Fabrication, microstructure, and machinability of aluminum metal-matrix composites

By using an in-situ fabrication technique, Al 6061 rods with a diameter of 25 mm were used as a matrix and GGBS particles as reinforcement. Table 1 shows the chemical composition of a sample matrix. The Al 6061 rods were measured and melted in an electric furnace in a graphite crucible. To avoid contamination, the inside of the chosen crucible was coated with WOLFRAKOT. The melt temperature was maintained at 900°C for Al 6061 and preheating of the reinforcement of GGBS by 650°C was carried out. GGBS was added into the crucible, and the GGBS particles’ size was ~ 20 μm; the chemical composition of the reinforcement added to the mix is indicated in Table 2. Every 5 min, the melt was thoroughly stirred. Castings with a 30 min and 60 min melt holding time were carried out for the formation of different volume fractions of GGBS 2.5 wt.%, 5 wt.%, and 7.5 wt.%. Argon gas was passed through the melt to prevent oxidation, which resulted in less slag formation [15]. The slag was removed after the synthesis period was finished, and the melt was then poured into the preheated die. The cast was taken out of the die after it had fully solidified. Schematic representations of the fabrication and machining processes are illustrated in Figures 1 and 2. Figure 3 depicts the aluminum 6061 matrix material, GGBS reinforcement powder, and casted samples.

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The Taguchi techniques have been utilized to perform optimization in the current study. The experiments are planned using Taguchi's L₉ OA, the aim of deploying which is to minimize the number of experimental runs. The Taguchi method was used to evaluate performance metrics, such as MRR and SR, using input parameters such as reinforcement weight percentage, cutting speed, feed rate, and depth of cut used in milling. Table 3 lists the parameters and levels that regulate the machining process. These values were chosen based on preliminary experiments [16].

Machining performance is evaluated with MRR and SR. MRR is the rate of removal of material during machining and it is calculated based on the depth of cut, width of cut, and feed rate; here width of the cut is 16 mm. The average surface peaks and valleys across the surface are used to calculate SR. The experiments are tabulated in Table 4 and were formed by L₉ OA using Minitab 18. Higher MRR and a lower SR are preferred in the machining process.

Micro-structural investigations of samples were performed to check particle agglomeration and distribution and the formation of defects. In the various obtained samples of composites, to obtain good quality microstructures, abrasive particles are initially used for carrying out the polishing. In an aluminum matrix, particles are found to be dispersed in nature. On comparing the prepared samples, oxide particles can be identified inside Al grains and grain boundaries. The addition of GGBS particles in samples of AMC shows clusters of silicon dioxide and oxide particles along the grain boundaries, as shown in Figure 4. Scanning electron microscopy (SEM) micrograph images confirm the presence of reinforcement particles, and also, even distribution of those particles is noticed. The separation of oxides is also noted in Figure 5. The SEM image reveals the occurrence of the distributed phase in which the calcium oxide is dispersed evenly in the matrix. There are no obvious changes in the morphology or size of the silicon dioxide and calcium particles, as observed. The grayish white-colored particles were determined to be calcium oxide, while the light gray-colored flake-like particles were determined to be Al₂O₃, as depicted in Figure 6. In addition, metallographic specimen analysis is also presented for 7.5% of GGBS reinforcement in Figure 7.

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EDX spectroscopy measurements on individual specimens in the SEM are used to determine the quantity of chemical composition of the Al composites. The atomic percentages of the elements found on the specimen surface are provided by the corresponding EDX profile analysis shown in Figure 8.

Fig. 8

The presence of magnesium, copper, aluminum, silicon, zinc, and oxides in the Al6061 alloy is depicted in Figures 7 and 8. A detailed study of the interfaces in reinforced metal-matrix composites confirmed the presence of SiO₂ and Al₂O₃. Oxide content has been found in all Al6061 with GGBS reinforcement compositions. The presence of oxides is due to the formation of Al₂O₃, SiO₂, CaO, K₂O, and MgO as the major compounds in GGBS. The results of EDX examination are presented in the form of weight/atomic values for major individual elements and data concerning these are presented in Table 5. Moreover, the areas chosen for EDX analysis are also indicated in Figures 8–10. From Figures 9 and 10, it is confirmed that the percentage improvement of GGBS reinforcement increases the oxides by 18.27% for 5% of reinforcement and 41.44% for 7.5% of reinforcement. The results of EDX examination are presented in the form of weight/atomic values for major individual elements, and the corresponding data are shown in Table 5.

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Figures 11–13 depict the pattern of XRD for the fabricated samples. The peaks of the GGBS phase and the Al phase have grown, according to the XRD analysis results for the samples of Al reinforced by GGBS. In fact, the XRD analysis findings show that an increase in the weight percent of the reinforcement materials causes a rise in the diffraction peaks’ intensity. According to Figures 11–13, the Al phase formed at 2θ for the planes (111), (200), and (311) in the XRD data for the pure Al (38.050, 44.310, and 77.950), respectively. Additionally, the GGBS phase was formed at 2θ (7.50°, 8.40°, and 64.75°), which denote a rise in the weight fraction of the GGBS phase and a fall in the aluminum lattice parameter.

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Since there are no other compounds present, the interface between Al6061 and GGBS is easily seen. A distinct interface between the matrix and reinforcement is necessary to show that AMCs have superior mechanical properties compared to monolithic alloys [17].

An S/N response table is used to analyze the effects of machining factors such as reinforcement weight percentage, cutting speed, feed rate, and depth of cut on MRR and SR. Table 6 deduces the “S/N” ratio response values for MRR and SR [18].

A signal-to-noise (S/N) ratio is created by converting the values of MRR and SR [19]. The quality characteristic that deviates from the desired values is measured using this method. Based on S/N ratio analysis, for every level of the control parameter, the S/N ratio is compared. Maximizing MRR and reducing SR are the objectives of this process. Table 3 provides the values for various levels of factors for MRR and SR, and Figures 14 and 15 show the same information graphically. The best control factor and level for the MRR value are shown in the “S/N” ratios response table as S/N = 65.53 (factor B) and level 3, and S/N = 69.17 (factor C) and level 3; and other parameters like spindle speed and percentage of reinforcement composition constantly affect the MRR at all levels. The feed rate (B3) of 260 mm³/min and the depth of cut (C3) of 0.75 mm produced the best MRR value. S/N = 9.281 (factor A) and level 2, S/N = 9.252 (factor B) and level 1, S/N = 9.144 (factor C) and level 1, and S/N = 9.178 (factor D) and level 2 were the best factors and levels for the lower SR, respectively. The best value of SR is obtained with a spindle speed (A2) of 1,250 rpm, a feed rate (B1) of 220 mm³/min, a depth of cut (C1) of 0.25 mm, and a percent of reinforcement composition (D2) of Al 6061 T6 with 5% GGBS. Figure 15 illustrates the impact of machining parameters on the average “S/N” ratio of SR.

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Fig. 15

Figures 16A–16D depict the three-dimensional (3D) response surfaces for MRR and SR that change with control factors. From Figure 16A, we see depicted the effect of feed rate and depth of cut on MRR. Based on the surface plot, we are able to ascertain that as the feed rate and depth of cut increased, the MRR has also increased. The maximum feed rate of 260 mm/min and depth of cut of 0.75 mm produces the higher MRR of 3,120 mm³/min. Hence, the other parameters like spindle speed and percentage of reinforcement composition constantly influence the MRR [20]. From Figure 16B, we see depicted the effect of feed rate and percentage of reinforcement composition on SR, which clearly illustrates that the SR will decrease when there is an increase in the percentage of reinforcement composition. Similarly, from Figures 16C and 16D, we see depicted the effect of percentage of reinforcement composition with spindle speed and depth of cut on SR. In general, lower SR was obtained with lower depth of cut and spindle speed. Here, SR will decrease with the increase of both spindle speed and depth of cut due to variation in reinforcement composition present in the different samples. In addition, a plot of S/N ratios also confirms the irregularity of the results obtained due to the variations in composition of reinforcement.

Fig. 16

From Figures 17A–17C, we see depicted the evaluation profile of different percentages of reinforcement composition. The three-dimensional topography of a surface is created by SR, which is a regular or irregular departure from the nominal surface. Traverse feed marks and other irregularities that fall within the parameters of the roughness sampling length are included in this. Roughness is the term used to describe the surface irregularity of longer wavelengths. Based on the profile, an average of the SR value was taken for all the trails, and it is tabulated in Table 4. Due to variation of percentage reinforcement of composition, an influence is exerted over the value of SR, and this is portrayed in Figure 17.

Fig. 17

In comparison to a non-reinforced Al alloy, the reinforcement improves the machinability in terms of SR, higher MRR, and a decreased propensity to clog the cutting tool. According to Zhang et al. [21], the addition of SiC particles improved the mechanical properties of the aluminum/SiC composite, which led to SR of the aluminum/SiC composites being lower than that of the aluminum metal during an end-milling experiment.