Optimization of Al-Si-Mg/MSSA Particulate Composite for Low Wear Rate
The wear rate of the developed composites are presented in Table 1
Table 1
Wear rate of the Al-Si-Mg composites
Runs
|
Parameter Settings
|
Wear Rate
|
Stir. Time (sec.)(A)
|
Pro. Temp. (℃)(B)
|
MSSA (wt. %)(C)
|
Part. Size (µm)(D)
|
Mean (mm3/N/m)
|
S/N (dB)
|
1
|
30
|
690
|
5
|
100
|
0.04499
|
26.9377
|
2
|
60
|
720
|
5
|
75
|
0.02248
|
32.9641
|
3
|
90
|
750
|
5
|
50
|
0.01538
|
36.2609
|
4
|
120
|
780
|
5
|
25
|
0.02036
|
33.8244
|
5
|
60
|
750
|
10
|
100
|
0.03131
|
30.0863
|
6
|
30
|
780
|
10
|
75
|
0.01348
|
37.4062
|
7
|
120
|
690
|
10
|
50
|
0.01783
|
34.9770
|
8
|
90
|
720
|
10
|
25
|
0.02371
|
32.5014
|
9
|
90
|
780
|
15
|
100
|
0.01788
|
34.9526
|
10
|
120
|
750
|
15
|
75
|
0.01628
|
35.7669
|
11
|
30
|
720
|
15
|
50
|
0.05062
|
25.9136
|
12
|
60
|
690
|
15
|
25
|
0.03671
|
28.7043
|
13
|
120
|
720
|
20
|
100
|
0.01318
|
37.6017
|
14
|
90
|
690
|
20
|
75
|
0.01614
|
35.8419
|
15
|
60
|
780
|
20
|
50
|
0.02452
|
32.2096
|
16
|
30
|
750
|
20
|
25
|
0.04225
|
33.0632
|
|
|
|
|
Mean
|
0.02432
|
33.0632
|
Table 1 shows the wear rate of the developed Al-Si-Mg/MSSA particulate composite at different runs (combinations). It also depicts the Wear Rate properties of the materials through the experimental runs carried out during the study and the signal-to-noise ratio. From Table 1, the wear rate general mean and the S/N ratio mean of the developed Al-Si-Mg/MSSA composites are 0.02432mm3/N/m and 33.0632dB respectively. The S/N ratio was calculated from the lower the better performance characteristics for the Wear Rate.
Table 2
Level
|
Stir. Time
|
Pro. Temp.
|
MSSA
|
Part. Size
|
Mean Wear Rate (mm3/N/m)
|
S/N Wear Rate (dB)
|
Mean Wear Rate (mm3/N/m)
|
S/N Wear Rate (dB)
|
Mean Wear Rate (mm3/N/m)
|
S/N Wear Rate (dB)
|
Mean Wear Rate (mm3/N/m)
|
S/N Wear Rate (dB)
|
1
|
0.0258
|
32.5
|
0.02684
|
32.39
|
0.03784
|
29.44
|
0.02892
|
31.62
|
2
|
0.02158
|
33.74
|
0.01709
|
35.49
|
0.02875
|
30.99
|
0.02750
|
32.25
|
3
|
0.03037
|
31.33
|
0.02709
|
32.34
|
0.01828
|
34.89
|
0.02631
|
32.4
|
4
|
0.02402
|
33.28
|
0.03076
|
30.63
|
0.01691
|
35.54
|
0.01906
|
34.6
|
Delta
|
0.00879
|
2.41
|
0.01366
|
4.87
|
0.02092
|
6.11
|
0.00986
|
2.98
|
Rank
|
4
|
4
|
2
|
2
|
1
|
1
|
3
|
3
|
Table 2 is the response Table for the wear rate of the developed composites where the wear rate of the composite was 0.02580mm3/N/m, 0.02158mm3/N/m, 0.03037mm3/N/m, and 0.02402mm3/N/m with S/N ratios of 32.50dB, 33.74dB, 31.33dB, and 33.28dB at stirring time of 30s, 60s, 90s, and 120s respectively. At processing temperatures of 630℃, 640℃, 650℃ and 680℃, the mean wear rate was 0.02684mm3/N/m, 0.01709mm3/N/m, 0.02709mm3/N/m, and 0.03076mm3/N/m with S/N ratios of 32.39dB, 35.49dB, 32.34dB, and 30.63dB respectively. The mean wear rate under the influence of MSSA content 5%, 10%, 15% and 20% were 0.03784mm3/N/m, 0.02875mm3/N/m, 0.01828mm3/N/m, and 0.01691mm3/N/m with S/N ratios of 29.44dB, 30.99dB, 34.89dB, and 35.54dB respectively. The wear rate in respect to the particle size of MSSA at 100µm, 75µm, 50µm, and 25µm, were 0.02892mm3/N/m, 0.02750mm3/N/m, 0.02631mm3/N/m, and 0.01906mm3/N/m at means and 31.62dB, 32.25dB, 32.40dB and 34.60dB at S/N ratios. The stirring time had the highest rank with a difference between the highest and lowest mean wear rate as 0.00879 mm3/N/m and the MSSA reinforcement had a difference between the highest and lowest mean wear rate as 0.00986mm3/N/m.
Figure 1 shows the effect of stirring time on the wear rate of the Al-Si-Mg/MSSA composite. There was a wear rate reduction with an increase in stirring time from 30s to 60s. Figure 1shows the lowest mean Wear Rate of 0.02158mm3/N/m at means and 33.74dB at S/N ratio on a stirring time of 60s and highest Wear Rate at 90s. Generally, it is observed that the wear rate increased with the increase in stirring time beyond 60s. But at a much higher stirring time, i.e. greater than 90s, the wear rate reduced. This is not disconnected from the fact that with more stirring time, there will be increased dispersion of the secondary phases in the alloy as reported in Ayar et al., (2021).
The effect of processing temperature on the wear rate of Al-Si-Mg/MSSA composite is shown in Figure 2. It shows that the wear rate of the composite decreases with the increased processing temperature from 690℃ to 720℃ where the lowest wear rate was observed. This is due to the ease of solidification within these temperatures. Beyond 720℃, the wear rate increased with an increase in pouring temperature due to the formation of voids by bubbling at these higher temperatures.
Effect of MSSA Content on the Wear Rate of Al-Si-Mg/MSSA Composite
Figure 3 shows the variation of wear rate with MSSA content. It shows that the wear rate reduces with an increase in MSSA content. The ash particles form a lubricating point at surfaces and an increase in these particle content increases the wear inhibition mechanism. The rate of reduction of wear is linear until 15% MSSA content where the rate of reduction in wear rate is reduced and this is due to the increase in more crystalline materials within the phases as observed by Stalin et al., (2021).
Effect of Particle Size on the Wear Rate of Al-Si-Mg/MSSA Composite
Figure 4 shows the variation of wear rate with particle size from 25µm-100µm. It shows that the wear rate decreases with a decrease in particle size in agreement with Vishal et al., (2021) who stated that particle size governs the mechanical and tribological characteristics of such composite materials. At 100µm particle size, the peak of wear rate was observed to be 0.02892mm3/N/m. The best (lowest) wear rate (0.01906mm3/N/m) was observed to be at the smallest particle size of 25µm.
Figures 5-8 show the interaction effect of MSSA content (in weight percent), stirring time, processing temperature, and particle size. It could be observed that the highest wear rate, was observed at MSSA content between 12-18% and at a low stirring time of less than 60s. So also, the wear rate was observed to be the highest at MSSA content between the range of 12-18% and pouring temperature of 700-740℃. The highest wear rate was also observed at particle size within 30-70µm. Figure 8 shows the interaction between stirring time and particle size.
Analysis of Variance for the Wear Rate of Al-Si-Mg/MSSA Composite
Table 3
Analysis of Variance of Means for Wear Rate of AL-SI-MG/MSSA Composite
Source
|
DF
|
Adj SS
|
Adj MS
|
F
|
P
|
Percentage Contribution
|
Stirring Time (sec.) (A)
|
1
|
0.00002
|
0.00002
|
0.25
|
0.627
|
1.07
|
Processing Temperature (℃) (B)
|
1
|
0.000014
|
0.000014
|
0.17
|
0.686
|
0.75
|
MSSA reinforcement (wt. %)(C)
|
1
|
0.000715
|
0.000715
|
8.94
|
0.012
|
38.09
|
Particle Size (µm)(D)
|
1
|
0.000248
|
0.000248
|
3.11
|
0.106
|
13.21
|
Error
|
11
|
0.00088
|
0.00008
|
|
|
|
Total
|
15
|
0.001877
|
|
|
|
|
Table 3 shows the analysis of variance of the wear rate of Al-Si-Mg/MSSA composite for the various factors that were considered. The MSSA reinforcement has the highest percentage contribution to the wear rate of the composite. Implying that for the factors considered, the MSSA content contributes 38.09% to the wear rate. In other to reduce the wear rate, the MSSA content must be taken into consideration. The particle size contributed 13.21% to the wear rate of the composite material. With a P-Value less than 0.05 at a 95% confidence level, the MSSA content was observed to be a significant factor in the wear rate of the developed material.
Optimal Wear Rate of Al-Si-Mg/MSSA Composite
The optimal development combination of the factors for the development of Al-Si-Mg/MSSA composite for low wear is obtained from the response table. From Figure 1-4, it could be observed that the best (optimum) development parameters are stirring time of the 60s, processing temperature at 720℃, MSSA content of 20%, and particle size of 25µm. Which is A2B2C4D4. The optimal Wear Rate of the composite was predicted using Equation 2 to be 0.00168mm3/N/m at means and 40.1804dB at S/N Ration.
$${W}_{Opt}={W}_{St}+{W}_{Pr}+{W}_{Ma}+{W}_{Ps}-3{W}_{m}$$
2
Where Wopt is the optimal wear rate, WPr is the lowest wear rate at the processing temperature, WMa is the lowest wear rate at varied mango seed shell ash content, and WPs is the lowest wear rate at different varied particle sizes.
To confirm the predicted optimum Wear Rate, a confirmatory experiment was carried out with the optimum set of parameters A2B2C4D4. The confidence interval calculated from Equation 3 showed that the interval lies on ±0.00021mm3/N/m of the predicted optimal Wear Rate.
$$Confidence interval=\sqrt{{f}_{\propto (1,{DoF}_{e})}\times {V}_{e}\times \left(\frac{1}{E}+\frac{1}{R}\right)}$$
3
\({f}_{\propto (1,{DOF}_{e})}\) is the f ratio tabulated (between 1 and DoFei.e. the degree of freedom of error), Ve is the variance of error, and R is the number of replications. E=total number of experiments/(1+total degree of freedom of factors).
A composite material was developed with the optimum material combination A2B2C4D4 which is Al-Si-Mg/MSSA composite with stirring time, processing temperature, MSSA content, and particle size of 60s, 720℃, 20%, and 25µm respectively obtained as the best or optimal composition. The wear rate test was carried out on three samples. The result of the confirmation test is presented in the observation Table 4.
Table 4
Observation of Wear Rate Confirmation Test
S/N | Trial Number | Average Wear Rate (mm3/N/m) | S/N Ratio (dB) |
---|
1 | 2 | 3 |
---|
1 | 0.00151 | 0.00151 | 0.00153 | 0.001517 | 56.38 |
Table 4 shows the result of the confirmatory test. The average Wear Rate (mean) of the confirmatory material was 0.001517mm3/N/m which was within the confidence interval such that (0.00168mm3/N/m - 0.00021 mm3/N/m) < 0.001517mm3/N/m < (0.00168mm3/N/m + 0.00021 mm3/N/m) which is 0.00147mm3/N/m< 0.001517mm3/N/m < 0.00189mm3/N/m.The predicted optimum wear rate and the experimental optimum wear rate is presented in Table 5.
Table 5
Confirmatory Test Result for the Optimal Wear Rate of Al-Si-Mg/MSSA Composite
| Optimal Process Parameter Settings | Predictive Values | Experimental Values |
---|
S/N ratio (dB) | A2B2C4D4 | 40.1804 | 56.38 |
Mean Wear Rate mm3/N/m) | A2B2C4D4 | 0.00168 | 0.001517 |
Wear Modeling
A mathematical model for the combination of stirring time (A), Processing temperature (B), MSSA content (C), and Particle size (D) was derived from regression analysis carried out using the Minitab® 19 statistical software which was used for the prediction of the Wear Rate properties of the developed composite. The regression analysis model is presented in Table 6.
Table 6
Regression analysis model for Wear Rate
Term | Coef | SE Coef | T-Value | P-Value | VIF |
---|
Constant | 0.04207 | 0.0091 | 4.62 | 0.001 | |
Stirring time (s)(A) | 0.000173 | 0.000965 | 0.18 | 0.861 | 1 |
Processing Temp. (℃)(B) | 0.000435 | 0.000386 | 1.13 | 0.284 | 1 |
MSSA Content (wt.%)(C) | -0.000146 | 0.000039 | -3.8 | 0.003 | 1 |
Particle Size (µm)(D) | -0.000615 | 0.000386 | -1.59 | 0.139 | 1 |
R-Square=0.9032 |
Regression Equation
Wear Rate = 0.538 - 0.00689 A + 0.000134 B - 0.00332 C - 0.00073 D (4)
Table 6 shows the regression analysis model for the wear rate. Also, equation 4.6 shows the regression model for the wear rate for the factors considered. R-Square value of 90.32% shows the accuracy of the regression model developed. It explains the suitability of the model in predicting the wear rate under the factors considered. A comparison of the predicted wear rate using the regression equation and the experimental values of the Al-Si-Mg/MSSA composite is compared in Figure 9.
Microstructural Analysis
Microstructural Analysis Using SEM
Figure 10 shows an almost uniform distribution of Al-Si-Mg alloy consisting of primary grains of α-Al solid solution (white) surrounded by interdendritic regions of coarse plates of Al-Si eutectic (deep black) in which various intermetallic phases are present including the precipitates of Mg2Si intermetallic compound. etched with Keller’s solution.
At 5%wt content, the mango shell ash (MSSA) particles reinforcement in the grain boundaries of the Al-Si-Mg matrix was observed. The structure reveals the precipitates of Mg2Si and platelet of eutectic Si particles in α-Al matrix with (MSSA) particles.
Also, at 15% wt MSSA content, there was more presence of the reinforcement within the grain boundaries of the Al-Si-Mg matrix. The structure revealed the precipitates of Mg2Si and networks of eutectic Si particles in α-Al matrix with a fairly uniform distribution of mango seed shell ash (MSSA) particles. This showed that there was good interfacial bonding between the 15% MSSA particles and the Al-Si-Mg matrix. The presence of magnesium in the matrix helps in enhancing the wettability of the MSSA particles in the metal matrix.
A higher percentage of the presence of reinforcement within the grain boundaries of Al-Si-Mg matrix was observed at the 20% wt content of MSSA reinforcement. The structure revealed the precipitates of Mg2Si and networks of eutectic Si particles in α-Al matrix with non-uniform distribution of mango seed shell ash particles (MSSAp). The excess presence of reinforcement (MSSAp) beyond 15% resulted in a poor distribution of MSSAp in the Aluminium matrix. This made the composite slurry, too thick, and reduce the fluidity of the molten metal which adversely affected the mechanical and physical properties of this sample. etched with Keller’s solution.