Surface Modification and Parametric Optimization of Tensile Strength of Al6082/SiC/Waste Material Surface Composite Produced by Friction Stir Processing

Abstract

Friction stir processing (FSP) is one of the promising tools to enhance the mechanical and microstructural features of any engineering material due to its excellence in grain refinement. Further, the successful utilization of waste material into a useful product instigates the use of chicken bone powder (CBP), walnut shell powder (WSP), and rice husk powder (RHP) as secondary reinforcement to develop surface composites and metal matrix composites to enhance the mechanical properties. In the present work, a surface composite of base alloy Al6082 is developed through the utilization of SiC as primary reinforcement and CBP, WSP, and RHP as secondary reinforcement. The experiments were performed as per Taguchi’s L9 orthogonal array and the analysis of variance (ANOVA) response is discussed in detail. The process parameters taken for the study are the type of tool pin profile such as hexagonal, square, and cylindrical threaded along with rotational speed and tool tilt angle. The result revealed the microstructural characterization through field emission scanning electron microscopy (FESEM) images equipped with energy-dispersive X-ray spectroscopy (EDS) phase mapping and elemental spectrum. The tensile strength of each specimen was tested through a horizontal tensometer and further studied to get the optimized value of the process parameter to achieve a larger value. The use of a hexagonal pin profile with the optimized value of the rotational speed of 1500 rpm and 3° tilt angle gives the higher tensile strength of 250.64 MPa.

1. Introduction

Friction stir processing (FSP) is the trending technique for grain refinement as well as modification of the microstructure of the material. Modification happened due to severe plastic deformation. It was developed in 1991 by “The welding Institute” (TWI) [1]. Every day, the need for sophisticated engineered materials with specialized qualities grows. As a substitute for ferrous alloys, composites are growing because of their lightweightedness, low density, high strength, and corrosion resistance, and aluminum has proven to be an excellent alternative [2]. During FSP, the composite made is named a surface composite due to the processing of the top surface of the base material [3]. The properties of the top surface of the base material are altered with processing due to severe plastic deformation and grain refinement [4]. Ceramics such as silicon carbide (SiC), titanium carbide (TiC), zirconium dioxide (ZrO₂), boron carbide (B₄C) etc., were used to reinforce alloys, resulting in surface composites [5]. When compared to base alloys, surface composites offer better mechanical and wear properties [6].

SiC is a mixture of silicon as well as carbon. It has many properties due to which it is the best choice for many researchers and different composite material-related industries. Low thermal expansion coefficient, high hardness and rigidity are some of its common properties [7]. Hybrid composite materials are becoming more popular in many engineering applications due to their improved features and benefits over non-hybrid with using only one reinforcement [8]. Hybrid composites consist of two or more reinforcements. It has great potential to improve differential mechanical properties such as tensile, hardness, wear resistance, and many more [9]. Nowadays some biowaste materials are also proven as a reinforcement to upgrade the properties of existing materials such as chicken bone powder (CBP), which is a waste material and is generally produced from the poultry farm. Storing this waste is a big problem because it produces unwanted gases which are harmful to the environment; however, utilizing the waste before it produces harmful gases is an eco-friendly alternative [10,11]. The chicken bone powder has a good amount of carbon as well as calcium which is a very useful for reinforcing elements. It also has good potential to provide strength as a calcium source. Walnut shell powder (WSP) is a green waste which is produced by walnut farm industries. Its soft abrasive nature has unique physical and chemical properties. It contains cellulose and lignin in high amounts which is structured as large and medium fiber. The covalent bond of lignin enhances the bonding strength which leads to improved mechanical properties while using as a reinforcement. It has also the potential to improve strength as well as wear properties. Rice husk powder (RHP) is an agricultural waste which is produced from farming. Its storage is a big problem for many farmers; hence, they destroy them by burning which produces unwanted gases which when comes in contact with the environment also changes the climate of the surrounding area. Rice husk has also good strength, good wear resistance, low coefficient of friction, and excellent machinability which makes it superior if used as a reinforcement [12].

In view of the mechanical properties, tensile test will provide the various results such as tensile modulus, yield and ultimate strength, percentage elongation, and other elastic coefficients. The general solution for the tensile properties of the material is given by generalized hook’s law. The elastic constants can also be obtained by the simulated results and can be useful to predict the elastic constants and other mechanical properties prior to the experimental run [13]. These properties also depend on the optimized values of process parameters. The process parameters of FSP play a significant role in the microstructural and mechanical properties of the surface composites. Process parameters such as tool rotational speed, traverse speed (feed rate), tool tilt angle, tool pin geometry (shape and size) etc., need to be optimized to complete the processing. Various optimization techniques such as Taguchi’s orthogonal array, response surface methodology (RSM) are reported by authors to find the optimum solution of the experimental problem. Taguchi’s design is considered as one of the standard designs of experiment (DOE) method to solve the experimental problems where approximated results are to be predicted with the help of analysis of variance (ANOVA) response in terms of significance. It is a robust design by eliminating and minimizing noise factors. The method is capable to predict both “larger is better”, as well as “smaller is better” approach in terms of signal to noise ratio. L9 (3^4) orthogonal array includes nine different experiments covering the range of the selected process parameter and used for approximation of the factors that influence the performance standards [14].

Several researchers have worked to optimize the different process parameters of the FSP operation. Awasthi et al. [15] optimized the process parameters i.e., tool rotation speed, tool tilt angle, and weight percentage on ZK60A/SiC/B₄C using FSP. Results revealed that optimized values are 1000 rpm (rotation speed), 2° (tilt angle), and 75/25 (wt.%). They also concluded that with increased wt.% of reinforcement particles of B₄C with scroll shoulder there is increased hardness. Taghiabadi and Moharami [16] optimized the effect of process parameters i.e., traverse speed and tool rotational speed on Mg₄Si using FSP. Results revealed that the optimized value of the traverse speed is 12.5 mm/min and the rotation speed is achieved at 1250 rpm. Tensile strength is increased up to 150 MPa whereas hardness is also increased up to 65 HV which is 140 and 20 times the multiple of base material, respectively. Moharami and Razaghian [17] investigated the effect of process parameters i.e., number of passes and tool rotation speed also examine corrosion behavior on Al-Mg₂Si using FSP. Results revealed that by increasing the number of passes from one to three, the corrosion resistance is reduced to (6.92 − 4.11) × 10⁻⁷ A·cm⁻² which will also help to wear resistance. There is also grain refinement that occurs from 112 µm to (10.5 − 2.3) µm in the first and third pass of FSP.

In the present work, SiC (2% by wt.) is used as a primary reinforcement and waste materials such as CBP, WSP, and RHP (vary from 2% to 6%) are used as secondary reinforcement. The study revealed the microstructural characteristics and effect of process parameters (rotational speed and tool tilt angle) along with the type of tool pin profile (Hexagonal, Square, Threaded) on the tensile strength of the developed specimens. Taguchi’s L9 orthogonal array is applied to examine the effect of process parameters and the analysis of variance (ANOVA) response is discussed in terms of the significance of the process parameters.

2. Experimental Procedure

Al6082 is chosen as a base material, which is available in the form of a plate of dimension (100 × 65 × 10) mm³. The chemical composition and mechanical properties of Al6082 are given in

Table 1. Chemical composition of Al6082 alloy.

Elements	Aluminum (Al)	Silicon (Si)	Magnesium (Mg)	Manganese (Mn)	Iron (Fe)	Chromium (Cr)	Zinc (Zn)	Titanium (Ti)	Copper (Cu)
wt. %	95.2	1.3	1.2	1.0	0.5	0.25	0.2	0.1	0.1

and

Table 2. Mechanical properties of Al6082 alloy.

Mechanical Properties	Values
Tensile Strength	180 MPa
Hardness Value (BHN)	49 BHN

.

A groove of (3 × 3) mm is prepared at the center of the Al6082 plate with the help of a shaper machine to accommodate the mixture of reinforcement. As a reinforcement, SiC (2% by wt.) is used as a primary reinforcement and waste materials such as CBP, WSP, and RHP (vary from 2% to 6%) are used as secondary reinforcement. The waste material reinforcements were prepared by ball milling operation with a planetary mono mill (Pulverisette 6 classic, made by Fritsch). The BPR and rpm kept for the operation were 12:1 and 300 rpm respectively with the Tungsten carbide ball of 20 mm diameter. The field emission scanning electron microscopy (FESEM) image and their corresponding energy-dispersive X-ray spectroscopy (EDS) spectrum for the presence of elements of CBP, WSP and RHP are shown in Figure 1a–c.

For the fabrication of the composite, there are three different pin profile tools chosen i.e., hexagonal (HEX), square (SQR), and threaded (THRD) as shown in Figure 2.

In the present work, the Taguchi method is used for the optimization of different process parameters. For this research L_9, the orthogonal array is used for the selection of process parameters of FSP operation such as type of tool, tool rotational speed, tool tilt angle, and type of secondary reinforcement with their wt. % (vary from 2% to 6%). The level of design of process parameters and L₉ orthogonal is illustrated in

Table 3. Level of design of process parameters.

	Levels	1	2	3
Factors
Tool		SQR	HEX	THRD
Tool Rotation Speed (RPM)		1000	1500	2000
Tilt Angle (°)		1	2	3
Secondary Reinforcement		CBP	WSP	RHP
% of Secondary Reinforcement (%)		2	4	6

and

Table 4. L₉ orthogonal array.

Experimental Run	Tool Pin Profile	Tool Rotation Speed (RPM)	Tool Tilt Angle (°)	Hybrid Reinforcement (By Wt.%) SiC (2%) +
1	SQR	1000	1	CBP (2%)
2	SQR	1500	2	CBP (4%)
3	SQR	2000	3	CBP (6%)
4	HEX	1000	2	WSP (2%)
5	HEX	1500	3	WSP (4%)
6	HEX	2000	1	WSP (6%)
7	THRD	1000	3	RHP (2%)
8	THRD	1500	1	RHP (4%)
9	THRD	2000	2	RHP (6%)

.

The FSP operation is performed on a vertical milling machine (make of “Rainu machine tools”) with the help of a special design fixture to hold the workpiece. A total of 9 experiments were conducted as per the process parameters given in Table 4 and made 9 specimens of FSP were for study purposes.

Each specimen was tested for morphological characterization through FESEM images, EDS study, and mechanical properties such as tensile strength and hardness (BHN). The microstructural specimens were prepared for 2% SiC/2% of each type of reinforcement (CBP/WSP/RHP). ASTM E3 standard was used to prepare the specimen for microstructural study followed by etching through Keller’s reagent (15 mL HCL + 25 mL HNO₃ + 10 mL HF + 50 mL H₂O). The FESEM images were taken by Joel jsm-7800 Prime field emission scanning electron microscope coupled with an EDS detector (LN₂ Free SDD X-max 80 Energy dispersive detector) at an acceleration voltage of 20 Kv and acquisition time of 60.4. The EDS spectrum is further discussed to confirm the presence of elemental percentage of composition of the type of primary reinforcement (SiC) and secondary reinforcement (CBP, WSP and RHP). As an outcome of the study, tensile strength is studied for all nine specimens to get the optimized value of process parameters of FSP. A tensile test was conducted on a horizontal Tensometer, made of KIPL, Model PC-2000. Specimens for the tensile study were developed as per ASTM E8 standard.

3. Result and Discussion

A total of nine specimens were developed through FSP operation as shown in Figure 3. An addition experiment with adding 2% SiC (primary reinforcement) without any secondary reinforcement is performed to evaluate the effect of secondary reinforcements in terms of tensile strength. The traverse speed for FSP operation was fixed to 25 mm/min while other process parameters taken for nine specimens are as per Taguchi’s L9 array given in Table 4. All the physical specimens were seeming adequate because of no major defects such as misrun or tunnelling. Tool traces and cutting marks are seen on the top of the FSPed region. However, it was removed by polishing it with grit paper before making specimens for testing purposes.

Figure 4, Figure 5 and Figure 6 show the FESEM images, phase mapping, and EDS spectrum for Al6082/2%SiC/2%(CBP/WSP/RHP) surface composites, respectively. FESEM images show the uniform distribution of both SiC and waste material (CBP/WSP/RHP) in the stirring zone. The FSP operation improves the microstructural features by refining the grains. A large number of equiaxed grains and grain boundaries can be seen in the FESEM images. The average grain size of the developed specimens varies in the range of 20 to 35 µm for all three types of composites. The minimum grain size of 6 µm is observed for Al6082/2%SiC/2%WSP. Clustering of the secondary reinforcements (CBP/WSP/RHP) can also be seen in the FESEM images. It is because adding CBP/WSP/RHP will utilize the frictional heat and create a hindrance to the movement of free electrons into the matrix material. Therefore, an energy gap is created which tends to accumulate the clustering of these particles. However, the clustering occurs in negligible amount. Similar observations were also recorded in other similar published work [18,19].

Phase mapping and EDS spectrum of the developed Al6082/2%SiC/2% (CBP/WSP/RHP) show the presence of major constituents of the matrix and alloy phase. The major elements such as Al and Si, of the matrix and primary reinforcement phase, can be seen more largely. However, the major constituents of secondary reinforcement such as Ca, Mg, Zn, and Fe are also seen in the significant amount. It is evident from the study that the reinforcement phase is completely diffused into the matrix material. Some other constituents of the reinforcement phase which have lower atomic numbers are not completely diffused and hence not seen in the EDS spectrum. Some other elements such as Ni, Cr, and F are present in specimens due to the chemical, metallurgical reactions, and etching operation. Carbon is available due to the presence of SiC and oxygen due to aluminum alloy, which naturally forms the native oxide layer and oxygen.

Further, a tensile test was carried out on each specimen as per standards. The graph of load vs elongation of tensile testing of all nine specimens is shown in Figure 7 and their corresponding values of tensile strength are presented in

Table 5. Experimental value of fabricated composite Al6082/2% SiC/2% (CBP/WSP/RHP).

Experimental Run	Tool Pin Profile	Rotation Speed (RPM)	Tilt Angle (°)	Tensile Strength (Avg. of 3 Readings) (MPa)
1	SQR	1000	1	206.55 ± 2
2	SQR	1500	2	223.34 ± 7
3	SQR	2000	3	236.62 ± 5
4	HEX	1000	2	224.98 ± 4
5	HEX	1500	3	249.91 ± 3
6	HEX	2000	1	217.07 ± 6
7	THRD	1000	3	240.09 ± 5
8	THRD	1500	1	220.81 ± 4
9	THRD	2000	2	222.09 ± 10
			Mean	226.83 ± 5

. The tensile testing of Al6082/2%SiC specimen is also conducted through the same standards and the average value was found to be 197.4 MPa. It is indicated that the addition of secondary and primary reinforcement increases the tensile strength compared to the 180 MPa of base alloy Al6082 tested with the same standards. The result also revealed that adding of primary reinforcement improves the tensile strength. However, the increment in numerical values of tensile strength observed are comparatively low by adding both primary and secondary reinforcement. It indicates that the addition of secondary reinforcement significantly affected the tensile strength and overall mechanical properties of the specimens. The load vs elongation curve revealed the mixed nature of the ductile and brittle failure. It is because the presence of hard reinforcement particles SiC and secondary reinforcement (CBP/WSP/RHP) has strong bonding strength capability, which improves the mechanical properties.

Further, the study is carried out to optimize the process parameters such as tool pin profile, tool rotation speed, and tilt angle through S/N ratio (Larger is better) and ANOVA. Taguchi’s design is analyzed with the help of Minitab 17 software. The estimated model coefficient for S/N ratios and mean are shown in

Table 6. Estimated model coefficients for SN ratios.

Term	Coef	SE Coef	T	p
Constant	47.1028	0.01954	2410.254	0.000
Tool SQR	−0.1825	0.02764	−6.603	0.022
Tool HEX	0.1407	0.02764	5.092	0.036
RPM 1000	−0.1192	0.02764	−4.312	0.050
RPM 1500	0.1690	0.02764	6.115	0.026
Tilt Ang 1	−0.4652	0.02764	−16.831	0.004
Tilt Ang 2 S = 0.5863	−0.1134 R-Sq = 99.7%	0.02764 R-Sq(adj) = 98.6%	−4.105	0.055

and

Table 7. Estimated model coefficients for mean.

Term	Coef	SE Coef	T	p
Constant	226.872	0.3345	678.311	0.000
Tool SQR	−4.702	0.4730	−9.941	0.010
Tool HEX	3.781	0.4730	7.944	0.015
RPM 1000	−2.999	0.4730	−6.340	0.024
RPM 1500	4.481	0.4730	9.474	0.011
Tilt Ang 1	−12.062	0.4730	−25.501	0.002
Tilt Ang 2 S = 1.003	−3.272 R-Sq = 99.9%	0.4730 R-Sq(adj) = 99.4%	−6.918	0.020

. ANOVA response for the S/N ratio and mean are given in

Table 8. Analysis of variance for SN ratios.

Source	DF	Seq SS	Adj SS	Adj MS	F	p	PC (%)
Tool	2	0.16457	0.16457	0.082283	23.94	0.040	8.23
RPM	2	0.13574	0.13574	0.067871	19.75	0.048	6.79
Tilt Angle	2	1.69210	1.69210	0.846048	246.14	0.004	84.64
Residual Error	2	0.00687	0.00687	0.003437
Total	8	1.99928

and

Table 9. Analysis of variance for means.

Source	DF	Seq SS	Adj SS	Adj MS	F	p	PC (%)
Tool	2	111.77	111.77	55.884	55.51	0.018	8.09
RPM	2	93.81	93.81	46.906	46.59	0.021	6.79
Tilt Angle	2	1174.05	1174.05	587.025	583.05	0.002	84.97
Residual Error	2	2.01	2.01	1.007
Total	8	1381.64

. It is observed from the ANOVA responses that the p value is less than 0.05 which confirms the statistical significance and rejects the null hypothesis. Similarly, the response table for the S/N ratio and mean is shown in

Table 10. Response table for signal-to-noise ratios.

Level	Tool	RPM	Tilt Angle
1	46.92	46.98	46.64
2	47.24	47.27	46.98
3	47.14	47.05	47.68
Delta	0.32	0.29	1.04
Rank	2	3	1
Larger is better

and

Table 11. Response table for means.

Level	Tool	RPM	Tilt Angle
1	222.2	223.9	214.8
2	230.7	231.4	223.5
3	227.7	225.3	242.2
Delta	8.5	7.5	27.4
Rank	2	3	1
Larger is better

. Response table describes the rank which is based on Delta value. The largest Delta value is 1.04 and 27.4 of tilt angle for S/N ratio and mean, which confirms the first rank as a result of greater impact on the response. However, the lower Delta value is 0.29 and 7.5 of tool rotational speed for S/N ratio and mean which is the lowest value than other parameters which shows the lesser impact on the response. While analyzing larger the better is chosen to get the best-optimized value with the goal of achieving maximum response. The main effect describes how much variation has taken place compared to the mean of the response at a lower value of the process parameter and the mean of the response at a higher value of the process parameter which is illustrated in Figure 8 and Figure 9. The optimized values are hexagonal (HEX) tool pin profile at 1500 rpm tool rotation speed with tilt angle 3° which is shown on the 5th experimental run of the design table.

The confirmation experiment has been conducted based on the optimized value of process parameters and found the maximum ultimate tensile strength of 250.64 MPa which is approximately closer to the experimental value. While discussing the effect of process parameters, each parameter has a significant effect on FSP operation and mechanical properties. In the present study, there are three pin profile tools are used. However, the hexagonal pin profile showed the optimum value of process parameters to achieve higher tensile strength. It is attributed to the fact that the hexagonal pin has sharp edges to remove the extra material from the front and mixed the reinforcement with it and deposit it at the back with the proper distribution. However, due to lower edges in the square, it does not show optimum value, whereas the threaded pin profile shows the better than square due to having better material flow. Rotational speed shows a vital role while the development of Al6082/2% SiC/2% (CBP/WSP/RHP). In the present study, three different tool rotation speeds are selected i.e., lower (1000 rpm), medium (1500 rpm), and higher (2000 rpm). At lower rpm, the result shows that insufficient friction takes place which causes lower heat generation, whereas sufficient heat generation takes place using a rotational speed of 1500 rpm. However, at 2000 rpm excessive heat was generated due to which improper material flow occurred compared to processing at a lower feed rate. At a tilt angle from 1° to 3° the tensile strength significantly increases. This happened due to good consolidation of the material under the tool shoulder while increasing the tilt angle from 1° to 3°. At a lower tilt angle, there is more contact between the tool shoulder and the workpiece, as a result, more friction takes place due to which no proper stirring action takes place; however, at a higher tilt angle defect-free optimized result is obtained.

4. Conclusions

The waste material CBP, WSP, and RHP are successfully utilized as secondary reinforcement to develop surface composites from FSP operation. Microstructural and mechanical characterization of the developed specimens evidences the improvement in overall properties. The followings are the conclusive results based on the study:

• FESEM images show the uniform distribution of both SiC and secondary reinforcement CBP, WSP, and RHP into the stir zone of the matrix material. The average grain size of the developed specimens varies in the range of 20 to 35 µm for all three types of composites. The minimum grain size of 6 µm is observed for Al6082/2%SiC/2%WSP.
• Phase mapping and EDS spectrum of the developed Al6082/2% SiC/2% (CBP/WSP/RHP) show the presence of major constituents of the matrix and alloy phase. It is evident from the study that the reinforcement phase is completely diffused into the matrix material.
• As an outcome, the tensile strength of each specimen has been evaluated and found significant increment of around 20% to 35% of tensile strength compared to base alloy Al6082.
• Taguchi’s L9 optimization approach and ANOVA response show the significance of the rotational speed and tool tilt angle and selected tool pin profile. It is concluded from the study that the tensile strength of processed samples is increased with using the hexagonal pin profile tool due to better stirring action as a result proper material flow takes place.
• Tool tilt angle also plays a vital role in increasing tensile strength. These values are increased after increasing the tilt angle. It is attributed to the thrusting effect and also due to contact between the shoulder and workpiece.
• The optimized value for tensile strength is in the range of (247.32–253.96) MPa with a hexagonal (HEX) tool pin profile, 1500 rpm, and 3° tilt angle.