grey Relational Analysis ◽

Welding Process ◽

Friction Stir ◽

Friction Stir Welding Process ◽

Relational Analysis ◽

Dissimilar Alloys ◽

Response Optimization ◽

Grey Relational

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Multi-response optimization of friction stir welding process parameters for dissimilar joining of Al6101 to pure copper using standard deviation based TOPSIS method

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1177/0954406219858628 ◽

2019 ◽

Vol 233 (18) ◽

pp. 6473-6482 ◽

Cited By ~ 2

Author(s):

Nidhi Sharma ◽

Zahid A Khan ◽

Arshad Noor Siddiquee ◽

Mohd Atif Wahid

Keyword(s):

Tensile Strength ◽

Friction Stir Welding ◽

Ultimate Tensile Strength ◽

Process Parameters ◽

Welding Speed ◽

Welding Process ◽

Micro Hardness ◽

Friction Stir ◽

Friction Stir Welding Process ◽

Response Optimization

Friction stir welding is a new and effective solid-state welding process for joining dissimilar materials such as aluminum (Al) and copper (Cu). Joint quality of the friction stir welded materials gets influenced by the welding strategy and different friction stir welding process parameters, i.e. rotational speed, welding speed, tool design, tool pin offset, and tilt angle. In this paper, the effect of combination of different friction stir welding process parameters during joining of Al-6101 and pure copper is studied using Taguchi L18 orthogonal array. Four friction stir welding process parameters, i.e. shoulder diameter (A), pin offset (B), welding speed (C), and rotational speed (D) each at three levels except shoulder diameter, which is at two levels are selected. The effect of different combinations of these parameters on ultimate tensile strength and micro-hardness of the joints is investigated. Subsequently, single response optimization for ultimate tensile strength and micro-hardness and multi-response optimization of ultimate tensile strength and micro-hardness taken together is carried out to obtain the optimal combination of the friction stir welding process parameters. Taguchi method is used for single response optimization, whereas Taguchi-based TOPSIS method is employed for multi-response optimization. For single optimization, the optimum combination of the friction stir welding parameters yielding maximum strength and micro-hardness are A1B1C2D2 and A2B1C2D3, respectively. The optimum combination of the process parameters for multi-response optimization is A2B1C2D2. From the results of the study for single- and multi-response optimization, it is revealed that the rotational speed is the most significant process parameter affecting the tensile strength and micro-hardness of the joints followed by the welding speed. Further, the macro/microstructure and micro-hardness profile of the joint obtained at the optimal combination of the multi-response optimization are given and discussed for better understanding of material mixing and joining.

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

Volume 2: Advanced Manufacturing ◽

10.1115/imece2016-65797 ◽

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.

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A new calculation method of viscoplastic heat production generated by plastic flow of friction stir welding process

Materials Chemistry and Physics ◽

10.1016/j.matchemphys.2021.124795 ◽

2021 ◽

pp. 124795

Author(s):

Fang Yan ◽

YuCun Zhang ◽

Jiuli Shen ◽

XianBin Fu ◽

Songtao Mi

Keyword(s):

Friction Stir Welding ◽

Plastic Flow ◽

Heat Production ◽

Calculation Method ◽

Welding Process ◽

Friction Stir ◽

Friction Stir Welding Process

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Application of Self-Made Dynamometer in Measuring Tool Forces in Friction Stir Welding Process

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.693.1339 ◽

2016 ◽

Vol 693 ◽

pp. 1339-1345

Author(s):

Hong Feng Wang ◽

J.L. Wang ◽

W.W. Song ◽

Dun Wen Zuo ◽

Q.Q. Zhu

Keyword(s):

Friction Stir Welding ◽

Design Principle ◽

Welding Process ◽

Cross Sensitivity ◽

Friction Stir ◽

Friction Stir Welding Process ◽

Measuring Tool ◽

Ring Deformation

In this paper, the dynamometer for measuring the forces of the tool in FSW process was designed. The design principle of the dynamometer was adopted octagonal ring deformation to get the forces in FSW process. The design dynamometer was calibrated, the result showed the linearity and cross sensitivity of the dynamometer in allowed range, the worked reliable of the dynamometer was good. It can be used to measure the forces in FSW process.

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