Analysis and Multi-Response Optimization of Friction Stir Welding Parameters for Stir-Cast AA6092/B₄C/ ZrO₂ Hybrid Composites

Abstract

In this research study, Aluminium-based alloy (AA6092) reinforced with 3 wt.% Boron Carbide (B₄C) and 5 wt.% Zirconium dioxide (ZrO₂) particulates was fabricated into Aluminium Metal Matrix Hybrid Composites (AMMHCs) via stir casting. These AMMHCs were subsequently friction-stir welded under various conditions to optimize the ultimate tensile strength (UTS) and weld nugget hardness (WNH) of the welded joints. This innovative AMMHC material is replacing the AA6061, and AA6082 composites for the applications like bulkhead partitions in ship hulls since this AMMHC has superior properties such as reduced weight, enhanced specific strength, and lower thermal expansion coefficient. To optimize the performance of friction stir welded butt joints in AA6092/3% B₄C/5% ZrO₂ composites, key Friction Stir Welding (FSW) process parameters including Tool Rotational Speed (TRS), Welding Speed (WS), Axial Load (AL) and Tool Tilt Angle (TTA) were examined. In this research work, empirical relationships were established between the most influential parameters (TRS, WS, and AL) and the resulting responses (UTS and WNH). A desirability function approach was employed to predict optimal values for UTS and WNH, leading to recommended process parameters of 1279.18 rpm for TRS, 53.54 mm/min for WS, and 4.9 kN for AL and TTA for 1.5°. The calculated UTS, and WNH values of 513.09 MPa and 194.92 HRB, respectively, were subsequently validated through experimental verification.

Keywords:
Friction stir welding; Aluminium alloy AA6092; Boron carbide; Zirconium dioxide; Weld nugget hardness; Ultimate tensile strength; Response surface methodology

1. Introduction

The automotive industry's increasing focus on environmental sustainability has driven the adoption of AMMHCs to reduce vehicle weight, fuel consumption, and emissions. By replacing steel components with lighter AMMHCs alternatives, such as bumpers, seat structures, and steering wheels, manufacturers can enhance fuel efficiency and recyclability¹,². These composites are often categorized as non-weldable due to the formation of poor solidification microstructures, voids, micro-cracks, shrinkage pores, brittle intermetallic compounds (IMCs) and porosity within the fusion zone³,⁴. Moreover, welded joints in these composites typically exhibit a substantial loss in mechanical properties compared to the base material. These factors render conventional welding processes or traditional welding methods including arc welding and laser welding unsuitable for joining these AMMHCs⁵,⁶. Solid-state welding techniques provide an attractive alternative for materials that are difficult to fusion-weld due to their lower welding temperatures⁷.

FSW is a solid-state joining technology that can mitigate or eliminate the issues associated with fusion welding techniques. FSW, a significant advancement in metal joining, was invented at The Welding Institute (TWI) in 1991⁸. Initially recognized for its effectiveness in joining aluminium alloys through a solid-state process, FSW has since expanded its application to include relatively harder metals and even plastics⁹. The standard FSW tool configuration consists of a solid cylindrical tool with a terminating pin. This tool is rotated and traversed along the interface of two rigidly clamped workpieces, supported by a backing plate. As the tool's shoulder makes contact with the workpiece surface, frictional heat is generated¹⁰. The shoulder area experiences a higher heat input compared to the pin. The intense heat and mechanical forces induce severe plastic deformation in the material surrounding the tool. The plasticized metal flows from the front of the tool to the trailing edge, where it is forged into a solid joint. FSW involves intricate interactions between heat generation, plastic deformation, and metallurgical processes¹¹. Friction and plastic deformation generate heat, which alters the microstructure and properties of the material. The kinetics of these processes are primarily influenced by temperature and strain rate, while microstructure evolution affects energy transfer within the system. A comprehensive understanding of heat transfer and material flow necessitates a strong coupling of thermal, mechanical, and metallurgical factors¹². The centre of the stir zone (SZ) undergoes dynamic recrystallization, followed by recovered microstructure in the surrounding regions at lower deformation and temperature levels. This process increases grain surface energy and the number of grain boundaries. A portion of the plastic deformation energy is stored within the thermo-mechanically affected zone (TMAZ) as increased dislocation densities within deformed grains. The heat-affected zone (HAZ) is primarily influenced by temperature through diffusional heat transfer and exhibits a microstructure similar to the base material¹³,¹⁴.

The automotive industry heavily relies on AA6092 aluminium alloy, renowned for its superior strength compared to AA6082. However, research on the FSW of AA6092 composites remains limited, with only a few studies available in the literature. Verma et al.¹⁵ employed a Central Composite Design (CCD) within a Response Surface Methodology (RSM) framework to optimize significant FSW process parameters (rotational speed, feed rate, and tilt angle) for AA7039 Armor-marine grade aluminium. Additionally, optimal conditions for maximum UTS (477 MPa) and TE (19.9%) exceeding base material values were identified at a rotational speed of 1337.5 rpm, a feed rate of 37.5 mm/min, and a tilt angle of 1.7°.

Acharya et al.¹⁶ conducted FSW on AA6092/17.5 SiC-T6 composite using a 2° tool tilt angle and a constant WS of 1 mm/s, varying the TRS with a taper pin profiled tool. Microhardness testing indicated that the minimum and maximum hardness values were achieved at 1500 rpm and 2000 rpm, respectively. Additionally, the highest impact strength of 21.6 J was observed at both 1000 rpm and 1500 rpm, while the maximum joint efficiency of 84% was attained at 1500 rpm under tensile loading. Salih et al.¹⁷ investigated the impact of FSW on the metallurgical and mechanical properties of AA6092/SiC/17.5p-T6 AMC by varying tool rotation and traverse speeds. Their findings revealed that the optimal combination of process parameters, leading to a maximum ultimate tensile strength (UTS) and a joint efficiency of 75%, was a rotational speed of 1500 rpm and a traverse speed of 100 mm/min. Pandiyarajan et al.¹⁸ studied the metallurgical and mechanical properties of friction stir welded stir cast AA6061/6%ZrO₂/2%C hybrid metal matrix composites (MMCs). The study concluded that a fine-grained microstructure, leading to a maximum hardness of 53 Hardness Rockwell B (HRB), was achieved in friction stir welded MMCs at a TRS of 850 rpm, an AL of 5 kN, and a WS of 48 mm/min.

Sameer et al.¹⁹ investigated the FSW of dual-phase 600 steel and AA6082-T6 aluminum alloy using a tungsten carbide tool. Their findings revealed that the optimal process parameters, leading to a maximum UTS of 240 MPa and a joint efficiency of 85%, were a TRS of 710 rpm, a WS of 40 mm/min, a TTA of 0.5°, and a tool pin offset of 1.3 mm. Additionally, the highest microhardness of 246 HV was observed within the stir zone. Khanna et al.²⁰ optimized FSW process parameters such as TRS, TTA, and AL for AA 8011-H14 aluminum alloy using Taguchi analysis. The study aimed to investigate the impact of these parameters on UTS and microhardness. The optimized parameters for maximum UTS (84.44 MPa) and microhardness (36.4 HV) were determined to be a TRS of 1500 rpm, a TTA of 1°, and AL of 50 mm/min. Abdullah et al.²¹ examined the influence of partial-contact TTA (0°, 1.5°, and 3°) on the mechanical and microstructural properties of AA1050 alloy friction stir welds (FSWs). They concluded that the optimal 0° TTA sample exhibited 45% of the base metal's strength, a peak temperature of 336°C, an ultimate tensile strength of 33 MPa, 75% elongation relative to the base metal, and an average stir zone hardness of 25 HV.

Das et al.²² presented a comprehensive review of the impact of friction stir processing (FSP) on the microstructure, mechanical properties, and tribological behavior of aluminum 2xxx series alloys. The study emphasizes that FSP, as a solid-state processing technique, significantly refines grain structures, eliminates casting defects, and homogenizes the microstructure, resulting in improved mechanical strength in these alloys. Kumar et al.²³ examined the effects of higher traverse speeds on the microstructural, mechanical, and force-torque characteristics of friction stir welded third-generation aluminum-lithium (Al-Li) alloys. The study revealed that an increase in traverse speed led to finer grain structures within the weld nugget zone, thereby enhancing mechanical properties such as tensile strength and hardness.

Kumar et al.²⁴ investigated the influence of tool tilt angle on the physical, thermal, and mechanical properties of friction stir welded Al-Cu-Li alloys. Their study highlights that optimizing the tool tilt angle is essential for achieving high-quality welds. An appropriate tilt angle improved material flow during welding, promoting a more refined microstructure with fewer defects. Consequently, this enhancement led to improved mechanical properties, such as increased tensile strength and hardness. Kesharwani et al.²⁵ investigated the impact of the tool velocity ratio on force-torque dynamics and mechanical properties in friction stir welded 2050-T84 Al-Li alloy plates. It is indicated that variations in the tool velocity ratio significantly affect the welding forces and torques encountered during the process.

Recent years have witnessed a surge in research on FSW of Aluminum Metal Matrix Composites (AMMCs). However, a comprehensive understanding of FSW for AA6092/B₄C/ZrO₂ composites, particularly regarding joint performance metrics like weld nugget hardness (WNH), ultimate tensile strength (UTS), and percent elongation (PE), remains elusive. This study aims to bridge this gap by investigating the FSW of AA6092/ B₄C/ ZrO₂ composites. To minimize experimental runs, a four-factor, five-level central composite rotatable design matrix was employed. Three regression models were developed to correlate significant process parameters—TRS, WS, AL, and TTA with UTS, PE, and WNH of the FSWed AA6092/ B₄C/ ZrO₂ composites. Subsequently, the developed regression models were optimized using the generalized reduced gradient method to achieve maximum UTS, PE, and WNH.

2. Investigative Framework

2.1. Fabrication of AA6092/ B₄C/ ZrO₂ metal matrix composite

The chemical composition of the AA6092 alloy is detailed in Table 1. In the current work, AA6092 grade Aluminium alloy is employed as the metal matrix The selection of AA6092 alloy over other aluminum series such as 2xxx, 7xxx, 8xxx, or Al-Li alloys is typically based on a combination of mechanical properties (Balanced Strength and Toughness), Superior Corrosion Resistance, Excellent Weldability, Machinability, processability, Thermal Stability and Fatigue Resistance. Table 2 presents the properties of B₄C reinforcement particulates of size 90 Mesh. B₄C and ZrO₂ are employed as reinforcement particulates. Boron carbide (B₄C) exhibits outstanding thermal and chemical stability, low density, extreme hardness, excellent neutron absorption, and ease of net shape manufacturing. These characteristics make it ideal for industrial and nuclear applications, including reactor control rods, wire drawing and ceramic forming dies, neutron shielding, nozzles, and armor. Zirconium dioxide (ZrO₂) offers exceptional fracture toughness, low thermal conductivity, and high resistance to mechanical stress and crack propagation. These properties make it well-suited for applications in medical devices, electronic components, oxygen sensors, fuel cell membranes, and engine valve seats.

Table 1
The chemical composition of AA6092 alloy matrix.

Element	Mg	Si	Fe	Mn	Cu	Cr	Zn	Ti	Al
Wt. %	1.2	0.4	0.3	0.15	0.7	0.15	0.25	0.15	Balance

Table 2
Mechanical and thermal properties of ZrO₂ and B₄C.

S.No.	Property	Unit	Value
			ZrO2	B4C
			(99.9% purity)	(99.9% purity)
1	Density	g/cc	5- 6.15	2.3 - 2.55
2	Young’s Modulus	GPa	100 – 250	362 – 472
3	Hardness	GPa	5.5 - 15.75	38.1 – 44.1
4	Fracture Toughness	MPa/m	1 – 8	2.5 – 5
5	Thermal Conductivity	W/mK	1.7 - 2.7	17 – 42
6	Coefficient of Thermal Expansion	10-6/ K	2.3 - 12.2	3.2 – 9.4

The samples are fabricated with varying compositions of B₄C and ZrO₂, as detailed in Table 3.

Table 3
Composition of Matrix and Reinforcement Particulates of AMMHCs.

Sample No		1	2	3	4	5	6	7
Composition in wt.%	AA6092	100	96	92	92	92	88	84
	B4C	0	2	4	5	3	6	8
	ZrO2	0	2	4	3	5	6	8
UTS (MPa)		448.7	468.48	483.7	492.56	502	474.63	470.18
PE (%)		6.52	6.96	7.52	7.72	7.81	7.22	6.92
Microhardness (HRB)		163	165.3	170.5	171.5	172.5	171.2	170.5

AA6092/ B₄C/ ZrO₂ composite was produced using the stir casting method. A custom-designed electric stir casting furnace with a bottom pouring setup was used for fabrication. Cleaned, extruded AA6092 rods (25 mm in diameter) were placed into a coated stainless-steel crucible, and the furnace was heated to 1000 °C. A coated stainless-steel stirrer, driven by an electric motor, was employed to stir the melt, ensuring uniform distribution of B₄C and ZrO₂ reinforcement within the molten alloy. Both the crucible and stirrer were coated to avoid contamination at high temperatures. The pre-heated B₄C and ZrO₂ particulates with different weight proportions are added was introduced into the melt at the vortex. To improve the wettability of the B₄C and ZrO₂ with the AA6092 matrix, 2 wt.% magnesium was added to the melt. The B₄C and ZrO₂ were stirred into the melt for 260 s, followed by an additional 1200 s of stirring before being poured into a preheated permanent mold (100 mm × 50 mm × 50 mm) via the bottom pouring arrangement. Argon gas was supplied at a constant flow rate of 2 lpm into the furnace once it reached 650 °C, continuing until the composite was poured²⁶-³¹.

Multiple AA6092/ B₄C /ZrO₂ composites with 3 wt.% B₄C and 5 wt.% ZrO₂ content were fabricated since it has higher UTS, Microhardness, and plates measuring 100 mm × 50 mm × 5 mm (Figure 1) were cut from the composite block for FSW trials, parameter determination, and FSW of composites based on the design matrix. SEM images in Figure 2a show the stir cast AA6092 matrix alloy, while Figure 2b display SEM images of AA6092/ B₄C/ZrO₂ composites. The SEM analysis confirms that B₄C and ZrO₂ particulates are uniformly distributed and embedded within the primary aluminium dendrites, rather than accumulating in the inter-dendritic regions. SEM analysis reveals that the reinforcement particulates (ZrO₂ and B₄C) serve as barriers to dendritic growth along the grain boundaries. The reduction in dendritic growth enhances the ultimate tensile strength (UTS) and micro-hardness of MMCs. Additionally, the analysis highlights the extent of cluster accumulation and its growth with the addition of ZrO₂ and B₄C particulates, which significantly contribute to the improved strength of MMCs.

Figure 1
The fabricated stir cast AA6092/3%B₄C/5%ZrO₂ composite plate.

Figure 2
(a) SEM analysis of AA6092 alloy and (b) AA6092/3%B₄C/5%ZrO₂ composites.

2.2. Identifying key process parameters for FSW

The literature review indicated that the mechanical properties of Friction Stir Welded (FSW) Aluminium Matrix Metal Composite (AMMC) joints are significantly influenced by process parameters like TRS, WS, AL, and TTA. Given the superior joint strength demonstrated by cylindrical tool pin profiles, FSW tool pins of this profile, without draft, were fabricated from H13 tool steel¹⁰-¹². The chemical composition of H13 tool steel is presented in Table 4. Cylindrical pins, measuring 5 mm in diameter and 4.8 mm in length, with a 15 mm shoulder diameter and 12 mm shoulder length, were manufactured using CNC turning and EDM techniques. Subsequent oil hardening resulted in a hardness of 60-62 Hardness Rockwell C (HRC). This geometry ensures uniform heat generation and effective stirring, which contributes to a refined microstructure and enhanced mechanical properties¹⁴,¹⁵. Figure 3 illustrates the tool's geometry and dimensions.

Table 4
Chemical Composition of tool steel H13.

Elements	Cr	Mo	Si	V	C
Content (%)	4.75-5.50	1.10-1.75	0.80-1.20	0.80-1.20	0.32-0.45
Elements	Ni	Cu	Mn	S	P
Content (%)	0.3	0.25	0.20-0.50	0.03	0.03

Figure 3
Detailed specifications of the FSW tool geometry.

2.3. Determining the feasible range of FSW process parameters

Numerous trials on AA6092/3%B₄C/5%ZrO₂ composites were conducted to establish the feasible range of FSW process parameters—TRS, WS, and AL. These parameters were adjusted to prevent macro-defects like tunnel defects, pinholes, and cracks. The feasible range for AMMHCs is narrower than for unreinforced alloys due to reduced ductility caused by ceramic particles¹⁸. This limitation is further exacerbated for cast AMMHCs. To facilitate experimental design, parameter limits were coded: +2 for the upper limit, -2 for the lower limit, and intermediate values calculated using Equation 1³².

$$E_i=2\left[2E-\left(E_{max}+E_{min}\right)\right]/(E_{max}-E_{min})$$ (1)

where E_i is the essential coded value of a variable E; E is any value of the variable between E_max and E_min; E_max is the upper limit of the variable; E_min is the lower limit of the variable. The selected levels of the process parameters with their notations and units are depicted in Table 5.

Table 5
Process parameters and its levels.

S. No.	Process Parameter	Notation	Unit	Levels
				-2	-1	0	1	2
4.	Tool Rotational Speed	TRS	rpm	1000	1100	1200	1300	1400
5.	Welding Speed	WS	mm/min	25	40	55	70	85
6.	Axial Load	AL	kN	3	4	5	6	7
7.	Tool Tilt Angle	TTA	°	0.5	1	1.5	2	2.5

2.4. Constructing the experimental design matrix

A four-factor, five-level central composite design was employed for this study, comprising 31 experimental conditions (Table 6). The design included 16 factorial points (2^4), 8 axial points (+/- 2), and 7 center points (0). This experimental strategy allowed for a comprehensive exploration of the process parameter space and efficient estimation of both linear and quadratic effects.

Table 6
Design matrix and experimental results.

Run	Tool rotational speed (rpm)	Welding speed (mm/min)	Axial force (kN)	Tool Tilt Angle (°)	UTS	PE	Joint efficiency (%)	WNH
					(MPa)	(%)		(HRB)
1	1200	55	5	1	552.64	9.56	93.94	203
2	1200	55	5	0.5	506.74	8.27	90.41	190.5
3	1200	55	3	2	459.02	6.52	81.46	173
4	1200	55	5	2	480.44	6.96	93.70	175.5
5	1300	40	4	2	501.37	7.94	87.13	186.5
6	1200	55	7	1	486.55	7.52	86.63	182.5
7	1300	40	6	1.5	471.18	6.42	88.88	168.9
8	1300	70	4	2	485.09	7.26	84.15	182.5
9	1100	40	6	1	472.15	6.68	89.08	174.5
10	1100	70	4	1	484.82	7.09	84.11	182.5
11	1200	55	5	2	505.76	8.22	90.23	190.5
12	1200	55	5	1	507.95	8.42	90.64	192.5
13	1200	85	5	1	457.58	4.98	81.19	158.5
14	1200	55	5	2	508.36	8.97	90.72	192.5
15	1100	70	6	1.5	466.14	5.85	87.88	166
16	1100	70	4	1	460.7	5.64	86.79	165.5
17	1000	55	5	1.5	469.83	6.19	83.49	167.7
18	1100	40	4	1.5	477.51	6.93	90.14	175.5
19	1100	40	6	1.5	501.68	8.01	87.19	186.5
20	1200	55	5	2	505.76	8.22	90.23	190.5
21	1300	70	4	1	473.71	6.9	89.39	174.5
22	1300	70	6	2.5	469.36	5.91	88.52	166.5
23	1200	25	5	1.5	471.38	6.6	83.78	173.5
24	1400	55	5	1.5	483.77	7.08	86.10	181.5
25	1200	55	5	1.5	507.95	8.42	90.64	191.5
26	1100	70	6	1.5	480.14	6.96	83.25	177.6
27	1300	40	6	2	494.85	7.61	85.94	184.5
28	1300	40	4	1.5	486.63	7.54	91.96	183.5
29	1300	70	6	1.5	498.56	7.62	86.62	185.5
30	1200	55	5	1.5	508.62	9.07	90.77	196.5
31	1100	40	4	1.5	502.03	8.15	87.25	186.5

2.5. Conducting the experiments based on the statistical design of experiments (DOE)

A square butt joint configuration (100 mm × 100 mm × 5 mm) was used for all experiments, following the design matrix outlined in Table 6. Before welding, the plate surfaces were cleaned by wire brushing followed by 2000-grit emery paper cleaning and acetone chemical cleaning. A single-pass butt welding procedure was employed, with the welding direction parallel to the plate's rolling direction. To minimize the impact of unknown variables, the 31 weld runs were conducted in random order using a semi-automatic FSW machine. For each test run, the TRS, WS, and AL were adjusted according to the design matrix. The tool pin was inserted into the joint interface, and the shoulder was pressed against the plates to initiate the welding process. A dwell period was maintained to generate sufficient frictional heat for plastic deformation. Once the desired dwell time (The operator visually assessed the material flow around the tool shoulder to determine when sufficient dwell time had been achieved) was reached, the machine table was moved at a constant speed, and the axial force was maintained until the weld was completed.

2.6. Recording the response variables

Three tensile specimens were machined from each welded plate, perpendicular to the welding direction, to ASTM E8M-04 standards. Ultimate Tensile Strength (UTS) and Percentage Elongation (PE) were measured at room temperature using a Computerized Universal Testing Machine (Associated Scientific Engineering Works, F-100, 5 Ton capacity). Joint efficiency was calculated using Equation 2³³-³⁵ and is reported in Table 4 for all 31 welded joints:

$$JointEfficiency\left(\%\right)=\left(UT{S}_{welded}{}_{joint}/UT{S}_{composite}\right)\times 100$$ (2)

Rockwell hardness testing was conducted on weld nuggets using a Wilson Wolpert tester (Germany), adhering to ASTM E10-08 standards. Measurements were taken at three points: one within the weld nugget zone (WNZ) and two in the heat-affected zone (HAZ). Transverse sections of the welded plate were etched with a solution of 4g KMnO₄ and 1g NaOH in 100ml distilled water. Metallurgical analysis was performed using an optical microscope (De-Wintour Inverted Trinocular Metallurgical Microscope) and a scanning electron microscope (FEI SEM-Apreo Model).

3. Deriving Empirical Relationships Based on Experimental Design and Analysis of Variance

The mechanical properties of friction stir welded (FSW) AA6092 composite joints are significantly influenced by various process parameters. In this study, the response variables – Ultimate Tensile Strength (UTS), Percentage Elongation (PE), and Weld Nugget Hardness (WNH) – were investigated as functions of four key process parameters: TRS, WS, AL, and the TTA. To establish the relationship between these variables, a response surface methodology (RSM) was employed³⁶,³⁷. The functional relationships between the response variables and the process parameters can be expressed as:

$$UTS=f\left(TRS,WS,AL,TTA\right)$$ (3)

$$PE=f\left(TRS,WS,AL,TTA\right)$$ (4)

$$WNH=f\left(TRS,WS,AL,TTA\right)$$ (5)

The second-order polynomial (regression) Equation 6 employed to denote the response surface is expressed by

$$X=a_0+\sum a_i{x}_i+\sum a_{ii}{x}_i{}^2+\sum a_{ij}{x}_i{x}_j+\epsilon$$ (6)

Second-order polynomial regression is employed to denote the ‘X’ response surface. Where a₀ is the average response; a_i, a_ii and a_ij are coefficients reliant on the major and interaction influences of the parameters; and ε is the statistical error.

The coefficients of the regression model were determined using statistical software (Design-Expert) and subjected to significance testing at a 95% confidence level. Insignificant terms were eliminated from the model to enhance its predictive accuracy and reduce model complexity. The final, simplified regression models for predicting UTS, PE, and WNH are presented in Equations 7, 8, and 9, respectively, in coded form³⁸-⁴⁴. Tables 7, 8, and 9 provide a detailed analysis of variance (ANOVA) for each response variable, highlighting the significance of the various process parameters and their interactions.

Table 7
ANOVA results for Ultimate Tensile Strength (UTS).

Source	Sum of Squares	df	Mean Square	F-value	p-value
Model	8761.42	14	625.82	2.70	0.0297	significant
A-Tool Rotational Speed	567.90	1	567.90	2.45	0.1368
B-Welding Speed	677.92	1	677.92	2.93	0.1063
C-Axial Load	186.48	1	186.48	0.8059	0.3827
D-Tool Tilt Angle	523.18	1	523.18	2.26	0.1522
AB	715.08	1	715.08	3.09	0.0979
AC	71.78	1	71.78	0.3102	0.5853
AD	694.82	1	694.82	3.00	0.1024
BC	574.32	1	574.32	2.48	0.1347
BD	534.86	1	534.86	2.31	0.1479
CD	3.79	1	3.79	0.0164	0.8997
A2	2090.17	1	2090.17	9.03	0.0084
B2	4467.21	1	4467.21	19.31	0.0005
C2	1511.06	1	1511.06	6.53	0.0212
D2	380.63	1	380.63	1.64	0.2179
Residual	3702.38	16	231.40
Lack of Fit	1495.24	8	186.90	0.6775	0.7027	not significant
Pure Error	2207.14	8	275.89
Cor Total	12463.80	30

• R-Squared: 0.7029, adj R-squared: 0.4430, pred R-squared: 0.0612, adeq precision: 5.3136³⁸

Table 8
ANOVA results for Percentage Elongation (PE).

Source	Sum of Squares	df	Mean Square	F-value	p-value
Model	26.66	14	1.90	3.96	0.0051	significant
A-Tool Rotational Speed	1.56	1	1.56	3.25	0.0904
B-Welding Speed	3.19	1	3.19	6.64	0.0203
C-Axial Load	0.0518	1	0.0518	0.1077	0.7470
D-Tool Tilt Angle	0.8160	1	0.8160	1.70	0.2110
AB	1.81	1	1.81	3.76	0.0704
AC	0.3783	1	0.3783	0.7872	0.3881
AD	0.9910	1	0.9910	2.06	0.1703
BC	0.8081	1	0.8081	1.68	0.2131
BD	0.9298	1	0.9298	1.93	0.1833
CD	0.0319	1	0.0319	0.0663	0.8000
A2	6.66	1	6.66	13.86	0.0019
B2	13.78	1	13.78	28.67	< 0.0001
C2	2.19	1	2.19	4.56	0.0484
D2	1.29	1	1.29	2.67	0.1215
Residual	7.69	16	0.4806
Lack of Fit	2.33	8	0.2916	0.4354	0.8696	not significant
Pure Error	5.36	8	0.6697
Cor Total	34.35	30

• R-Squared: 0.7761, adj R-squared: 0.5802, pred R-squared: 0.1606, adeq precision: 7.2478³⁸

Table 9
ANOVA results for Weld Nugget Hardness (WNH).

Source	Sum of Squares	df	Mean Square	F-value	p-value
Model	2431.82	14	173.70	3.25	0.0133	significant
A-Tool Rotational Speed	232.11	1	232.11	4.34	0.0536
B-Welding Speed	211.25	1	211.25	3.95	0.0643
C-Axial Load	0.9999	1	0.9999	0.0187	0.8929
D-Tool Tilt Angle	144.51	1	144.51	2.70	0.1197
AB	155.84	1	155.84	2.91	0.1071
AC	34.39	1	34.39	0.6430	0.4344
AD	179.63	1	179.63	3.36	0.0855
BC	79.50	1	79.50	1.49	0.2404
BD	84.64	1	84.64	1.58	0.2264
CD	0.3504	1	0.3504	0.0066	0.9365
A2	627.16	1	627.16	11.73	0.0035
B2	1337.96	1	1337.96	25.02	0.0001
C2	234.59	1	234.59	4.39	0.0525
D2	165.22	1	165.22	3.09	0.0979
Residual	855.69	16	53.48
Lack of Fit	329.04	8	41.13	0.6248	0.7395	not significant
Pure Error	526.65	8	65.83
Cor Total	3287.51	30

• R-Squared: 0.7397, adj R-squared: 0.5120, pred R-squared: -0.1845, adeq precision: 6.4680³⁸

$$\begin{array}{l}UTS,\left(MPa\right)=-675.0683+1.8026xTRS-\\ 0.1134xWS+98.3642xAL-205.0473xTTA+\\ \left(0.0059xTRSxWS\right)-\left(0.02574xTRSxAL\right)+\\ \left(0.2701xTRSxTTA\right)+\left(0.4482xWSxAL\right)-\\ \left(1.3495xWSxTTA\right)+\left(1.3760xALxTTA\right)-\\ \left(0.001xTRS²\right)-\left(0.0689xWS²\right)-\\ \left(9.1155xAL²\right)-\left(21.3345xTTA²\right)\end{array}$$ (7)

$$\begin{array}{l}PE,\left(\%\right)=-67.6021+0.1132xTRS+\\ 0.0382xWS+4.6527xAL-6.5415xTTA+\\ \left(0.0003xTRSxWS\right)-\left(0.0019xTRSxAL\right)+\\ \left(0.0102xTRSxTTA\right)+\left(0.0168xWSxAL\right)-\\ \left(0.0563xWSxTTA\right)+\left(0.1261xALxTTA\right)-\\ \left(5.5262e-05xTRS²\right)-\left(0.00383xWS²\right)-\\ \left(0.3473xAL²\right)-\left(1.240xTTA²\right)\end{array}$$ (8)

$$\begin{array}{l}WNH,\left(HRB\right)=-506.2484+1.0531xTRS+0.5926xWS+47.7208xAL-101.6459xTTA+\\ \left(0.0028xTRSxWS\right)-\left(0.01782xTRSxAL\right)+\left(0.1373xTRSxTTA\right)+\left(0.1668xWSxAL\right)-\\ \left(0.5369xWSxTTA\right)+\left(0.4182xALxTTA\right)-\left(0.0005xTRS²\right)-\left(0.0377xWS²\right)-\\ \left(3.5916xAL²\right)-\left(14.0561xTTA²\right)\end{array}$$ (9)

4. The Influence of FSW Process Parameters (TRS, WS, AL, TTA) on the Mechanical Properties (UTS, PE, WNH)

4.1. Ultimate Tensile Strength (UTS)

The severe plastic deformation and dynamic recrystallization during FSW result in a fine, equiaxed grain structure in the weld nugget. The presence of B₄C and ZrO₂ particulates further restricts grain growth, leading to improved UTS and WNH. The stirring action of FSW helps distribute B₄C and ZrO₂ particles uniformly within the weld zone, minimizing clustering and ensuring effective load transfer. This uniform dispersion enhances the mechanical interlocking and strengthens the weld joint. ZrO₂ and B₄C particulates act as obstacles to dendritic growth, refining the microstructure and contributing to increased hardness and strength. The fine dispersions of B₄C and ZrO₂ particles hinder dislocation movement, enhancing the UTS through the Orowan strengthening effect. FSW eliminates issues like porosity and cracks typically found in fusion welding, leading to improved joint integrity and mechanical properties. The intense plastic deformation and heat during FSW may facilitate precipitation hardening of the AA6092 matrix, further enhancing the hardness of the weld nugget.

In this section, it is delved into the intricate relationship between FSW process parameters and the resulting mechanical properties of the AA6092 composite joints, specifically focusing on Ultimate Tensile Strength (UTS), Percentage Elongation (PE), and Weld Nugget Hardness (WNH). To gain deeper insights into these interactions, it is analyzed the impact of two process parameters on each response variable while keeping the third parameter fixed at its average level.

The perturbation plot for UTS (Figure 4) provides a visual representation of how variations in each process parameter influence the UTS within the experimental design space. This plot clearly demonstrates that TRS is the most significant factor affecting UTS, followed by WS and AL. Interestingly, TTA emerges as the dominant factor influencing UTS, surpassing the impact of TRS, AL, and WS.

Figure 4
Perturbation plot (influence of process parameters on the UTS).

Figures 5, 6, and 7 graphically depict the intricate interplay between the process parameters (TRS, WS, AF, and TTA) on the Ultimate Tensile Strength (UTS) of the FSWed AA6092 composite joints. Figure 5a and 5b illustrate the combined effect of TRS and WS on UTS, while maintaining AL at 5 kN and TTA at 1.5°. The 2D contour plot in Figure 5a provides a visual representation of the UTS values across different combinations of TRS and WS. The concentric circles represent contours of constant UTS, with the optimal UTS of approximately 514.46 MPa achieved at a TRS of 1200 rpm and a WS of 55 mm/min. Figure 6 explores the interaction between AL and TRS on UTS, while keeping WS and TTA constant at 55 mm/min and 1.5°, respectively. Both the 2D and plots in Figure 6 indicate that the optimal UTS of approximately 514.46 MPa is achieved at a TRS of 1200 rpm and an AL of 5 kN.

Figure 5
(a) 2D Contour plot, (b) Contour plots (impact of TRS and WS on UTS of FSW Joint).

Figure 6
(a) 2D Contour plot, (b) Contour plots (influence of TRS and AL on UTS of FSW Joint).

Figure 7
(a) 2D Contour plot, (b) Contour plots (influence of TRS and TTA on UTS of FSW Joint).

Figure 7 delves into the synergistic effect of TTA and TRS on UTS, while keeping AL and WS) constant at 5 kN and 55 mm/min, respectively. The optimal UTS of approximately 515.09 MPa is achieved at a TRS of 1200 rpm and a TTA of 1.5°.

Figure 8 explores the combined influence of AL and WS on UTS, with TRS and TTA fixed at 1200 rpm and 1.5°, respectively. The optimal UTS of approximately 515.09 MPa is attained at a WS of 55 mm/min and an AL of 5 kN. Figure 9 investigates the interaction between TTA and WS, while maintaining AL and TRS at 5 kN and 1200 rpm, respectively. The optimal UTS of approximately 515.09 MPa is achieved at a WS of 55 mm/min and a TTA of 1.5°. Finally, Figure 10 examines the combined effect of TTA and AL on UTS, with TRS and WS fixed at 1200 rpm and 55 mm/min, respectively. The optimal UTS of approximately 515.09 MPa is attained at a TTA of 1.5° and an AL of 5 kN.

Figure 8
(a) 2D Contour plot, (b) Contour plots (influence of AL and WS on UTS of FSW Joint).

Figure 9
(a) 2D Contour plot, (b) Contour plots (influence of TTA and WS on UTS of FSW Joint).

Figure 10
(a) 2D Contour plot, (b) Contour plots (influence of TTA and AL on UTS of FSW Joint).

4.2. Weld Nugget Microhardness (WNH)

The microhardness measurements reveal a significant increase in hardness within the stir zone compared to the base AA6092 alloy, which exhibits a hardness of 172.5 HRB. This enhancement in hardness can be attributed to two primary factors namely Grain Refinement and Dispersion Strengthening. The intense plastic deformation during the FSW process results in a substantial reduction in grain size within the stir zone. This fine-grained microstructure significantly improves the mechanical properties, including hardness, as per the Hall-Petch relationship, which establishes a direct correlation between decreasing grain size and increasing hardness. The presence of intermetallic particles and uniformly dispersed B₄C and ZrO₂ particulates within the weld nugget further contributes to the increased hardness. These particles act as obstacles to dislocation motion, impeding plastic deformation and thereby enhancing the material's strength and hardness through a mechanism known as Orowan strengthening. The heat-affected zone (HAZ), while experiencing some degree of grain refinement, does not undergo the same intense plastic deformation as the stir zone. Consequently, the hardness of the HAZ remains lower than that of the stir zone. The perturbation plot in Figure 11 visually depicts the impact of FSW process parameters on WNH. It is evident that, regardless of the TRS, the weld nugget consistently exhibits higher hardness than the base metal. Furthermore, the plot highlights the significant influence of TTA on WNH, followed by TRS, AL, and WS.

Figure 11
Perturbation plot (influence of process parameters on the WNH).

The interaction effects of the process parameters, namely TRS, WS, AL, and TTA, on WNH are comprehensively illustrated in Figures 12 to 17. Figure 12a and 12b depict the combined influence of TRS and WS on WNH, while maintaining AL constant at 5 kN. The 2D contour plot in Figure 12a visually represents the variation in WNH as a function of TRS and WS. The optimal WNH of 195.16 HRB is achieved at a TRS of 1200 rpm and a WS of 55 mm/min.

Figure 12
(a) 2D Contour plot, (b) Contour plots (influence of TRS and WS on WNH of FSW Joint.

Figure 13
(a) 2D Contour plot, (b) Contour plots (influence of TRS and AL on WNH of FSW Joint).

Figure 14
(a) 2D Contour plot, (b) Contour plots (influence of TTA and WS on WNH of FSW Joint).

Figure 15
(a) 2D Contour plot, (b) Contour plots (influence of TTA and AL on WNH of FSW Joint).

Figure 16
(a) 2D Contour plot, (b) Contour plots (influence of TTA and WS on WNH of FSW Joint).

Figure 17
Contour plots (a) 2D Contour plot, (b) (influence of TTA and AL on WNH of FSW Joint).

Figure 13 explores the interaction between AL and TRS on WNH, keeping WS and TTA constant at 55 mm/min and 1.5°, respectively. The optimal WNH of approximately 195.16 HRB is observed at a TRS of 1200 rpm and an AL of 5 kN. Figure 14 investigates the combined effect of TTA and WS on WNH, while maintaining TRS and AL constant at 1200 rpm and 5 kN, respectively. The optimal WNH of 195.16 HRB is attained at a WS of 55 mm/min and a TTA of 1.5°.

Figure 15 delves into the interaction between TTA and AL on WNH, keeping TRS and WS constant at 1200 rpm and 55 mm/min, respectively. The optimal WNH of approximately 195.16 HRB is achieved at a TTA of 1.5° and an AL of 5 kN. Figure 16 explores the combined effect of TTA and WS on WNH, while maintaining TRS and AL constant at 1200 rpm and 5 kN, respectively. The optimal WNH of approximately 195.16 HRB is attained at a WS of 55 mm/min and a TTA of 1.5°.

Finally, Figure 17 investigates the interaction between W and AL on WNH, keeping TRS and WS constant at 1200 rpm and 55 mm/min, respectively. The optimal WNH of approximately 195.16 HRB is achieved at a TTA of 1.5°.and an AL of 5 kN.

4.3. Percentage elongation

FSW induces dynamic recrystallization, producing a fine, equiaxed grain structure in the weld nugget. Smaller grains improve ductility by enhancing grain boundary sliding and delaying crack initiation during tensile loading. The stirring action ensures a uniform distribution of B₄C and ZrO₂ particulates, reducing particle clustering. This prevents localized stress concentration and crack initiation, enhancing elongation. FSW removes porosity, voids, and segregation commonly found in fusion welding. The absence of these defects improves the material’s ability to deform plastically before failure. Unlike fusion welding, FSW occurs below the melting point, reducing residual stresses and avoiding brittle intermetallic phases. Lower residual stress enhances the material’s ability to stretch under tensile loads, increasing elongation. ZrO₂ and B₄C particles reinforce grain boundaries, preventing premature grain boundary cracking. Strengthened grain boundaries contribute to a higher elongation percentage by allowing more uniform deformation. The fine grains and well-distributed reinforcement particles facilitate dislocation motion, delaying material failure. This increased plasticity results in higher ductility and elongation.

Figure 18 presents a perturbation plot that delves into the impact of FSW process parameters on the PE of an optimized design. A key observation is that, regardless of the operational level of TRS, the PE of the welded joints consistently surpasses that of the base metal. This signifies a significant enhancement in the ductility of the material post-welding. A closer examination of the plot reveals a hierarchy of influence among the process parameters. The weight percentage of TTA emerges as the most dominant factor affecting PE, followed by TRS, AL, and WS. These findings underscore the critical role of material composition and process kinetics in determining the mechanical properties of FSW joints.

Figure 18
Perturbation plot (influence of process parameters on the PE).

Figures 19 to 24 provide a comprehensive analysis of the interactive effects of TRS, WS, AL, and TTA on the PE of the welded joints.

Figure 19
(a) 2D Contour plot, (b) Contour plots (influence of TRS and WS on PE of FSW Joint.

Figure 20
(a) 2D Contour plot, (b) Contour plots (influence of TRS and AL on PE of FSW Joint).

Figure 21
(a) 2D Contour plot, (b) Contour plots (influence of TTA and WS on PE of FSW Joint).

Figure 22
(a) 2D Contour plot, (b) Contour plots (influence of TTA and AL on PE of FSW Joint).

Figure 23
(a) 2D Contour plot, (b) Contour plots (influence of TTA and WS on PE of FSW Joint).

Figure 24
(a) 2D Contour plot, (b) Contour plots (influence of TTA and AL on PE of FSW Joint).

Figure 19a presents a 2D contour plot visualizing the influence of TRS and WS on PE, while maintaining constant AL and TTA at 5 kN and 1.5 ° respectively. A concentric circle representation is employed, with the optimal PE value of 8.79% located at the plot’s centre. This optimal condition corresponds to a TRS of 1200 rpm and a WS of 55 mm/min. The surface plot in Figure 19b further corroborates this finding.

Figure 20 delves into the interaction between AL and TRS at a fixed WS of 55 mm/min and TTA of 1.5°. Both the 2D and plots indicate that the peak PE of approximately 8.79% is achieved at a TRS of 1200 rpm and an AL of 5 kN. Finally, Figure 21 explores the interactive effect of TTA and WS, keeping TRS at 1200 rpm and AL at 5 kN. The optimal PE of 8.79% is attained at a WS of 55 mm/min and a TTA of 1.5°. These findings collectively highlight the intricate interplay between process parameters and material composition in determining the mechanical properties of FSW joints.

Figure 22 illustrates the influence of TTA and AL on the Percentage Elongation (PE) of the Friction Stir Welded joint. The analysis is conducted at a constant TRS of 1200 rpm and a WS of 55 mm/min. Both the 2D contour and surface plots reveal that the optimal PE of approximately 8.79% is achieved at a TTA of 1.5° and an AL of 5 kN. Figure 23 explores the interactive effects of TTA and WS on PE, while maintaining a constant TRS of 1200 rpm and an AL of 5 kN. The 2D and plots indicate that the peak PE of approximately 8.79% is attained at a WS of 55 mm/min and a TTA of 1.5°. Similarly, Figure 24 investigates the combined impact of TTA and AL on PE at a fixed TRS of 1200 rpm and a WS of 55 mm/min. The optimal PE of approximately 8.79% is observed at an AL of 5 kN and a TTA of 1.5°. These findings underscore the complex interplay between process parameters and material composition in influencing the mechanical properties of FSW joints. By carefully optimizing these variables, it is possible to achieve significant enhancements in the ductility and overall performance of the welded components.

5. Results Derived from Optimization

Following a comprehensive optimization study aimed at achieving the desired mechanical properties in the welded joint, the optimal welding conditions were determined based on established criteria, as detailed in Table 10. The experimental and optimization results consistently indicate that a TRS of approximately 1200 rpm is crucial for attaining optimal UTS, PE, and WNH. Notably, the TTA emerges as the most influential parameter compared to other input variables in determining these responses. Table 11 presents the optimized FSW process parameters and predicted responses generated by the design expert software. Figure 25 further visualizes these findings through a contour plot and overlay plot, predicting an optimal UTS of 513.09 MPa, a PE of 8.7%, and a WNH of 194.92 HRB. These optimal values are anticipated at a TRS of 1279.18 rpm, a WS of 53.54 mm/min, an AL of 4.9 kN and a TTA of 1.5°.

Table 10
Optimization criteria used in this work.

Process Parameters / Responses	Goal	Minimum Limit	Maximum Limit	Importance
Tool Rotational Speed (rpm)	is in range	1100	1300	3
Welding Speed (mm/min)	is in range	40	70	3
Axial Load (kN)	is in range	4	6	3
Tool Tilt Angle (°)	is in range	1	1.5	3
Ultimate Tensile Strength (MPa)	maximize	457.58	552.64	5
Percentage Elongation (%)	maximize	4.98	9.56	5
Weld Nugget Hardness (HRB)	maximize	158.5	203	5

Table 11
Optimized FSW process parameters and responses predicted by design expert software.

Tool rotational speed (rpm)	Welding Speed (mm/min)	Axial load (kN)	Tool Tilt Angle (°)	UTS (MPa)	PE (%)	Microhardness (HRB)
1279.18	53.54	4.9	1.5	513.09	8.70	194.92

Figure 25
Contour plot and overlay plot for prediction plot of UTS, PE and WNH.

6. Validation Process for the Developed Model

To validate the empirical or mathematical model established using the desirability approach, a comparative analysis was conducted between the predicted values and the experimental results obtained from thirty-one experimental runs (Table 6). The experimental data was acquired through physical experimentation, while the predicted values were determined using the empirical equations generated by the design expert software. Table 12 presents a detailed comparison of the experimental and predicted values for Ultimate Tensile Strength (UTS), Percentage Elongation (PE), and Weld Nugget Hardness (WNH), along with the corresponding percentage errors. The percentage error for UTS ranged from - 0.78% to +1.23%, for PE from -1.0 to +1.46%, and for WNH from -1.30% to + 1.55%. These results demonstrate a high degree of accuracy in the newly developed model's ability to predict UTS, PE, and WNH values. The close proximity between the predicted and experimental values underscores the model's reliability and its potential to effectively guide future FSW process optimization efforts.

Table 12
Experimental and Predicted values for Thirty-One runs.

Run	UTS (MPa)			PE (%)			WNH (HRB)
	Experimental Value	Predicted Value	Error in %	Experimental Value	Predicted Value	Error in %	Experimental Value	Predicted Value	Error in %
1.	552.64	555.42	-0.50	9.56	9.5	0.63	203	202.87	0.06
2.	506.74	509.75	-0.59	8.27	8.24	0.36	190.5	189.57	0.49
3.	459.02	462.28	-0.71	6.52	6.56	-0.61	173	171.36	0.96
4.	480.44	482.84	-0.50	6.96	6.97	-0.14	175.5	175.51	-0.01
5.	501.37	503.72	-0.47	7.94	7.97	-0.38	186.5	183.7	1.52
6.	486.55	488.48	-0.40	7.52	7.43	1.21	182.5	183.02	-0.28
7.	471.18	474.78	-0.76	6.42	6.39	0.47	168.9	167.3	0.96
8.	485.09	481.87	0.67	7.26	7.28	-0.27	182.5	180.24	1.25
9.	472.15	473.13	-0.21	6.68	6.64	0.60	174.5	173.92	0.33
10.	484.82	482.97	0.38	7.09	7.18	-1.25	182.5	183.05	-0.30
11.	505.76	509.75	-0.78	8.22	8.24	-0.24	190.5	189.57	0.49
12.	507.95	509.75	-0.35	8.42	8.44	-0.24	192.5	189.57	1.55
13.	457.58	459.35	-0.39	4.98	4.94	0.81	158.5	158.62	-0.08
14.	508.36	509.75	-0.27	8.97	8.94	0.34	192.5	189.57	1.55
15.	466.14	465.53	0.13	5.85	5.89	-0.68	166	165.75	0.15
16.	460.7	459.45	0.27	5.64	5.61	0.53	165.5	165.27	0.14
17.	469.83	464.12	1.23	6.19	6.16	0.49	167.7	169.76	-1.21
18.	477.51	476.43	0.23	6.93	6.83	1.46	175.5	174.49	0.58
19.	501.68	500.49	0.24	8.01	8.04	-0.37	186.5	185.9	0.32
20.	505.76	509.75	-0.78	8.22	8.24	-0.24	190.5	189.57	0.49
21.	473.71	471.65	0.44	6.9	6.97	-1.00	174.5	174.95	-0.26
22.	469.36	465.76	0.77	5.91	5.9	0.17	166.5	166.39	0.07
23.	471.38	466.8	0.98	6.6	6.66	-0.90	173.5	171.26	1.31
24.	483.77	484.67	-0.19	7.08	7.07	0.14	181.5	179.32	1.22
25.	507.95	509.75	-0.35	8.42	8.44	-0.24	191.5	189.57	1.02
26.	480.14	484.46	-0.89	6.96	6.94	0.29	177.6	179.34	-0.97
27.	494.85	493.85	0.20	7.61	7.66	-0.65	184.5	183.89	0.33
28.	486.63	490.07	-0.70	7.54	7.58	-0.53	183.5	185.92	-1.30
29.	498.56	501.38	-0.56	7.62	7.69	-0.91	185.5	184.47	0.56
30.	508.62	509.75	-0.22	9.07	9.14	-0.77	196.5	195.57	0.48
31.	502.03	504.53	-0.50	8.15	8.18	-0.37	186.5	185.77	0.39

To validate the accuracy of the developed model under the predicted optimal welding conditions, three confirmation experiments were conducted. These experiments were carried out using a TRS of 1279.18 rpm, a WS of 53.54 mm/min, an AL of 4.9 kN, and a TTA of 1.5°. The results of these validation experiments are summarized in Table 13. A comparative analysis between the predicted and experimental values revealed a high degree of agreement, with maximum percentage errors of +0.18% for UTS, +1.15% for PE, and +0.55% for WNH. These negligible errors further substantiate the model's reliability and its ability to accurately predict the mechanical properties of FSW joints under optimal process conditions.

Table 13
Validation of test results.

Run	Tool Rotational Speed (rpm)	Welding Speed (mm/min)	Axial Force (kN)	Tool Tilt Angle (°)	UTS (MPa)		Error in %	Percentage Elongation (%)		Error in %	Weld Nugget Hardness (HRB)		Error in %
					Actual value	Predicted value		Actual value	Predicted value		Actual value	Predicted value
1	1279.18	53.54	4.9	1.5	514	513.09	0.18	8.60	8.70	-1.15	194	194.92	-0.47
2	1279.18	53.54	4.9	1.5	513	513.09	-0.02	8.80	8.70	1.15	196	194.92	0.55
3	1279.18	53.54	4.9	1.5	512	513.09	-0.21	8.50	8.70	-2.30	195	194.92	0.04

6.1. Microstructural analysis and characterization

Figure 26a illustrates the coarse-grained microstructure of the base A6092/B₄C/ZrO₂ composite, which exhibits a characteristic dendritic structure resulting from the stir casting process. This microstructure is indicative of the solidification pattern typically observed in cast materials, where grain growth occurs in a directional manner. In contrast, Figure 26b presents a macroscopic view of the friction stir welded (FSW) joint, highlighting the distinct regions formed due to the welding process. A detailed examination of the cross-sectional microstructure of the FSW joint (Figures 26b-d) reveals four well-defined zones: the weld nugget zone (WNZ), the thermo-mechanically affected zone (TMAZ), the heat-affected zone (HAZ), and the unaffected base material. Each of these regions exhibits unique microstructural characteristics resulting from the varying degrees of thermal exposure and mechanical deformation experienced during welding.

Figure 26
(a) Microstructural analysis of AA6092/3% B₄C/5% ZrO₂, (b) Macrostructural analysis of FS welded Composite and (c-e) Microstructural analysis of FS welded Composite.

A significant observation in the FSW joint is the absence of notable micro-level defects such as voids, cracks, or porosity. This can be attributed to the efficient heat generation and plasticized material flow induced by the rotating tool, which promotes proper consolidation of the joint. The frictional heat and intense stirring action facilitate uniform mixing of the material, preventing defect formation and ensuring sound weld integrity. One of the most prominent microstructural modifications in the FSW joint is the considerable grain refinement compared to the base material. This refinement is most pronounced in the WNZ, where the extreme plastic deformation and dynamic recrystallization processes driven by the rotating tool result in the breakdown of the coarse grains and the formation of ultrafine, equiaxed grains. This refined grain structure significantly enhances the mechanical properties of the weld. Moving outward from the WNZ, the TMAZ, HAZ, and unaffected base material exhibit progressively coarser grain sizes, corresponding to the decreasing intensity of thermal and mechanical effects. The TMAZ experiences moderate plastic deformation and thermal exposure, leading to some grain distortion but not full recrystallization. The HAZ, on the other hand, undergoes thermal cycling without significant plastic deformation, which causes grain coarsening due to heat exposure. The base material remains unaffected by the welding process and retains its original dendritic microstructure. The transition from the coarse-grained base material to the fine-grained structure in the FSW joint is a direct result of the unique mechanisms of the FSW process. The combination of intense plastic deformation, frictional heat, and dynamic recrystallization leads to a refined microstructure, which in turn has a profound impact on the mechanical performance of the joint. The finer grains in the WNZ contribute to improved mechanical properties, including higher strength, enhanced ductility, and better toughness, making the FSW joint superior to the base material in terms of structural integrity and load-bearing capacity.

Figure 27a presents a Scanning Electron Microscope (SEM) micrograph of the base AA6092/3%B4C/5%ZrO2 composite, revealing its relatively coarse grain structure. This microstructure, characteristic of the stir casting process used in composite fabrication, consists of large, dendritic grains that result from the solidification and cooling process. The presence of reinforcement particles within the matrix can also influence grain morphology, affecting the overall mechanical behavior of the material. In contrast, Figure 27b provides a macroscopic view of the friction stir welded (FSW) joint, distinctly illustrating the four major zones that form due to the thermal and mechanical effects of the welding process: the thermo-mechanically affected zone (TMAZ), the weld nugget zone (WNZ), the heat-affected zone (HAZ), and the unaffected base material. These zones differ significantly in their microstructural characteristics due to varying degrees of plastic deformation and heat exposure during FSW.

Figure 27
(a-d) SEM analysis of AA6092/3% B₄C/5% ZrO₂ Composite and FS welded Composite.

A closer inspection of the microstructures shown in Figures 27c and 27d highlights the substantial grain refinement that occurs within the WNZ compared to the TMAZ, HAZ, and the unaffected base material. This transformation in grain size is a direct consequence of the intense mechanical stirring and dynamic recrystallization triggered by the rotating tool during FSW. The process subjects the material in the WNZ to extreme plastic deformation and elevated temperatures, facilitating the fragmentation and redistribution of grains. The high strain rates and thermal cycling lead to the breakdown of the original coarse-grained structure, forming fine, equiaxed grains through continuous dynamic recrystallization.

The formation of this fine-grained microstructure in the WNZ plays a crucial role in enhancing the ultimate tensile strength (UTS) of the FSW joint. The refined grains serve as barriers to dislocation motion, thereby strengthening the material by increasing resistance to plastic deformation and impeding crack propagation. However, while this grain refinement enhances strength, it may also lead to a reduction in ductility. The limited ability of grain boundaries to slide under stress restricts the material’s plastic deformation capability, potentially making the joint more brittle under certain loading conditions.

Additionally, the micrographs reveal the presence of clusters within the composite microstructure, which are agglomerations of B₄C and ZrO₂ reinforcement particles. These clusters play a significant role in determining the mechanical properties of the AA6092/B₄C/ZrO₂ composite by acting as secondary reinforcement phases. The effectiveness of these clusters in strengthening the material depends on their size, distribution, and interfacial bonding with the aluminum matrix. Well-dispersed clusters can contribute to improved load transfer and resistance to deformation, while non-uniform agglomerations may lead to stress concentrations and potential failure sites.

7. Conclusions

In this study, a comprehensive investigation was conducted to optimize the FSW process for AA6092/3% B₄C/5% ZrO₂ composite joints. Through a series of experiments, the influence of critical process parameters, including TRS, WS, AL, and TTA, was systematically examined which led to the following key findings:

• The liquid metallurgy stir casting technique is successfully performed to fabricate seven samples of AA 6082/ZrO₂/B₄C composites by varying Wt.% of B₄C and ZrO₂. Among the seven sample, AA 6082/3% B₄C/5% ZrO₂ composites provide high UTS of 502 MPa, P.E of 7.81 and microhardness of 172.5 HRB.

• Regression models were developed using Response Surface Methodology (RSM) to accurately predict the Ultimate Tensile Strength (UTS), Percentage Elongation (PE), and Weld Nugget Hardness (WNH) of the FSW joints.

• The developed models were validated through a series of confirmation experiments, demonstrating high accuracy and reliability.

• Perturbation and contour plots were employed to analyze the interactive effects of process parameters on the mechanical properties.

• Optimal process conditions were identified: a TRS of 1279.18 rpm, a WS of 53.54 mm/min, a TTA of 1.5°, and an AL of 4.9 kN. These conditions resulted in the highest UTS of 514 MPa, PE of 8.80, and WNH of 196 HRB values.

• The developed model exhibited high accuracy, with maximum prediction errors of +0.18 for UTS, +1.15% for PE, and +0.55% for WNH, further validating its reliability.

• Microstructural characterization revealed significant grain refinement in the weld nugget zone, contributing to improved mechanical properties.

• The absence of major defects, such as cracks and porosity, further validated the effectiveness of the optimized FSW process.

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Publication Dates

• Publication in this collection
  12 May 2025
• Date of issue
  2025

History

• Received
  25 Jan 2025
• Reviewed
  05 Mar 2025
• Accepted
  23 Mar 2025