Influence of processing parameters on the tool and workpiece mechanical interaction during Friction Stir Welding

Zimmer-Chevret, Sandra; Langlois, Laurent; Laye, Julien; Goussain, Jean‐Claude; Martin, Patrick; Bigot, Régis

doi:10.1007/s12289-009-0496-7

Cited by 10 publications

(8 citation statements)

References 1 publication

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“…Several studies used heuristic methods for optimized problem solving, such as adaptive large neighborhood search (ALNS), genetic algorithm (GA), differential evolution (DE), particle swarm optimization (PSO), variable neighborhood strategy adaptive search (VaNSAS), etc. These heuristics are successful in problem solving and lead to better solutions than conventional methods [15,43,44,50,51]. The VaNSAS algorithm was found to give higher accuracy than other algorithms, with an average solution accuracy of 99.92% [44,51,52,54].…”

Section: Introductionmentioning

confidence: 97%

“…Thereafter, the heat and plastic deformation are controlled by the rotation speed and welding speed parameter. The weld movement reduces the tool wear and axial force [44]. Therefore, both the axial force and tool material parameter were neglected in several previous study (see Table 1).…”

Section: Introductionmentioning

confidence: 99%

“…These heuristics are successful in problem solving and lead to better solutions than conventional methods [15,43,44,50,51]. The VaNSAS algorithm was found to give higher accuracy than other algorithms, with an average solution accuracy of 99.92% [44,51,52,54]. Assembly line balancing problems in manufacturing processes and location routing problems in transportation can be solved using the VaNSAS algorithm to reduce transport time and costs.…”

Section: Introductionmentioning

confidence: 99%

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Variable Neighborhood Strategy Adaptive Search for Optimal Parameters of SSM-ADC 12 Aluminum Friction Stir Welding

et al. 2021

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In this study, we present a new algorithm for finding the optimal friction stir welding parameters to maximize the tensile strength of a butt joint made of the semisolid material (SSM) ADC12 aluminum. The welding parameters were rotational speed, welding speed, tool tilt, tool pin profile, and rotational direction. The method presented is a variable neighborhood strategy adaptive search (VaNSAS) approach. The process of finding the optimal friction stir welding parameters comprises five steps: (1) identifying the type and range of friction stir parameters using a literature survey; (2) performing experiments according to (1); (3) constructing a regression model using the response surface method optimizer (RSM optimizer); (4) using VaNSAS to find the optimal parameters for the model obtained from (3); and (5) confirming the results from (4) using the parameter levels obtained from (4) to perform real experiments. The computational results revealed that the tensile strength generated from VaNSAS was 3.67% higher than the tensile strength obtained from the RSM optimizer parameters. The optimal parameters obtained from VaNSAS were a rotation speed of 2200 rpm, a welding speed of 108.34 mm/min, a tool tilt of 1.23 Deg, a tool pin profile of a hexagon, and a rotational direction of clockwise.

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Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Variable Neighborhood Strategy Adaptive Search for Optimal Parameters of SSM-ADC 12 Aluminum Friction Stir Welding

et al. 2021

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“…Furthermore, under suitable process conditions, FSW can allow the obtaining of a microstructure able to provide mechanical properties much higher than those of most fusion welding processes and formability levels so high that post-welding forming processes of welded blanks can be performed. Because of these advantages, FSW can be very useful both in joining materials with poor weldability or that are un-weldable, such as aluminium and magnesium alloys, and in the obtaining of joints characterised by high efficiency [1][2][3][4][5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Influence of Process Parameters on the Vertical Forces Generated during Friction Stir Welding of AA6082-T6 and on the Mechanical Properties of the Joints

Forcellese

Simoncini

Casalino

2017

Metals

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Abstract:The influence of the process parameters on the vertical force generated during friction stir welding of AA6082-T6 aluminium alloy sheet blanks was studied by performing experiments with constant values of the rotational speed, varying between 1200 and 2500 rpm, and welding speed, ranging between 30 and 100 mm/min. The effect of the tool dwelling was also analysed. The force vs. processing time curve has shown a very complex behaviour during the lowering motion of the pin tool related to the occurrence of both primary and secondary plunging. The tool dwelling produces a quick decrease in the vertical force with growing processing time until reaching a constant value. It was also seen that the tool dwelling does not influence the vertical force in the subsequent stage. As the tool began its welding motion, the vertical force immediately gets to a constant value until tool pulling out takes place. Furthermore, it was shown that the growth in the welding speed and the decrease in the rotational speed lead to an increase in the vertical force. The mechanical properties of the joints were evaluated versus the process parameters and the relationships among the ultimate tensile strength and ultimate elongation and the vertical force were defined. Finally, the microstructure developed during the friction stir welding was investigated and related to the mechanical properties of the joints.

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“…Therefore, a methodology based on the analysis of the kinematical and mechanical interactions generated during welding between the product, the process and the resources was developed by Zimmer and al. [4]. The idea is to analyze the interactions generated during welding between the tool / workpiece and the tool / material.…”

Section: Introductionmentioning

confidence: 99%

Using the Plunging and Welding Process Windows to Determine a FSW Means of Production

Zimmer-Chevret

Langlois

Laye

et al. 2010

AMR

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This paper presents an experimental methodology to determine a Friction Stir Welding (FSW) means of production based on the experimental study of the tool / material mechanical interactions generated during the plunging and welding stages. These two stages have been identified as being characteristic for the qualification of a FSW equipment. This paper presents the experimental results of the parametric study done on the plunging and welding phases. Ranges of forces and torques diagrams were established according to the processing parameters, in order to qualify a means of production and select the process parameters allowing the operation on the available FSW equipment.

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Influence of processing parameters on the tool and workpiece mechanical interaction during Friction Stir Welding

Cited by 10 publications

References 1 publication

Variable Neighborhood Strategy Adaptive Search for Optimal Parameters of SSM-ADC 12 Aluminum Friction Stir Welding

Variable Neighborhood Strategy Adaptive Search for Optimal Parameters of SSM-ADC 12 Aluminum Friction Stir Welding

Influence of Process Parameters on the Vertical Forces Generated during Friction Stir Welding of AA6082-T6 and on the Mechanical Properties of the Joints

Using the Plunging and Welding Process Windows to Determine a FSW Means of Production

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