Experimental investigation on influence of process parameter on friction stir processing of AA6082 using response surface methodology

Chanakyan, C.; Sivasankar, S.; Meignanamoorthy, M.; Ravichandran, M.; Muralidharan, T. C.

doi:10.1016/j.matpr.2019.05.384

Cited by 14 publications

(13 citation statements)

References 14 publications

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“…The objective function of the model was given by RSM (Equations (7)- (12)) and used in RSM-MDE. RSM-MDE was used to find the optimal solution of the problem subject to Equations (14)- (16). The range of parameter values that can be applied using RSM-MDE is shown in Table 3.…”

Section: Results Using Rsm-mdementioning

confidence: 99%

“…Each optimization software/program/method (Minitab RSM-optimizer, Lingo, and MDE) was executed 30 times. Minitab RSM-solver and MDE were used to solve Equations (14)- (16) to optimality, and the computational time was recorded, while these equations were individually solved in Lingo (Lingo cannot solve all equations at the same time), and the computational time of all equations was added together. The computational result is shown in Table 17.…”

Section: Results Using Rsm-mdementioning

confidence: 99%

“…where Q slide is the generated heat while sliding (watts), µ is the friction coefficient of the material, p is the axial force (kN), is the tool angular rotation speed (rad −1 ), D is the diameter of the shoulder (mm), d is the diameter of the pin (mm), and α is the shoulder angle ( • ). Table 1 lists the welding parameters and their values gathered from the literature review [8,9,[13][14][15][16][17][18][19]. The table shows that three factors affect the tensile efficiency: rotational speed (rpm), welding speed (mm/min), and axial force (kN).…”

Section: Introductionmentioning

confidence: 99%

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Combined Response Surface Method and Modified Differential Evolution for Parameter Optimization of Friction Stir Welding

et al. 2020

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In this study, we constructed a new algorithm to determine the optimal parameters for friction stir welding including rotational speed, welding speed, axial force, tool pin profile, and tool material. The objective of welding is to maximize the ultimate tensile strength of the welded aluminum. The proposed method combines the response surface method and the modified differential evolution algorithm (RSM-MDE). RSM-MDE is a method that involves both experimental and simulation procedures. It is composed of four steps: (1) finding the number of parameters and their levels that affect the efficiency of the friction stir welding, (2) using RSM to formulate the regression model, (3) using the MDE algorithm to find the optimal parameter of the regression model obtained from (2), and (4) verifying the results obtained from step (3). The optimal parameters generated by the RSM-MDE method were a rotation speed of 1417.68 rpm, a welding speed of 60.21 mm/min, an axial force of 8.44 kN, a hexagon-tapered tool pin profile, and the SKD 11 tool material. The ultimate tensile strength obtained from this set of parameters was 294.84 MPa, which was better than that of the RSM by 1.48%.

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Section: Results Using Rsm-mdementioning

confidence: 99%

Section: Results Using Rsm-mdementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Combined Response Surface Method and Modified Differential Evolution for Parameter Optimization of Friction Stir Welding

et al. 2020

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“…It establishes the equivalence between the input process parameters for friction stir processing. Regression equations ( 1) and ( 2) provide the equivalence between the measured process parameters to produce the maximum tensile strength and microhardness [19]. Figures 9(a (2)…”

Section: Regression Equation Of Tensile Strength and Microhardnessmentioning

confidence: 99%

Optimization of FSP Process Parameters on AA5052 Employing the S/N Ratio and ANOVA Method

Chanakyan

Sivasankar

Meignanamoorthy³

et al. 2021

Advances in Materials Science and Engineering

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AA5052 bead-on-plate processing has been achieved by the friction stir processing (FSP) technique to examine the manipulation of process parameters. It also improved the base metal surfaces to analyze the microstructure. The tool spinning speed, traverse speed, and axial load were preferred to investigate the effect of friction stir bead-on-plate processing on the tensile strength qualities and microhardness in AA5052. An optical microscope was used to dissect the fabricated processed zones of the microstructure. By using the design of the experiment, the orthogonal array of the L9 Taguchi method was used to construct the processing experiments. The analysis of variance and the signal-to-noise ratio methods were employed to identify the optimum unification of process parameters and the significant benefaction of a specific parameter on the responses. The outcomes showed that the tool spinning speed was the principal factor affecting the characteristics of tensile strength and microhardness, succeeded by the traverse speed and axial load. The intermetallic compound layer had formed during the processing under specified conditions. This examination revealed that the optimum parameters could intensify the mechanical behaviour of AA5052.

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“…The material AA2024 has a typical microstructure and crystallographic characteristics that alloy it to be suitable for aerospace applications involving higher strength, structural rigidity, good joining ability, etc., [6][7][8]. Chanakyan et al [9] investigated the effects of process parameters on ultimate tensile strength and micro hardness using RSM. Parameters like rotational speed, traverse speed and axial load were considered for developing mathematical models for predicting UTS and HV.…”

Section: Introductionmentioning

confidence: 99%

Interfacial Microstructure Analysis of AA2024 Welded Joints by Friction Stir Welding

Rajkumar¹,

Raja²,

Lingadurai³

et al. 2020

JNMES

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Process of joining different components by the application of external heat has resulted in induced stress on metals. Friction stir welding has been developed in order to avoid such residual stress development while joining. In this present work, aluminium alloy AA2024 plates were welded by using Friction stir welding process. The experiments were conducted for different combinations of parameters such as rotational speed, transverse speed and axial load. Welded joints developed were tested for mechanical and microstructure analysis. Mechanical joints developed have a maximum hardness of 147.6 hv in nugget zone and maximum tensile strength of 368.76 N/mm 2. Response surface analysis carried out has revealed that transverse speed and rotational speed has high impact on the hardness and tensile strength respectively. The grains at the nugget zone were very fine and uni-axed improving their tensile strength.

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Experimental investigation on influence of process parameter on friction stir processing of AA6082 using response surface methodology

Cited by 14 publications

References 14 publications

Combined Response Surface Method and Modified Differential Evolution for Parameter Optimization of Friction Stir Welding

Combined Response Surface Method and Modified Differential Evolution for Parameter Optimization of Friction Stir Welding

Optimization of FSP Process Parameters on AA5052 Employing the S/N Ratio and ANOVA Method

Interfacial Microstructure Analysis of AA2024 Welded Joints by Friction Stir Welding

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