# Synthesis and Experimental Investigations of Tribological and Corrosion Performance of AZ61 Magnesium Alloy Hybrid Composites

Authors: R. Venkatesh; C. Ramesh Kannan; S. Manivannan; M. Vivekanandan; J. Phani Krishna; Amine Mezni; Saiful Islam; S. Rajkumar
Journal: Journal of Nanomaterials
 (2022)

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## Abstract

Magnesium alloy is the light weight material compared to aluminium alloy, and it possesses high strength; these alloys are used to manufacturing of vehicle parts. Magnesium alloy has extreme mechanical and thermal properties, and it is applied to aerospace applications. This study planned to improve the tribological and corrosion resistance of AZ61 magnesium alloy with reinforcement of boron carbide (B4C) and zirconium dioxide (ZrO2). Magnesium alloy hybrid composites are fabricated through stir casting process. Tribological and corrosion performance are analyzed through Taguchi L27 Orthogonal Array. In the tribological analysis, four parameters are involved such as % of reinforcement (4%, 8%, and 12%), disc speed (1 m/s, 2 m/s, and 3 m/s), normal load (30 N, 40 N, and 50 N), and sliding distance (1300 m, 1500 m, and 1700 m). Similarly, in salt spry corrosion analysis, four parameters are influenced used such as % of reinforcement (4%, 8%, and 12%), pH (7, 8, and 9), temperature (30°C, 35°C, and 40°C), and hanging time (30 hrs, 40 hrs, and 50 hrs). From this analysis, percentage of reinforcement is highly influenced in wear test, and in corrosion test, temperature is extremely influenced.


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## Body

## 1. Introduction

Normally, the composite materials are offered excellent mechanical properties and thermal properties. In composite preparation, the matrix material and reinforced particle selections are highly toughest one due to obtain of the desired properties [1]. Naturally, the pure magnesium is the light weight material compared to aluminum; it has 33% lighter in similar manner 75% lighter than steel material [2]. Magnesium possesses low density, and particular properties are lifting the consuming level of magnesium. For recent trends, the magnesium and its alloys are used in the high end applications. Magnesium is having some good quality characters, namely, excellent manufacturability, easy to fusion, and higher machinability [3–5]. All these points are considered to selection of materials with omitting of aluminium and such other materials. In machinability point of view, the magnesium has 50% higher than aluminium and possesses more energy [6–8]. In automobile sectors, magnesium is one of the substitute materials for aluminium for making of steering shaft, pistons, and brake components [9]. In major consideration in the engine design, the magnesium reduces the weight of the engine compared to cast iron [10–12]. It is a suitable one for replacing of cast iron engine and improving the vehicle mileage as well as reducing the fuel consumption. In the magnesium material, the wear occurrence takes place in moderate range but addition of reinforced particles is influenced to reduce the wear rate of the magnesium [13–15]. Hybrid composites generally possess high wear resistance as well as corrosion resistance even influencing of high performance parameters [16]. Taguchi optimization is one of the statistical tools to improve the mechanical properties, increasing the corrosion resistance, reduced the wear rate by the way of parameter optimization [17–20]. The main objective of this experimental work is focusing on to prepare the magnesium hybrid composites with influencing of boron carbide and zirconium oxide-reinforced particles. Further study of wear and corrosion rate of the fabricated composites is conducted through Taguchi tool.


## 2. Materials and Methods

In this experimental investigation, 2 kg of AZ61 magnesium alloy is purchased from the Andavan Arul Alloys, Chennai. Reinforced particles of boron carbide and zirconium dioxide are procured from Ashoka Marketing Agencies, Chennai, by each 500 g. Stir casting methodology is considered for this investigation to make a high strength magnesium alloy hybrid composites [21]. Bottom pouring stir casting equipment is used for this experimental work. Agitation process is controlled by electric motor in the stir casting process.


## 3. Experimental Work

Stir casting process is one of the economical ways to produce the hybrid composites within a short period. Initially, the reinforced particles are preheated in the crucible; different weight percentages (4%, 8%, and 12%) of boron carbide and zirconium oxide are preheated at 450°C for 5 hours in the crucible [22]. The preheating process remove the impurities present in the reinforced particles. Pure magnesium alloy is heated by applying of 800°C in the bottom pouring furnace; further, the preheated reinforce particles are mixed to the pure magnesium alloy. Mixing of preheated reinforced particles and the pure magnesium alloy are mixed well by using stirring action, the stirring process is controlled by electric controller in the motor [23]. Stirring speed is maintained as 400 rpm with 1 hour. After stirring action, the molten material is pouring into the die and allowed to cool; further, the cooled material is separated from the die. The required dimensions of wear and corrosion samples are sliced out from the casted magnesium hybrid composites.


### 3.1. Wear Test

Wear analysis is conducted through DUCOM model dry sliding wear test apparatus as shown in Figure1. Specimens are prepared as per the ASTM G99 standard under the dimensions of 12 mm diameter and 30 mm length. Initially, the disc and specimens are cleaned well by using, and then, each sample is weighted initially with the help of digital balance [24]. EN 32 steel disc with 65 HRC is used for conducting of dry sliding wear test; different process parameters are involved to conduct the wear test such as % of reinforcement, disc speed, normal load, and siding distance.Figure 1
Dry sliding wear test apparatus.The sample is placed vertically against to rotating disc; time taken to conduct wear test per sample is 20 min. Finally, after conducting the wear test, the samples are weighted to calculate the mass loss. Figure2(a) illustrates the 27 numbers of wear test specimens.Figure 2
(a) Image of wear test specimens. (b) Image of salt spray test specimens.
(a)(b)


### 3.2. Salt Spray Test

Salt spray test is one of the faster methods to analyze the corrosion resistance of the materials. In this work, initially, the samples are prepared as per the ASM standard ax (ASTM B117) with the dimensions of 30 mm diameter and 10 mm thickness. Samples are cleaned well and weighted; the initial weights are noted carefully for evaluating the difference of mass loss and also find the corrosion rate. Figure2(b) shows the salt spray test specimens; initially, the specimens are loaded in the salt spray chamber such as all the specimens are hung in the chamber [25]. The salt spray model is CARELAB with the dimensions of 650mm×450mm×4010mm. After loading the samples, the chamber cabin door is closed; using an atomizer, the 5% of NaCl solution is continually sprayed on the specimen’s surfaces [26]. The salt spray is achieved by using of pump circulation with constant flow rate. After reaching the specified time period, the specimens are taken out from the chamber and cleaned well with using of running water; further, the specimens are dried. All specimens are weighed and calculate the difference of mass loss [27].Table1 presented the wear test parameters and their levels; in wear test, four parameters such as % of reinforcement, disc speed, normal load, and sliding distance were selected. All four parameters have three levels ton satisfying L27 OA. The wear rate is obtained with
(1)WearrateWI=W1−W2Time×Density.Table 1
Wear test process parameters and their levels.
S. no.ParametersLevel 1Level 2Level 31% of reinforcement48122Disc speed (m/s)1233Normal load (N)2030404Sliding distance (m)130015001700


## 3.1. Wear Test

Wear analysis is conducted through DUCOM model dry sliding wear test apparatus as shown in Figure1. Specimens are prepared as per the ASTM G99 standard under the dimensions of 12 mm diameter and 30 mm length. Initially, the disc and specimens are cleaned well by using, and then, each sample is weighted initially with the help of digital balance [24]. EN 32 steel disc with 65 HRC is used for conducting of dry sliding wear test; different process parameters are involved to conduct the wear test such as % of reinforcement, disc speed, normal load, and siding distance.Figure 1
Dry sliding wear test apparatus.The sample is placed vertically against to rotating disc; time taken to conduct wear test per sample is 20 min. Finally, after conducting the wear test, the samples are weighted to calculate the mass loss. Figure2(a) illustrates the 27 numbers of wear test specimens.Figure 2
(a) Image of wear test specimens. (b) Image of salt spray test specimens.
(a)(b)


## 3.2. Salt Spray Test

Salt spray test is one of the faster methods to analyze the corrosion resistance of the materials. In this work, initially, the samples are prepared as per the ASM standard ax (ASTM B117) with the dimensions of 30 mm diameter and 10 mm thickness. Samples are cleaned well and weighted; the initial weights are noted carefully for evaluating the difference of mass loss and also find the corrosion rate. Figure2(b) shows the salt spray test specimens; initially, the specimens are loaded in the salt spray chamber such as all the specimens are hung in the chamber [25]. The salt spray model is CARELAB with the dimensions of 650mm×450mm×4010mm. After loading the samples, the chamber cabin door is closed; using an atomizer, the 5% of NaCl solution is continually sprayed on the specimen’s surfaces [26]. The salt spray is achieved by using of pump circulation with constant flow rate. After reaching the specified time period, the specimens are taken out from the chamber and cleaned well with using of running water; further, the specimens are dried. All specimens are weighed and calculate the difference of mass loss [27].Table1 presented the wear test parameters and their levels; in wear test, four parameters such as % of reinforcement, disc speed, normal load, and sliding distance were selected. All four parameters have three levels ton satisfying L27 OA. The wear rate is obtained with
(1)WearrateWI=W1−W2Time×Density.Table 1
Wear test process parameters and their levels.
S. no.ParametersLevel 1Level 2Level 31% of reinforcement48122Disc speed (m/s)1233Normal load (N)2030404Sliding distance (m)130015001700


## 4. Results and Discussion

### 4.1. Wear Analysis

Influencing of four parameters and three levels was extremely influenced to estimate the wear rate of specimens. Table2 presented the wear input parameters and the response of wear rate. From this wear test analysis, the minimum wear rate was recorded as 0.0018 mm3/m. The minimum wear rates attained by the influence of parameters were 12% of reinforcement, 1 m/s of disc speed, 40 N of normal load, and 1500 m of sliding distance. On the contrary, the maximum wear rate was occurred as 0.051 mm3/m by influencing of 8% of reinforcement, 1 m/s of disc speed, 30 N of normal load, and 1700 m of sliding distance.Table 2
Response table for means (wear rate).
Exp. runs% of reinforcementDisc speed (m/s)Normal load (N)Sliding distance (m)Wear rate (mm3/m)1412013000.00382412013000.0463412013000.00344423015000.03415423015000.01176423015000.0347434017000.00628434017000.0279434017000.007110813017000.002311813017000.05112813017000.008613824013000.007314824013000.012815824013000.014816832015000.003917832015000.004818832015000.0156191214015000.0028201214015000.0126211214015000.0018221222017000.0107231222017000.0061241222017000.0037251233013000.0027261233013000.0147271233013000.0025Table2 and Table 3 presented the response tables of wear rate; these tables presented the higher influence parameter in priority order. Higher priority was illustrated by the delta and rank order; the percentage of reinforcement was higher priority in the wear test. Normal load was the second priority, disc speed was the third priority, and sliding distance was fourth priority. Optimal parameters of the wear rate was found as 12% of reinforcement, 3 m/s of disc speed, 40 N of normal load, and 1500 m of sliding distance.Table 3
Response table for signal to noise ratios (wear rate); smaller is better.
Level% of reinforcementDisc speed (m/s)Normal load (N)Sliding distance (m)10.0192670.0147260.0106830.01205220.0132460.0150280.0180090.01328230.0064730.0092330.0102940.013652Delta0.0127940.0057950.0077150.001601Rank1324Figures3 and 4 represented the main effects plot for means and S/N ratios of the wear rate; increasing of reinforcement percentage decreases the wear rate. Maximum reinforcement 12% offered minimum wear rate; further increasing of disc speed also reduces the wear rate. Maximum level 3 m/s of disc speed offered minimum wear rate. Influencing of normal load such as 20 N to 30 N wear rates was increased; further, 30 N to 40 N of normal load, the wear rate was decreased. Finally, the 40 N of normal load recorded minimum wear rate. Consideration of sliding distance, 1500 m of sliding distance offered minimum wear rate; further increasing of 1500 m and 1700 m of sliding distance, the wear rate was increased. Figure 5 highlights the residual plot for the wear rate.Figure 3
Main effects plot for mean (wear rate).Figure 4
Main effects plot for S/N ratios (wear rate).Figure 5
Residual plots for wear rate.Normal probability plot represents that all the points were lying on the mean line; it tell about the selected parameters, and the levels are good one. In versus fits plot, all the points were distributed uniformly, and within the limits, similar trends were observed in the versus order plot. All these points demonstrate that chosen model is appropriate one. In histogram plot, all the rectangles were skewed in normal position. Figure6 demonstrates the parallel set plot for wear rate; Figure 6(a) shows the correlation between % of reinforcement and disc speed. From this parameter connection, the minimum wear rate was recorded by 12% of reinforcement and 1 m/s of disc speed.Figure 6
Parallel set plot: (a) % of reinforcement vs. disc speed; (b) disc speed vs. normal load; (c) normal load vs. sliding distance; (d) normal load vs. % of reinforcement.
(a)(b)(c)(d)Figure6(b) illustrates the relations between disc speed and normal load. In this analysis, 1 m/s of disc speed and 40 N of normal load produced minimum wear rate. Figure 6(c) presents the connection between normal load and sliding distance. Minimum wear rate was registered by 40 N of normal load and 1500 m sliding distance. Figure 6(d) shows the minimum wear rate by 20 N of normal load and 12% of reinforcement.


### 4.2. Corrosion Analysis

Table4 illustrates the corrosion input parameters and the response of corrosion rate. From this corrosion test analysis, the minimum corrosion rate was registered as 0.112 mm/year. The minimum corrosion rates obtained by the influence of parameters were 8% of reinforcement, 7 pH value, 35°C of temperature, and 50 hrs of hanging time.Table 4
Summary of corrosion test process parameters and corrosion rate.
Exp. runs% of reinforcementpHTemperature (°C)Hanging time (hrs)Corrosion rate ×10-3 (mm/year)14730300.13524730300.17834730300.14244835400.13154835400.11864835400.12774940500.15384940500.14994940500.176108735500.112118735500.119128735500.125138840300.134148840300.142158840300.155168930400.193178930400.143188930400.1611912740400.1522012740400.1492112740400.1722212830500.1342312830500.1212412830500.1822512935300.1392612935300.1272712935300.116Table5 and Table 6 presented the response tables of corrosion rate; these tables illustrated the higher influence parameter in priority order. Based on the delta and rank values, the higher priority was decided; from this analysis, chamber temperature was a higher priority in the corrosion test. Further, the parameters were followed by pH value, hanging time, and percentage of reinforcement. Optimal parameters of the corrosion rate was recorded as 8% of reinforcement, 8 pH value, 35°C of temperature, and 50 hrs of hanging time.Table 5
Response table for means (corrosion rate).
Level% of reinforcementpHTemperature (°C)Hanging time (hrs)10.14540.14270.15430.140920.14270.13820.12380.149630.14360.15080.15360.1412Delta0.00280.01260.03060.0087Rank4213Table 6
Response table for signal to noise ratios (corrosion rate); smaller is better.
Level% of reinforcementpHTemperature (°C)Hanging time (hrs)116.7616.9516.1517.01216.9617.1518.1416.54316.8316.4516.2617.01Delta0.200.701.980.47Rank4213Figures7 and 8 illustrated the main effects plot for means and S/N ratios of the corrosion rate; increasing of reinforcement percentage decreases the corrosion rate. Minimum corrosion rate was obtained by 8% of reinforcement; similarly, increasing of pH value the corrosion rate was decreased. Minimum corrosion rate was recorded by influencing of 8 pH value. Increasing of temperature from 30°C to 35°C decreases the corrosion rate, 35°C of temperature offered minimum corrosion rate. Higher hanging hours such as 50 hours recoded minimum corrosion rate.Figure 7
Main effects plot for means (corrosion rate).Figure 8
Main effects plot for S/N ratios (corrosion rate).Figure9 presented the residual plots for corrosion rate; this figure comprises the four plots in a single plot. From all the four plots, the data points were distributed uniformly and within the limits; hence, the selected parameters and model were suitable one. In the normal probability plot, all the data points touch the mean line; it was denoted that the model was accurate one.Figure 9
Residual plots for corrosion rate.Figure10 illustrates the contour plot for corrosion rate; Figure 10(a) represents the correlation between % of reinforcement and pH value. In both of these parameters’ correlation, the minimum corrosion rate was recorded by 8% of reinforcement and 8 pH value. Figure 10(b) presented the pH value and temperature relations; for that, these parameters offered a minimum corrosion rate by 8 pH value and 35°C of temperature. Figure 10(c) presented the correlation between temperature and hanging time; both were offered a minimum corrosion rate such as 35°C of temperature and 50 hours of hanging time. Figure 10(c) demonstrates the connection between hanging time and % of reinforcement; 50 hours of hanging and 8% of reinforcement offered minimum corrosion rate.Figure 10
Contour plot: (a) % of reinforcement vs. pH value; (b) pH value vs. temperature; (c) temperature vs. hanging time; (d) hanging time vs. % of reinforcement.
(a)(b)(c)(d)Normally, the magnesium alloy material was light weight material; adding of reinforcement particles improves the wear properties. In stir casting process, the reinforced particles, namely, boron carbide (B4C) and zirconium dioxide (ZrO2), were highly melted and blended into the magnesium alloy. The uniform blending increases the mechanical properties of the magnesium composites; the enhanced strength reduces the wear rate of the composite and also reduces the corrosion. The hybrid reinforced particles make superior strength and offered excellent corrosion resistant to the composite material; it was evidently showed in the numerical analysis.


## 4.1. Wear Analysis

Influencing of four parameters and three levels was extremely influenced to estimate the wear rate of specimens. Table2 presented the wear input parameters and the response of wear rate. From this wear test analysis, the minimum wear rate was recorded as 0.0018 mm3/m. The minimum wear rates attained by the influence of parameters were 12% of reinforcement, 1 m/s of disc speed, 40 N of normal load, and 1500 m of sliding distance. On the contrary, the maximum wear rate was occurred as 0.051 mm3/m by influencing of 8% of reinforcement, 1 m/s of disc speed, 30 N of normal load, and 1700 m of sliding distance.Table 2
Response table for means (wear rate).
Exp. runs% of reinforcementDisc speed (m/s)Normal load (N)Sliding distance (m)Wear rate (mm3/m)1412013000.00382412013000.0463412013000.00344423015000.03415423015000.01176423015000.0347434017000.00628434017000.0279434017000.007110813017000.002311813017000.05112813017000.008613824013000.007314824013000.012815824013000.014816832015000.003917832015000.004818832015000.0156191214015000.0028201214015000.0126211214015000.0018221222017000.0107231222017000.0061241222017000.0037251233013000.0027261233013000.0147271233013000.0025Table2 and Table 3 presented the response tables of wear rate; these tables presented the higher influence parameter in priority order. Higher priority was illustrated by the delta and rank order; the percentage of reinforcement was higher priority in the wear test. Normal load was the second priority, disc speed was the third priority, and sliding distance was fourth priority. Optimal parameters of the wear rate was found as 12% of reinforcement, 3 m/s of disc speed, 40 N of normal load, and 1500 m of sliding distance.Table 3
Response table for signal to noise ratios (wear rate); smaller is better.
Level% of reinforcementDisc speed (m/s)Normal load (N)Sliding distance (m)10.0192670.0147260.0106830.01205220.0132460.0150280.0180090.01328230.0064730.0092330.0102940.013652Delta0.0127940.0057950.0077150.001601Rank1324Figures3 and 4 represented the main effects plot for means and S/N ratios of the wear rate; increasing of reinforcement percentage decreases the wear rate. Maximum reinforcement 12% offered minimum wear rate; further increasing of disc speed also reduces the wear rate. Maximum level 3 m/s of disc speed offered minimum wear rate. Influencing of normal load such as 20 N to 30 N wear rates was increased; further, 30 N to 40 N of normal load, the wear rate was decreased. Finally, the 40 N of normal load recorded minimum wear rate. Consideration of sliding distance, 1500 m of sliding distance offered minimum wear rate; further increasing of 1500 m and 1700 m of sliding distance, the wear rate was increased. Figure 5 highlights the residual plot for the wear rate.Figure 3
Main effects plot for mean (wear rate).Figure 4
Main effects plot for S/N ratios (wear rate).Figure 5
Residual plots for wear rate.Normal probability plot represents that all the points were lying on the mean line; it tell about the selected parameters, and the levels are good one. In versus fits plot, all the points were distributed uniformly, and within the limits, similar trends were observed in the versus order plot. All these points demonstrate that chosen model is appropriate one. In histogram plot, all the rectangles were skewed in normal position. Figure6 demonstrates the parallel set plot for wear rate; Figure 6(a) shows the correlation between % of reinforcement and disc speed. From this parameter connection, the minimum wear rate was recorded by 12% of reinforcement and 1 m/s of disc speed.Figure 6
Parallel set plot: (a) % of reinforcement vs. disc speed; (b) disc speed vs. normal load; (c) normal load vs. sliding distance; (d) normal load vs. % of reinforcement.
(a)(b)(c)(d)Figure6(b) illustrates the relations between disc speed and normal load. In this analysis, 1 m/s of disc speed and 40 N of normal load produced minimum wear rate. Figure 6(c) presents the connection between normal load and sliding distance. Minimum wear rate was registered by 40 N of normal load and 1500 m sliding distance. Figure 6(d) shows the minimum wear rate by 20 N of normal load and 12% of reinforcement.


## 4.2. Corrosion Analysis

Table4 illustrates the corrosion input parameters and the response of corrosion rate. From this corrosion test analysis, the minimum corrosion rate was registered as 0.112 mm/year. The minimum corrosion rates obtained by the influence of parameters were 8% of reinforcement, 7 pH value, 35°C of temperature, and 50 hrs of hanging time.Table 4
Summary of corrosion test process parameters and corrosion rate.
Exp. runs% of reinforcementpHTemperature (°C)Hanging time (hrs)Corrosion rate ×10-3 (mm/year)14730300.13524730300.17834730300.14244835400.13154835400.11864835400.12774940500.15384940500.14994940500.176108735500.112118735500.119128735500.125138840300.134148840300.142158840300.155168930400.193178930400.143188930400.1611912740400.1522012740400.1492112740400.1722212830500.1342312830500.1212412830500.1822512935300.1392612935300.1272712935300.116Table5 and Table 6 presented the response tables of corrosion rate; these tables illustrated the higher influence parameter in priority order. Based on the delta and rank values, the higher priority was decided; from this analysis, chamber temperature was a higher priority in the corrosion test. Further, the parameters were followed by pH value, hanging time, and percentage of reinforcement. Optimal parameters of the corrosion rate was recorded as 8% of reinforcement, 8 pH value, 35°C of temperature, and 50 hrs of hanging time.Table 5
Response table for means (corrosion rate).
Level% of reinforcementpHTemperature (°C)Hanging time (hrs)10.14540.14270.15430.140920.14270.13820.12380.149630.14360.15080.15360.1412Delta0.00280.01260.03060.0087Rank4213Table 6
Response table for signal to noise ratios (corrosion rate); smaller is better.
Level% of reinforcementpHTemperature (°C)Hanging time (hrs)116.7616.9516.1517.01216.9617.1518.1416.54316.8316.4516.2617.01Delta0.200.701.980.47Rank4213Figures7 and 8 illustrated the main effects plot for means and S/N ratios of the corrosion rate; increasing of reinforcement percentage decreases the corrosion rate. Minimum corrosion rate was obtained by 8% of reinforcement; similarly, increasing of pH value the corrosion rate was decreased. Minimum corrosion rate was recorded by influencing of 8 pH value. Increasing of temperature from 30°C to 35°C decreases the corrosion rate, 35°C of temperature offered minimum corrosion rate. Higher hanging hours such as 50 hours recoded minimum corrosion rate.Figure 7
Main effects plot for means (corrosion rate).Figure 8
Main effects plot for S/N ratios (corrosion rate).Figure9 presented the residual plots for corrosion rate; this figure comprises the four plots in a single plot. From all the four plots, the data points were distributed uniformly and within the limits; hence, the selected parameters and model were suitable one. In the normal probability plot, all the data points touch the mean line; it was denoted that the model was accurate one.Figure 9
Residual plots for corrosion rate.Figure10 illustrates the contour plot for corrosion rate; Figure 10(a) represents the correlation between % of reinforcement and pH value. In both of these parameters’ correlation, the minimum corrosion rate was recorded by 8% of reinforcement and 8 pH value. Figure 10(b) presented the pH value and temperature relations; for that, these parameters offered a minimum corrosion rate by 8 pH value and 35°C of temperature. Figure 10(c) presented the correlation between temperature and hanging time; both were offered a minimum corrosion rate such as 35°C of temperature and 50 hours of hanging time. Figure 10(c) demonstrates the connection between hanging time and % of reinforcement; 50 hours of hanging and 8% of reinforcement offered minimum corrosion rate.Figure 10
Contour plot: (a) % of reinforcement vs. pH value; (b) pH value vs. temperature; (c) temperature vs. hanging time; (d) hanging time vs. % of reinforcement.
(a)(b)(c)(d)Normally, the magnesium alloy material was light weight material; adding of reinforcement particles improves the wear properties. In stir casting process, the reinforced particles, namely, boron carbide (B4C) and zirconium dioxide (ZrO2), were highly melted and blended into the magnesium alloy. The uniform blending increases the mechanical properties of the magnesium composites; the enhanced strength reduces the wear rate of the composite and also reduces the corrosion. The hybrid reinforced particles make superior strength and offered excellent corrosion resistant to the composite material; it was evidently showed in the numerical analysis.


## 5. Conclusion

In this experimental investigation, magnesium alloy hybrid composites were prepared through stir casting process with reinforcement of boron carbide and zirconium oxide. Using of Taguchi analysis, the optimal parameters of the wear and corrosion test were evaluated successfully; finally, the minimum wear rate and corrosion rate were obtained, and the results were described as follows:(i)
From the wear test analysis, the minimum wear rate was recorded as 0.0018 mm3/m due to homogeneous mixture of the reinforced particles into the magnesium alloy composites. Higher percentage of reinforced particles improved the wear properties. In contrary, the lower percentage of reinforced particles is not influenced in the wear behavior of the composites; hence, the maximum wear rate was obtained in the wear test as 0.051 mm3/m. Optimal of the wear rate was recorded as 12% of reinforcement, 3 m/s of disc speed, 40 N of normal load, and 1500 m of sliding distance(ii)
In the salt spray corrosion test analysis, minimum corrosion rate was recorded as 0.112 mm/year owing to uniform distribution of reinforced particles into the magnesium alloy composites. From the corrosion rate analysis, the optimal parameters were registered as 12% of reinforcement, 3 m/s of disc speed, 40 N of normal load, and 1500 m of sliding distance. Percentage of reinforcement was highly influenced in the wear analysis, and the chamber temperature was extremely influenced in the salt spray corrosion analysis.



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