Optimization of process parameters in friction stir welding of AA5451

doi:10.21203/rs.3.rs-1606359/v1

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Optimization of process parameters in friction stir welding of AA5451

https://doi.org/10.21203/rs.3.rs-1606359/v1

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Friction stir welding is one of the primary fabrication techniques for making different engineering components, especially aluminum alloys. The welded joint with the friction stir process greatly depends on the process parameters, i.e., feed rate, rotational speed, and pin profile of the tool. In the current study, plates of AA5451 were joined by the friction stir welding technique, and the Taguchi method was used to find the process parameters at an optimal level. It was concluded that for tensile strength, tool rotation speed of 1400, threaded tool pin profile and feed rate of 18 mm/min were optimum parameters. At the same time, the optimum parameters for hardness were tool rotation speed of 1200, threaded tool pin profile and feed rate of 18 mm/min. Overall, the tool pin profile was the major parameter for improving the welded joint’s tensile strength and hardness. In addition, the contribution in terms of percentage of each input parameter was found by the Analysis of Variance (ANOVA). The ANOVA results also revealed that the pin profile of tool has the maximum contribution on the results of tensile strength and hardness. The study also investigated the joint efficiency of friction stir welded joint, hardness at weld zone, and metallography on friction stir welding samples at the optimized level.

AA5451

Friction stir welding

Taguchi method

Analysis of variance

Aluminium and its alloys have enormous applications in engineering due to its outstanding mechanical properties, like higher strength to weight ratio, low density, high resistance to corrosion, easy fabrication, and recycling [1, 2]. However, aluminium alloys faced several challenges in conventional welding methods. For example, one of the main disadvantages of fusion welding is a complete alteration of microstructure and inferior mechanical properties. These issues can be prevented in friction stir welding, which provides improved joint properties compared to fusion weld joints [3].

The friction stir welding technique can be applied to weld similar and dissimilar metals and is gaining popularity nowadays. During friction stir welding, a welding tool that is non-consumable is forcibly plunged into the joint line of plates to be welded with a particular rotation speed. The tool travels along the length of the joint and creates sufficient heat through friction to plastically deform the material [4]. The weld zone in the FSW consists of HAZ, TMAZ and the nugget zone. In the HAZ, no plastic deformation occurs in the materials; however, the welding heat affects this region and causes some microstructural changes. In the second zone, i.e., TMAZ, the generated heat during the FSW affects the material and becomes partially deformed. Finally, the material is deformed severely in the SZ at the pin location during the weld [4].

Joints made with FSW are much stronger and more economical than traditional fusion welding techniques. Further, FSW improves weld quality, reduces defects, and lowers health hazards [5]. The most significant parameters that contribute to the weld quality and affect the welded zone properties include the tool pin profile, rotation speed of the tool and feed rate [6].

Previously, Gomathisankar et al. [7] investigated FSW parameters using the Taguchi method on AA-6061 to examine the friction stir welded region’s mechanical properties. The result revealed that the feed rate played an essential role in improving tensile strength and hardness. In comparison, tool rotation speed, time of dwell and tilt angle of the tool have comparatively less effect on mechanical properties. Dawood et al. [8] considered AA6061 to study the influence of pin profiles of the tool on friction stir welded joint’s mechanical properties. The fracture surface analysis indicated that the joints were affected using different pin profiles of the tool. Shojaeefard et al. [9] optimized the tool rotation speed, feed rate and tool shoulder diameter for tensile strength, grain size, and hardness using Taguchi’s technique. The optimum conditions were 1120 tool rotational speed, a 1.5-degree tilt angle, and a 6.5 mm/min feed rate. The maximum hardness value occurred at the middle of the welded nugget region because of the formation of tiny, recrystallized grains. Boldsaikhan et al. [10] introduced a new technique for the detection of wormhole defects in the FSW in a non-destructive manner. They demonstrated an approach that provided feedback information for weld quality in real-time. Baratzadeh et al. [4] studied the mechanical properties and microstructure of FSW joint of automotive aluminium alloys AA-6082-T6 and AA-6063-T6. Their study identified the enhanced process parameters using dissimilar aluminium alloys for increased weld quality. Msomi et al. [11] discussed the joint quality of 5083-H111 and 1050-H14 aluminium alloys joined by friction stir welding. The microstructure and mechanical properties of the welded joint were analyzed and compared with base materials. Correlation between the mechanical behaviour and microstructure of the welded joint was discussed. The results indicated that the tensile strength of the welded joint was larger than the AA-1050-H14 and lower than AA-5083-H111. The micro-hardness of the friction stir region was greater than AA-1050-H14 and came in the same range when compared with AA-5083-H111. Recently, Nakowong and Sillapasa [12] used the Taguchi method, regression analysis and analysis of variance for the optimization of process parameters for the FSW. Their focus was tensile strength, hardness, and microstructure; however, the studied material was the semi-solid metal 5083 aluminium alloy.

The above studies indicate that it is significantly essential in optimizing specified parameters for industrial decision-making. The previous studies also show the optimization of process parameters of different materials that are joined by FSW technique, including aluminium alloys. However, none of the above studies optimized process parameters using friction stir welding on AA5451. Aluminum alloy AA5451 is generally used in marine applications because of its excellent weldability and corrosion resistance.

Therefore, the current work aims to optimize process parameters by the Taguchi method for FSW of AA5451 with three different process parameters: tool rotational speed, feed rate, and the tool geometry. The focus of the study is to analyze the tensile strength and hardness at the weld zone; however, the joint efficiency and microstructure at the weld zone are also examined. Additionally, ANOVA was applied to calculate the percentage contributions of input parameters in improving the tensile strength and hardness of the weld.

Commercially available AA5451 was used in the present study. The dimensions of AA5451 plates were 900mm×60mm×6mm. The chemical composition of the AA5451 was found using spectromax, and obtained results are shown in Table 1.

Table 1

Chemical composition of AA-5451
Al	Si	Mg	Fe	Cr	Mn	Cu	V	Ti	Zn	P
97.19%	0.07%	2.23%	0.17%	0.2%	0.08%	0.004%	0.02%	0.02%	0.01%	0.002%

A vertical head CNC milling machine was used to prepare sheared faces edges with excellent finishing and perpendicularity. Three pairs of plates were welded with three different regions having varying parameters for process optimization. These factors with their levels are given in Table 2. The welding direction and rolling direction were perpendicular to each other and a single weld pass was used to fabricate the joints. The same tools were previously recommended by Nakowong and Sillapasa [12]; however, their base material was Al5083. Also, they used the tool pin profile with different levels of tool rotational speed. Further, their levels of feed rates were different from those selected in this study. The selected tool was made of HSS (H-13) material with three geometries, as presented in Fig. 1.

Table 2

Input parameters involved along with their levels
Factors	Level 1	Level 2	Level 3
Tool Rotation Speed	1000	1200	1400
Feed Rate (mm/min)	16	18	20
Tool Pin Profile	Taper	Threaded	Cylindrical

ASTM E8 standard was applied for the preparation of tensile test specimens, as depicted in Fig. 2. It was ensured that the gauge length of the tensile specimens incorporates the central part of the welded portion. A strain rate of 3 mm/min was set up until the complete fracture of specimens. Finally, the ultimate tensile strength was obtained from the stress-strain curve for each specimen welded with different process parameters. Figure 3 (a) and 3 (b) show the tensile specimen before and after failure.

Further, the microhardness values were taken at the bead. A Vickers tester with a dwelling time of 10 to 15 seconds was used to get the microhardness values of the weld specimens. For the optimization of parameters, the Taguchi method was implemented that includes an L₉ orthogonal array using all three factors with their respective levels. Therefore, welding was carried out for nine different combinations based on input parameters given in Table 3.

Table 3

Input variables or L₉ Orthogonal Array
Sr. No	Tool Rotation Speed (rpm)	Feed Rate (mm/min)	Tool Pin Profile
1	1000	16	Taper
2	1000	18	Threaded
3	1000	20	Cylindrical
4	1200	16	Threaded
5	1200	18	Cylindrical
6	1200	20	Taper
7	1400	16	Cylindrical
8	1400	18	Taper
9	1400	20	Threaded

The study is organized around optimizing the process parameters to achieve higher tensile strength and hardness value. However, the other output parameters, such as joint efficiency, and metallography on FSW samples, were also performed. This investigation was carried out using the process parameters at the optimum level obtained after the tensile test and the hardness of FSW joints. For metallography, Leica Zeiss 100 microscope (magnification 25x ~ 1000x) was used. Finally, the percentage contribution of each parameter was found by analysis of variance. A 95% confidence is taken while performing analysis of variance, which is usually used by past researchers [13].

3.1. Process parameters optimization for the tensile strength and hardness

In this study, the Taguchi method was used to optimise process parameters to obtain a higher value of tensile strength and hardness of AA5451 after FSW. In the Taguchi method, experimental values are converted into signal-to-noise ratios. The larger the better signal to noise ratio (S/N ratio) criteria were chosen to maximize the response using Eq. 1. Experimental results, along with signal-to-noise ratios, are shown in Table 4.

$\text{S}/\text{N} \text{r}\text{a}\text{t}\text{i}\text{o} \left({\eta }\right)= -10{\text{log}}_{10}\frac{1}{\text{n}}\sum _{\text{i}=1}^{\text{n}}\frac{1}{{\text{y}}_{\text{i}}^{2}}$	(1)
where,
n = Number of experiments
${\text{y}}_{\text{i}}$ = ${\text{i}}^{\text{t}\text{h}}$ the experimental value for the parameter

Table 4

Result of experiments and corresponding signal to noise ratios
Trial No	Orthogonal Array with Control Factors			Experimental layout with control factors and levels			Experimental Results		S/N Ratios
Trial No	Tool Rotational Speed	Feed rate	Tool Pin Profile	Tool Rotational Speed	Feed rate	Pin Profile of tool	Tensile strength (MPa)	Hardness (Weld zone)	Tensile strength (MPa)	Hardness (Weld zone)
1	1	1	1	1000	16	Taper	110.91	69.5	40.8996	36.8397
2	1	2	2	1000	18	Threaded	150.60	79.6	43.5565	38.0183
3	1	3	3	1000	20	Cylindrical	120.20	72.1	41.5981	37.1587
4	2	1	2	1200	16	Threaded	155.80	78.2	43.8513	37.8641
5	2	2	3	1200	18	Cylindrical	127.60	77.3	42.1170	37.7636
6	2	3	1	1200	20	Taper	118.90	70.7	41.5036	36.9884
7	3	1	3	1400	16	Cylindrical	139.00	73.5	42.8603	37.3257
8	3	2	1	1400	18	Taper	136.70	73.7	42.7154	37.3493
9	3	3	2	1400	20	Threaded	143.66	74.9	43.1467	37.4896

The main effect plots from Fig. 4 and S/N ratios from Table 5 show that the optimum conditions for high tensile strength are 1400 tool rotational speed, a feed rate of 18 mm/min, and a threaded tool pin profile. Figure 5 and Table 5 also show that the optimum conditions at which hardness values are obtained are the tool rotational speed of 1200, feed rate of 18 mm/min, and the threaded tool pin profile. A likely explanation for this is that the threaded pin profile made a flawless joint due to adequate stirring of material around the pin. It is also evident from previous research that tool shoulder generates 80%, and tool pin profile produces 20% of total heat generation during stirring [14]. However, the influence of the tool pin profile on material flow behavior is more significant than the tool shoulder [15].

Table 5

Tensile strength and hardness S/N ratios
S/N Ratio Response Values for tensile strength
Level	Tool Rotational Speed	Feed Rate (mm/min)	Tool Pin Profile
1	42.02	42.54	41.71
2	42.49	42.80^a	43.52 ^a
3	42.91^a	42.08	42.19
Delta	0.89	0.71	1.81
Rank	2	3	1
S/N Ratio Response Values for hardness
Level	Tool Rotational Speed	Feed Rate (mm/min)	Tool Pin Profile
1	73.73	73.73	71.30
2	75.40 ^a	76.87 ^a	77.57 ^a
3	74.03	72.57	74.30
Delta	1.67	4.30	6.27
Rank	3	2	1
^a Optimum value.

3.2 Results using Analysis of Variance

Analysis of variance is used to understand the effect of each input parameter on the output parameters. The input parameters used in current study are feed rate, tool rotational speed and tool pin profile, while the responses in this study are the tensile strength and hardness. The confidence interval taken into consideration for the current investigation was 95%. Table 6 displays input parameters contribution in terms of percentage on responses. Table 6 shows that the tool rotation speed has an impact of 12.68%, feed rate with 9.78% and tool pin profile has the effect of 67.77% on tensile strength. Therefore, the pin profile of the tool has more impact than the feed rate and rotational speed of the tool on the tensile strength. However, in this study, the confidence interval taken was 95%. Therefore, those parameters become insignificant, whose p-value is greater than 0.05. Thus, none of the parameters is significant at a 95% confidence level. For hardness, the tool rotational speed has an impact of 5.01%, feed rate with 31.42% and pin profile of tool with 62.42%. For hardness pin profile of tool and feed rate are significant parameters while rotational speed of the tool becomes insignificant. Table 4 also revealed that the significant process parameters affecting the hardness at a 95% confidence level were tool pin profiles following the feed rate and rotational speed, which is in agreement with previous studies [26]

Table 6

ANOVA Table for tensile strength and hardness
Source	D.F	Seq. SS	Contribution	Adj. SS	Adj. MS	F-Value	P-Value
Tensile Strength
Tool Rotation Speed	2	236.9	12.68%	236.9	118.46	1.30	0.435
Feed Rate	2	182.7	9.78%	182.7	91.34	1.00	0.500
Pin Profile of tool	2	1266.0	67.77%	1266.0	632.98	6.94	0.126
Error	2	182.5	9.77%	182.5	91.26	-	-
Total	8	1868.1	100.00%	-	-	-	-
Hardness (Weld zone)
Tool Rotation Speed	2	4.74	5.01%	4.74	2.368	4.38	0.186
Feed Rate	2	29.67	31.42%	29.67	14.834	27.41	0.035
Pin Profile of tool	2	58.94	62.42%	58.94	29.471	54.46	0.018
Error	2	1.08	1.15%	1.08	0.541	-	-
Total	8	94.43	100%	-	-	-	-

3.3 Response optimization for tensile strength and hardness

Response optimization identifies the combination of input variables that collectively optimize single or multiple output responses. The input parameters are the Tool Rotational Speed, Feed Rate and Tool Pin with the combination shown in Table 4. The output response is the tensile strength. The tensile strength value predicted by the response optimisation technique was 160.6907 MPa obtained at 18 mm/min feed rate, 1400 rotational speed with threaded tool pin profile, as given in Table 7. Similarly, the hardness value of 81.056 HV was predicted with a feed rate of 18 mm/min, tool rotation speed of 1200 rpm, and threaded pin profile of tool, given in Table 8.

Table 7

Response optimization for tensile strength
Parameters
Response			Goal	Lower	Target	Upper	Weight	Importance
Tensile strength (MPa)			Maximum	110.912	155.8	-	1	1
Solution
Solution		Tool rotational speed		Feed rate	Tool Pin profile	Tensile strength (MPa) Fit		Composite Desirability
1	1400			18	Threaded	160.691		1
Multiple Response Prediction
Variable						Setting
Tool Rotation Speed						1400
Feed rate						18
Pin Profile of tool						Threaded
Response				Fit	SE Fit	95% CI	95% PI
Tensile strength (MPa)				160.69	8.43	(124.44, 196.94)	(105.88, 215.50)

Table 8

Response optimization for hardness
Parameters
Response		Goal	Lower	Target	Upper	Weight	Importance
Hardness (Hv)		Maximum	69.5	79.6		1	1
Solution
Solution	Tool rotational speed		Feed rate	Tool Pin profile	Tensile strength (MPa) Fit		Composite Desirability
1	1200		18	Threaded	81.0556		1
Multiple Response Prediction
Variable					Setting
Tool Rotation Speed					1200
Feed rate					18
Pin Profile of tool					Threaded
Response			Fit	SE Fit	95% CI	95% PI
Hardness (Hv)			81.056	0.649	(78.264, 83.847)	(76.835, 85.276)

3.4 Joint Efficiency at Optimum Level

From the response optimizer data, the optimum parameters considered for tensile strength were 1400 tool rotational speed, 18 mm/min feed rate and threaded pin profile. Therefore, the tensile strength value at the optimal level of the welded specimen was found as 157 MPa, thus validating the optimum combination of parameters. Additionally, the experimental tensile strength of base material AA5451 was found as 195 MPa. Therefore. The joint efficiency at optimum condition comes out to be 80.5% calculated using Eqs. (2)

$$\mathbf{J}\mathbf{o}\mathbf{i}\mathbf{n}\mathbf{t} \mathbf{E}\mathbf{f}\mathbf{f}\mathbf{i}\mathbf{c}\mathbf{i}\mathbf{e}\mathbf{n}\mathbf{c}\mathbf{y}=\frac{\mathbf{S}\mathbf{t}\mathbf{r}\mathbf{e}\mathbf{n}\mathbf{g}\mathbf{t}\mathbf{h} \mathbf{o}\mathbf{f} \mathbf{w}\mathbf{e}\mathbf{l}\mathbf{d}}{\mathbf{S}\mathbf{t}\mathbf{r}\mathbf{e}\mathbf{n}\mathbf{g}\mathbf{t}\mathbf{h} \mathbf{o}\mathbf{f} \mathbf{b}\mathbf{a}\mathbf{s}\mathbf{e} \mathbf{m}\mathbf{a}\mathbf{t}\mathbf{e}\mathbf{r}\mathbf{i}\mathbf{a}\mathbf{l}}$$

3.5 Hardness Properties at Optimum Level

Similarly, at the optimum level for hardness at the weld zone i.e., tool rotational speed of 1200, feed rate 18 mm/min with threaded pin profile, the Vickers hardness values at different regions were measurement as shown in Fig. 6. These regions include the Advancing Side, Bead, HAZ and Retarding side. The hardness of the advancing side and retarding side was found to be the same and lower from the bead. However, the friction stirs welded region exhibit’s a higher value of Vickers microhardness than the base region, which could be expected from refined grain size. Since the microstructure of the advancing side and retarding side are not affected by the welding process, their values are comparatively lower and different from the weld zone.

3.6 Microstructures at Optimum Level

The microstructure of the samples made at the optimum levels described in section 3.5 was analyzed and matched with the base metal as presented in Fig. 7. In the base region of AA5451, the grain size is larger. In contrast, the friction stir welded region has smaller grains. This result indicates that the friction stir welded region is deformed plastically due to the spinning probe’s mechanical stirring action. After the stirring action, the grains are modified by dynamic recrystallization. Recrystallization of grains into the fine structure is also observed in the research work reported by Hall-Petch [16]. Refinement of grain size was observed in this study with an increased value of the tool rotational speed. This improved microstructure would lead to welded joints with enhanced mechanical properties.

In the current study, the optimum level was found by the Taguchi method, and ANOVA was used to evaluate the %age contribution of each factor. The following results were concluded from the present study.

The highest value of tensile strength, i.e., 160.6907 Mpa, was shown by friction stir welded joints fabricated using optimum conditions of 1400 tool rotation speed, feed rate of 18 mm/min and the tool pin with threads.

The improved tensile strength was attributed to grain size refinement, which is directly related to the high rotational speed of the tool, sufficient feed rate, and geometry of the tool pin profile that provide better stirring action in the weld zone.

The maximum value of hardness, i.e. 81.056 HV, was shown by friction stir welded joints fabricated using optimum conditions of 1200 tool rotational speed, feed rate of 18 mm/min with threaded tool pin profile.

The higher value of Vickers microhardness was also observed in the friction stir zone due to refining microstructure.

Tool geometry was the major factor affecting tensile strength, contributing with 67.77%, while feed rate has the least effect on tensile strength, contributing 9.78%.

Tool geometry was the major factor affecting the hardness, contributing 62.42%, while tool rotation speed has the least effect on hardness contributing with 5%.

The effectiveness and reliability of FSW joints for shipping industry applications can be observed by joint efficiency. That was investigated at optimum conditions, and it comes out to be 82.4%.

Data Availability: The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

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No competing interests reported.

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Optimization of process parameters in friction stir welding of AA5451

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Version 1

Abstract

Figures

1. Introduction

2. Materials And Methods

3. Results And Discussions

3.1. Process parameters optimization for the tensile strength and hardness

3.2 Results using Analysis of Variance

3.3 Response optimization for tensile strength and hardness

3.4 Joint Efficiency at Optimum Level

3.5 Hardness Properties at Optimum Level

3.6 Microstructures at Optimum Level

5. Conclusions

Declarations

References

Additional Declarations

Status:

Version 1

\(\text{S}/\text{N} \text{r}\text{a}\text{t}\text{i}\text{o} \left({\eta }\right)= -10{\text{log}}_{10}\frac{1}{\text{n}}\sum _{\text{i}=1}^{\text{n}}\frac{1}{{\text{y}}_{\text{i}}^{2}}\)	(1)
where,
n = Number of experiments
\({\text{y}}_{\text{i}}\) = \({\text{i}}^{\text{t}\text{h}}\) the experimental value for the parameter