Sliding Wear Response of Beryl Reinforced Aluminum Composite - A Factorial Design Approach

Al-Beryl MMCs were successfully fabricated using powder metallurgy route. Processing conditions such as beryl content and particle size were varied and its influence on dry sliding wear response was studied. Effect of test parameters like applied load and sliding distance on wear performance of Al-Beryl MMCs were discussed detail. Sliding wear tests were conducted using a pin on disc machine based on the 24 (4 factors at 2 levels) factorial design. Analysis of variance (ANOVA) was performed to obtain the contribution of control parameters on wear rate. The present study shows that wear resistance of Al-beryl MMCs not only depends on the beryl content but also influenced by normal load, sliding distance and particle size. The results show that most significant variables affecting wear rate of Al - beryl MMCs are size of the beryl particles (22%), beryl content (19.60%), sliding distance (18.47%), and normal load (10.30%). The interaction effects of these parameters are less significant in influencing wear rate compared to the individual parameters. The correlation between sliding wear and its parameters was obtained by multiple regression analysis. Regression model developed in the present study can be successfully implemented to predict the wear response of Al-Beryl MMCs.


Introduction
Aluminium metal matrix composites (AMMCs) possess unique properties such as high elastic modulus, tensile strength and wear resistance [1] and are used as brake rotors, pistons, connecting rods, engine blocks and bearings [2]. Worldwide attention has been focused on the processing and fabrication of AMMCs due to favorable manufacturing costs and performance [3]. Two major processing techniques that have been found suitable for these composites are powder metallurgy (P/M) and liquid metallurgy vortex technique (LMVT) [4]. The most commonly employed metal matrix composite system consists of Al reinforced with hard ceramic particles usually silicon carbide and alumina [5,6]. These composite materials showed different strengthening mechanisms when compared with conventional metallic materials [7]. The presence of hard ceramic particles has endowed these composites with improved tribological characteristics. These properties along with good specific 1 strength and modulus make them good candidate materials for many engineering applications where sliding contact is experienced. Among various ceramic additions to Al, SiC has been given greater attention by many researchers. However, Al-SiC MMCs still has some limitations such as the formation of Al 4 C 3 during high temperature synthesis, which impairs poor mechanical properties. Thus, efforts have been made to overcome such problems by incorporating reinforcing materials such as beryl which is naturally occurring ceramic material. AMMCs generally posses superior wear resistance compared with unreinforced aluminum. The processing conditions that control the wear performance of Al-Beryl MMCs are beryl content and size of the beryl particles. Quantitative analysis of reinforcement distribution in Al matrix is not widely studied. Moreover, a homogeneous distribution of reinforcement is responsible for increased wear resistance [11][12][13]. The present work is focused to study the influence of processing conditions such as beryl content and beryl particle size on dry sliding wear behaviour of Al-Beryl MMCs. Also, the work is aimed to understand the effect of variation of test parameters like applied load and sliding distance on wear performance of Al-Beryl MMCs.

Materials and Processing
Al powder having a density of 2.71 g/cc and beryl with density 2.64 g/cc were taken as starting materials. The chemical composition of Al and beryl is shown in Table 1 and 2. Beryl with chemical formula Be 3 Al 2 Si 6 O 18 is a naturally occurring ceramic particle which is abundantly found in many parts of India. Processing of AMMCs using LMVT showed a non uniform distribution of ceramic particles in Al matrix due to the difference between the densities of Al matrix and reinforcement material. As a result, beryl having a density almost nearer to density of Al was selected as a reinforcement particle. Many processing methods such as LMVT and P/M are available for fabrication of AMMCs. In case of LMVT matrix is melted in a crucible and reinforcement particles are added to the molten Al. The process can produce efficient castings of AMMCs but has a limitation. The weight percentage of reinforcement cannot be more than 15 Wt. %. Increasing particle size leads to more pull-off force due to Vander walls forces in which attraction depends on first power of particle size. It means increasing particle size leads to increasing Vander walls forces which may lead to non uniform distribution of reinforcement in casting. On the other hand, researchers have showed many limitations for using nano and sub-micron sized reinforcement particles in LMVT because of their tendency to agglomerate. Large difference in densities between the matrix and reinforcement may also lead to settling down of reinforcement particles while processing through LMVT. To overcome such problems P/M is used to fabricate Al -Beryl MMCs. In case of P/M, reinforcement up to 30 Wt. % can be added to the Al matrix without any settling down problems. As a result, the distribution of beryl in Al matrix is expected to be uniform. Beryl was procured in the form of stones and was crushed to powder form using a ball mill. A proper ball to powder ratio was maintained to avoid powder agglomeration. Crushed beryl particles were sieved to segregate into various sizes. Particle Size Analysis (PSA) was carried out after sieving. Fabrication of Al-Beryl MMCs was carried out by varying the size of the beryl particles and beryl content. Beryl particles of sizes 108 μm (coarse) and 38 μm (fine) were used to fabricate Al-Beryl MMCs. Percentage of beryl content was varied by 5%, 10% and 15% by weight.

Sliding wear test
Dry sliding wear test was conducted on Al-Beryl MMCs using a pin-on-disc test apparatus as per ASTM G99-95 standards. The standard wear specimen (pin) having a diameter of 10mm and 40 mm height was required to perform wear test. Sintered Al-Beryl samples were having a thickness of 10 mm. These samples were adhered to a steel pin to obtain required thickness as shown in Figure 1.

Figure 1. Wear test specimens of Al -Beryl MMCs
Before wear testing, the specimen surface was polished with a 400-grit emery paper to permit proper contact between the specimen surface and the abrasive media. The initial weight of the specimen was measured in a single pan electronic weighing machine with least count of 0.0001 g. During the test the pin was pressed against EN32 steel disc by applying the normal load of 0.5 and 0.75 kg. After running through a fixed sliding distance, the specimens were removed, cleaned with acetone, dried and weighed to determine the weight loss due to wear. The difference in the weight measured before and after test gave the sliding wear of the composite specimen and then the volume loss was calculated. The sliding wear of the composite was studied as a function of the volume percentage of the reinforcement, sliding distance, the applied load and the sliding distance.

2 k Factorial Design
Estimating the effects of factors like percentage reinforcement of beryl, Size of beryl particles, load and sliding distance on wear rate with a minimal number of tests is crucial for being able to optimize the output of the process [15]. Factorial Experiments are used to investigate the effects of two or more factors on the output response of a process. The major advantage of this technique is to find out the possible interaction between the parameters. A two-level full factorial design of experiments was used in the present study. Four parameters were varied on two levels i.e. upper level and lower level. The upper level and lower level of the four parameters i.e. beryl percentage, applied load, sliding distance and size of beryl particles used in the present study are reported in Table 3. To develop the linear regression equation from the experimental values, one must conduct at least 2 k number (where k stands for number of parameters) of experiments. Following this concept, sixteen sets of wear test experiments as reported in Table 4 were conducted and each set was repeated three times. The average of the response variables were used for the calculation. The upper level of beryl percentage, applied load, sliding distance and beryl particle size are 15 wt%, 0.75 kg, 1200 m and 108 μm respectively. The lower level of beryl percentage, applied load, sliding distance and beryl particles size are 5 wt%, 0.5 kg, 400 m and 38 μm respectively.
In order to find the significance of each parameter a design matrix as shown in Table 5 has been developed. The effect beryl reinforcement percent by weight on wear rate of Al -Beryl MMC is calculated using equation (1).
Similar equations were used to find the effect of other parameters and their interactions. In 2 k designs, the magnitude of the factor effects indicates which variables are important. Analysis of variance (ANOVA) was used to confirm the significant factors.

Multiple Regressions
The relationship between the control parameters (Reinforcement percent ( ), normal load ( ), Sliding Distance ( ), Particle Size (D)) and the output performance (wear rate) are obtained by multiple regression analysis. Ultimately, the following regression models are fitted to the wear rate.

Particle size analysis (PSA)
Particle size influences many properties of particulate materials and is a valuable indicator of quality and performance. The size and shape of powders influences flow and compaction properties. Particle size analysis of beryl powders is carried out using Mastersizer 2000, which confirms to ISO13320-1 guidelines. The results are shown in Figure 2 and Figure 3. It can be observed from PSA results that the samples collected after sieving were in the range of 108 μm and 38 μm.

Optical studies
Scanning electron microscope (SEM) images of Al powder as in Figure 4 shows aluminum particles were of uniform size and there are no flakes present in the powder. SEM images of crushed beryl powders were shown in Figure 5 which confirms that there is no particle agglomeration and also the shape of the particles was uniform. Optical images of Alberyl MMCs were shown in Figure 6. It can be observed that beryl particles were uniformly distributed throughout the matrix.

Effect of Control Parameters on Wear Rate
The design matrix for four parameters each at two levels along with the results of the wear tests are presented in Table 6. Effect of beryl reinforcement on wear rate was found using equation (1). Similar equations were used to find the effect of other parameters and their interactions. The effects of these parameters and their contribution on wear rate are listed in Table 7.  It can be observed from Table 7 that the effect of beryl content was negative indicating that increasing the beryl content from low level (5% by weight) to a high level (15% by weight) will decrease the wear rate. This is attributed to the increase of hardness with beryl concentration. The depth of wear grooves depends on the hardness of the specimen surface. The higher the hardness, the more shallow and finer is the wear grooves, thus leading to less wear rate. Effect of load during wear test is positive indicating that increasing the load form low level (0.5 kg) to high level (0.75 kg) will increase the wear rate. Effect of size of beryl particles on wear rate is positive which indicates that on increasing the particle size of the beryl from low level (38μm) to a high level (108 μm) will increase wear rate. It is reported that the wear rate depends on the actual microscale contact made by the beryl particles [17,18]. With the increase of beryl particle size, the effective load on each particle increases due to variation in actual contact area and they have greater tendency for large penetration. This leads to deeper and wider abrasive grooves and finally causes more wear. The percentage contribution of each parameter and their interactions are documented in Table 7. It can be observed that the beryl content (19.6%), the normal load (10.3%), the sliding distance (18.47%) and the size of beryl particles (22%) are significant factors that affect the wear performance of Al-Beryl MMCs than their interactions. The interaction between beryl content and beryl particle size (6.47%) is the significant interaction model terms.

Statistical Analysis of Variance (ANOVA)
ANOVA is a statistical design method used to break up the individual effects from all control factors. The percentage contribution of each control factor is employed to measure the corresponding effect on the quality characteristic [19]. Tables 7 show the results of statistical analysis of variance. The error contribution in the ANOVA for wear rate is very less. The present analysis indicates that control parameters selected in the study have both statistical and physical significance as the percentage contribution is greater than the error.
(3) 2 k factorial design and ANOVA tests confirm that main effect of the parameters are significant than their interactions and hence the equation (3) was modified by neglecting the interactions of the parameters. (4) The validity of equation (4) Table 9. The variations between the experimental and the calculated values as reported in Table 9 are very less.

Conclusions
Al-Beryl MMCs were successfully prepared by P/M and synthesized to dry sliding wear test. Effect of processing conditions such as beryl content and particle size were varied and its influence on dry sliding wear response was studied. Test parameters like applied load and sliding distance were varied and studied in detail. 2 k factorial design approach was successfully implemented to find out the significance of individual parameters and their interactions. ANOVA was used to confirm the results of 2 k factorial design approach. A linear regression equation was developed to predict the wear rate at the intermediate points and the equation was validated using experimental values. A complete analysis of worn out surfaces were carried out using scanning electron microscope. The following conclusions were drawn from the present study (i) Factorial design approach is an excellent tool and is used to identify the significance of various parameters on wear rate. (ii) Effect of processing conditions like beryl content, particle size and effect of test parameters like normal load and sliding distance are more significant than their interactions on wear behavior of Al-Beryl MMCs. (iii) Interaction between beryl content and particle size has greater influence on wear behavior of Al-Beryl MMCs among all other interactions. (iv) The percentage contribution of beryl content, normal load, sliding distance and beryl particle size are 19.6%, 10.3%, 18.47% and 22% respectively. (v) The influence of beryl particle size has more effect on wear behavior of Al-Beryl MMCs (vi) Regression equation developed during the present study can be successfully implemented to predict the wear behavior of Al-Beryl MMCs.