Effect of Experimental Parameters on Reciprocating Wear

Tribology Online, 4, 5 (2009) 115-126. ISSN 1881-2198

DOI 4.2474/trol.4.115

Japanese Society of Tribologists (http://www.tribology.jp/) Tribology Online, Vol. 4, No. 5 (2009) / 115

Article

Effect of Experimental Parameters on Reciprocating Wear Behavior of Al-Si-SiCp Composites under Dry Condition

Vamadevan Rajalekshmi Rajeev*, Dheerendra Kumar Dwivedi and Satish Chandra Jain

Department of Mechanical and Industrial Engineering, Indian Institute of Technology

Roorkee-247667, Uttarkhand, India *Corresponding author: [email protected]

( Manuscript received 15 May 2009; accepted 28 September 2009; published 15 October 2009 )

In this paper the nonlinear dry reciprocating wear behavior of three composites A319/15%SiCp A336/15%SiCp and A390/15%SiCp subjected to high temperature were reported. Composites were produced through liquid metal metallurgy route. Five controllable input parameters selected for the wear study were applied load, reciprocating velocity, sliding distance, counter surface temperature and silicon content in composites. Two output responses wear and coefficient of friction were measured. The input parameter levels were fixed through pilot experiment conducted in the indigenously developed reciprocating friction and wear test rig. The counter surface material used for the wear study was cast iron having Vickers hardness of 244 HVN. Wear study under dry condition was carried out through response surface methodology by considering five input parameters as variables and two output parameters as responses. It had been demonstrated through established equations that the nonlinearity is more pronounced with the increase in applied load and reciprocating velocity. Also it was found that high percentage silicon content composite exhibited a low wear compared to the low percentage silicon content composite. Moreover, the wear increased with increasing applied load, sliding distance and counter surface temperature and it decreased with silicon content in composites and square of reciprocating velocity.

Keywords: reciprocating wear, response surface methodology, mathematical model, high temperature, wear resistance

1. Introduction

The SiC reinforced aluminum silicon metal matrix composites (MMC) have been increasingly used in the automobile industry because of their high strength-to-weight ratio, good castability, and better high temperature strength over the unreinforced alloys. Potential applications of these composites may be found in many components such as brake rotors, cylinder heads and pistons that are used in tribological systems1). Several wear studies related to these applications have been conducted during the past decade. Almost all of them were performed using either pin-on-disk or block-on-ring testing machines where the composite material experienced only unidirectional sliding wear2-5). Alpas et al have extensively studied wear behavior of Al-Si alloys reinforced with SiC particles by using block-on-ring wear tests2,5). They proposed three wear rate regimes of the composites varying with sliding distance and applied load. An extensive review work on dry sliding wear characteristics of aluminum alloy based

composites was undertaken by Sannino and Rack6), and abrasive wear behavior by Deuis et al7) which summarize effect of reinforcement volume fraction, reinforcement size, sliding distance, applied load, sliding speed, hardness of the counter face and properties of the reinforcement phase on the dry sliding wear behavior of Al matrix composites. However, very few of these tests were reported under reciprocal sliding conditions where the same material may behave differently compared to that under unidirectional wear conditions8-10). High wear rate has been reported under reciprocating condition than unidirectional sliding11,12). For many industrial components, such as cylinder blocks and engine pistons, these composites are subjected to wear under reciprocating condition rather than unidirectional sliding. In unidirectional sliding the pin is held stationary while the disc is rotating at constant velocity. The piston in an engine reciprocates within the cylinder block sinusoidally. Therefore the pin-on-disc wear test rig cannot simulate the actual wear phenomenon of reciprocating wear condition. The present study aims to carry out experimentation in a

Copyright © 2009 Japanese Society of Tribologists 115

Vamadevan Rajalekshmi Rajeev, Dheerendra Kumar Dwivedi and Satish Chandra Jain


reciprocating friction wear test rig where the counter surface material (slider) is reciprocated through slider crank mechanism which in turn can simulate the actual condition prevails in an engine. It is therefore important to understand the reciprocal sliding wear behavior of these composites considering the fact that a number of industrial applications, such as engine cylinders, pistons etc., involve reciprocal sliding wear. Studies on wear performance under dry conditions are therefore of practical significance, and not enough investigations concerning the influence of combined effect of wear parameters on the dry reciprocating wear of the MMCs have been reported in the literature.

Further, research into the wear of composites has usually investigated the effect of a single factor, such as sliding distance, sliding speed or contact pressure, on the wear performance. However, attempt to predict wear of composites in terms of applied load, sliding distance, reciprocating velocity, counter surface temperature and silicon content in composites is lacking. It is possible to assess quantitatively the influence of each of the above variables separately on the wear and coefficient of friction of composites through deriving some empirical equations involving statistical analysis of the recorded data through response surface methodology. However, such an approach has not been adopted to examine the combined effect of five wear and friction test parameters on the adhesive wear response of aluminum alloy composites.

In view of the above, an attempt has been made to develop a linear regression equation for (a) calculating the adhesive wear of three aluminium alloy SiC particle composites taking into consideration the parameters like applied load, sliding distance, reciprocating velocity, counter surface temperature and silicon content in the composites, (b) quantifying the effect of each variables and their interaction on the wear and coefficient of friction of aluminium alloy composites and (c) compare the effect of each variable and their interaction on the wear and coefficient of friction of the composites. The corresponding theoretically calculated values of wear and coefficient of friction have been counter checked through experimentally observed ones.

2. Response surface methodology

The response surface methodology (RSM) is an empirical modeling approach for determining the relationship between various processing parameters and responses with the various desired criteria and searches for the significance of these process parameters in the coupled responses13). It is a sequential experimentation strategy for building and optimizing the empirical model. Therefore, RSM is a collection of mathematical and statistical procedures, and is good for the modeling and analysis of problems in which the desired response is affected by several variables. The mathematical model of the desired response to several independent

input variables is gained by using the experimental design and applying regression analysis14). In this study, the approximation of the mathematical model is proposed using the fitted second-order polynomial regression model, which is called the quadratic model. In this study, the experimental design adopts the centered central composite design (CCD) in order to fit the quadratic model of the RSM. The factorial portion of CCD is a full factorial design with all combinations of the factors at two levels (high, +1 and low, −1) and composed of the eight star points, and six central points (coded level 0) which is the midpoint between the high and low levels. The star points are at the face of the cube portion on the design which corresponds to an α value of 1. This type of design is commonly called the face-centered CCD.

The RSM is a sequential procedure and its procedure for determining the wear parameters with optimal performance characteristics including seven steps is summarized as follows: 1. Defining the independent input variables and desired responses with the design constraints 2. Adopting the face-centered CCD to plan the experimental design 3. Performing the regression analysis with the quadratic model of RSM 4. Calculating the statistical analysis of variance (ANOVA) for the independent input variables and to find which parameter significantly affects the desired response 5. Determining the situation of the quadratic model of the RSM and deciding whether the model of the RSM needs screening variables or not 6. Finding the optimum set of experimental factors that produces maximum or minimum value of responses. 7. Representing the direct and interactive effects of wear parameters on wear and coefficient of friction of composites through two dimensional and three dimensional graphs.

3. Experimental Methods

3.1. Materials The Al-Si alloys used for manufacturing of

aluminum matrix composites were based on A319, A336 and A390. These alloys provide excellent combination of strength, low coefficient of thermal expansion at elevated temperature and excellent wear resistance15). The SiC particles were used to fabricate the composite had an average particle size of 32 µm and average density of 3.2 g/cm3. The SiC particle reinforcement was fixed at 15-wt pct. The nominal chemical composition (in wt pct) of the matrix alloys are given in Table 1.

3.2. Preparation of the composites The liquid metallurgy technique was used to prepare

composite specimens16,17). In this process, matrix alloy was melted at 800°C and then the temperature was



lowered gradually below the liquidus temperature at 610°C to keep the matrix alloy in the semi-solid state. At this temperature, the preheated SiC particles at 720°C were introduced into the slurry and mixed. The composite slurry temperature was increased to molten state and then stirring was continued for 5 min at an average stirring speed of 325 rpm. The melt was then superheated above liquidus temperature and finally poured into mould of cast iron of size 40×40×250 mm3. The castings were solution heat treated at 500°C for 6 hours, water quenched at room temperature and precipitation hardened at 190°C for 12 hours. The optical microstructures of A319/SiCp, A336/SiCp and A390/SiCp heat-treated composite with uniformly distributed SiC particle in alloy matrix is evident from micrograph shown in Fig.1 (a, b & c). The measured density and Vickers hardness of the heat-treated composites are shown in Table 2.

Table 1 Composition of aluminum alloys (wt %) Si Fe Cu Mn Mg Ni Zn Ti Al A319 6 1 4 0.5 0.1 0.35 3 0.25 BalA336 12 1.2 1.5 0.35 0.7 2 0.35 0.25 BalA390 18 0.5 5 0.1 0.45 - 0.1 0.20 Bal.

Table 2 Density and hardness of heat-treated composites Composite Density(g/cm3) Hardness (HVN)A319/15wt%SiCp 2.67 148.3 A336/15wt%SiCp 2.51 162 A390/15wt%SiCp 2.42 240.2

3.3. Experimental setup and procedure A reciprocating wear test rig (Fig. 2) used to investigate

the dry sliding wear characteristic of the composite was fabricated as per ASTM G 133 - 05 standards. The wear specimen (pin) of 6 mm diameter and 30 mm length was cut from heat-treated samples. 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 the reciprocating counter surface made of grey cast iron plate (244 HVN) by applying the dead load. Counter surface was heated using a press fit element with a temperature controller for studying the effect of temperature on the wear of the composite. 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. During the wear testing, the relative humidity of the laboratory atmosphere was measured to vary between 60% and 65%. The frictional force was measured using four strain gauges mounted on a metallic ring of thickness 2 mm and diameter 100 mm as per Wheatstone bridge circuit. The four leads of the circuit were attached to a digital strain gauge indicator to get the strain in the form of digital output. The ring was calibrated using known weights up to 5 kg and the calibration curve was plotted and the same was used to convert the digital output to the corresponding tangential friction force (Fp). Knowing the normal force Fn (applied force), the coefficient of friction (COF) between the two materials tested was computed by using the following formula:

COF = Fp/Fn

(a) (b)

(c)

Fig. 1 Optical microstructure of heat-treated (a) A319/SiCp (b) A336/SiCp and (c) A390/SiCp composites


DOI 4.2474/trol.4.115


3.4. Plan of experiments The experiments were conducted as per the

response surface methodology. The resolution of the design used was 5 with five experimental parameters and two responses. Table 3 shows the levels of five experimental parameters. In the present investigation 25-1 face centred central composite design array was chosen, which has 32 rows and 5 columns (Table 4). The experimental parameters chosen for the experiments were (1) applied load (L), (2) sliding distance (D), (3) reciprocating velocity (V), (4) counter surface temperature (T) and (5) silicon content in composite (S). In this study, these parameters are chosen as the independent input variables. The study of reciprocating wear behavior of the composites and its significance lies in direct industrial applications such as in reciprocating machineries and passenger cars where the wear intensive region of the liner represents the upper section (top) against the cast iron cylinder. The combustion pressure acting radially on the piston ring is converted into normal force and it generally lies between 30 N and 100 N20). Hence, applied load in the present study was taken as the first wear and friction test parameter with the low, middle and high levels were fixed as 60 N, 90 N and 120 N respectively. Nesarikar et al12) have reported that the wear of the cast iron sliding against composite plate started to increase after a sliding distance of approximately 220 m for Al2O3-particle-reinforced aluminum alloy composites. Hence, the low and high ranges of sliding distance in the present case study were kept at 250 m and 750 m respectively while the middle level was fixed at 500 m. The typical cases for passenger car engines and reciprocating pumps are subjected to a sliding velocity of approximately 0.3 m/s20). Hence the low and high levels of reciprocating velocity in the present research were kept as 0.2 m/s and 0.4 m/s respectively while the middle level was fixed at 0.3 m/s. Martin et al10) conducted elevated temperature studies in the reciprocating wear of 2618 Al alloy reinforced with 15%SiC particulates and the corresponding alloy in the temperature range 20-200°C. The authors found that the mild wear region of the composite was extended up to 150°C that was 50°C higher for the composite as compared to its base alloy. They also found that at 200°C the specific wear of the peak aged composite after 288m of sliding was two orders of magnitude higher than that at 150°C and subsequently the test was stopped due to severe wear. Hence, in the present study, the high level temperature of the composites was fixed

at 200°C. Since 150°C was observed as the transition temperature for mild to severe wear for the above mentioned composite, in the present case also the middle level temperature was fixed at 150°C while the low level temperature was fixed at 100°C. It has been observed that addition of silicon in aluminum increases its wear resistance, increases fluidity and results in low shrinkage of the Al-Si alloys15). Si can be made to dissolve into Al to form a solid solution. However, there is a saturation point that limits how much Si can be dissolved into Al to form a solid solution. When Si is added above this particular saturation point, it will precipitate out in the form of hard, small Si particles. For an Al-Si system this saturation point is nearly 12%Si. Therefore Al alloys with less than 12%Si are referred to as hypoeutectic, those with close to 12%Si as eutectic and those with greater than 12%Si as hypereutectic. Hence, the mid value of composition is kept near the eutectic composition and is fixed at 12% Si (by wt). Also, it has been observed that eutectic and hypereutectic compositions of Al-Si alloys exhibit the highest wear resistance21). Hence, the upper level of composition of the alloy is considered as 18% Si (by wt). Since, the difference in level between the upper and middle level range is 6% Si (by wt), therefore the range of variation between the mid level and low level of alloy composition should also be 6% Si (by wt). Hence the lower range of alloy composition is fixed at 6% Si (by wt).

Table 3 indicates the factors and their levels. The experimental plan is generated using the stipulated conditions based on the face centred CCD and involves 32 runs as shown in Table 4. The investigated response variables are the wear and coefficient of friction. The experiment consists of 32 tests (each row in the 25-1 design arrays) and the columns were assigned with parameters as shown in Table 4 along with abbreviations.

4. Results and Discussion

The results of the wear performance of the composites as per the experimental plan are tabulated in Table 4. In order to ensure the goodness of fit of the quadratic model obtained in this study, the test for significance of the regression model, the test for significance on individual model coefficients and the test for lack-of fit need to be performed13,14). The analysis of ANOVA is usually applied to summarize the above tests performed.




Table 3 Design scheme of experimental parameters and their levels

Levels Factors Unit Low (-1) High (+1)

Applied load N 60 120

Sliding distance m 250 750

Reciprocating velocity m/s 0.2 0.4

Counter surface temperature °C 100 200

Silicon content in composite wt.% 6 18

Fig. 2 Photographic view of the reciprocating friction wear test rig



Table 4 Design of experimental matrix and experimental results

Design parameters Experimental results

Exp. No. Applied

load (N) Sliding

distance (m) Reciprocating

velocity (m/s)

Counter surface

temperature (°C)

Silicon content in

composites (wt. %)

Wear (mg)

Coefficient of friction

1 60 250 0.2 100 18 8.9 0.3484 2 120 250 0.2 100 6 7 0.3046 3 60 750 0.2 100 6 14.3 0.3445 4 120 750 0.2 100 18 21.5 0.2433 5 60 250 0.4 100 6 3.8 0.3270 6 120 250 0.4 100 18 5.3 0.2316 7 60 750 0.4 100 18 8.7 0.3328 8 120 750 0.4 100 6 18.1 0.2871 9 60 250 0.2 200 6 9.3 0.4282

10 120 250 0.2 200 18 5.7 0.2764 11 60 750 0.2 200 18 11.9 0.3504 12 120 750 0.2 200 6 28.5 0.2647 13 60 250 0.4 200 18 1.9 0.2706 14 120 250 0.4 200 6 8.6 0.2696 15 60 750 0.4 200 6 10.4 0.3348 16 120 750 0.4 200 18 13.2 0.2657 17 60 500 0.3 150 12 7.8 0.4068 18 120 500 0.3 150 12 12.1 0.2569 19 90 250 0.3 150 12 3.8 0.2180 20 90 750 0.3 150 12 11.6 0.2972 21 90 500 0.2 150 12 15 0.2517 22 90 500 0.4 150 12 9.4 0.2530 23 90 500 0.3 100 12 8.5 0.2439 24 90 500 0.3 200 12 10.8 0.2452 25 90 500 0.3 150 6 8.8 0.2582 26 90 500 0.3 150 18 7 0.2452 27 90 500 0.3 150 12 9.8 0.2310 28 90 500 0.3 150 12 9.1 0.2258 29 90 500 0.3 150 12 11.5 0.2738 30 90 500 0.3 150 12 8.8 0.2517 31 90 500 0.3 150 12 7.2 0.2673 32 90 500 0.3 150 12 7 0.2465

4.1. ANOVA analysis The results of quadratic model for wear of

composites in the form of ANOVA are presented in Table 5. The value of �Prob.>F� in Table 5 for this model is less than 0.05 (i.e. α=0.05, or 95% confidence) indicates that the model is considered to be statistically significant, which is desirable as it demonstrates that the terms in the model have a significant effect on the response. In the same manner, the main effect of factor L (applied load), factor D (sliding distance), factor V (reciprocating velocity) and factor S (silicon content in composites), the second order effect of V (reciprocating velocity) and the interaction effect of factor L (applied load) with factor D (sliding distance), factor D (sliding distance) with factor V (reciprocating velocity) and factor T (counter surface temperature) with factor S (silicon content in composites) are significant model terms. The other model terms can be regarded as not significant effect due to their �Prob.>F� value being greater than 0.05. These insignificant model terms can be removed and

the test of lack-of-fit also displays to be insignificant.

The reduced quadratic model results in Table 5 reveal that this model is still significant in the status of the value of �Prob.>F� is less than 0.05 and the test of lack-of-fit is also insignificant due to their �Prob.>F� value still being greater than 0.05. The other important coefficient R2 in the resulting ANOVA table is defined as the ratio of the explained variation to the total variation. It is a measure of the degree of fit. When R2 approaches unity, the better the response model fits the actual data. The value of R2 calculated in Table 5 for this reduced model is over 0.94, reasonably close to unity, which is acceptable. It demonstrates that about 94% of the variability in the data is explained by this model. It also confirms that this model provides an excellent explanation of the relationship between the independent factors and the response (wear).

Furthermore, the value of adequate precision in this model, which compares the range of the predicted value at the design point to the average prediction error, is well above 4. The value of the ratio is greater than 4



and then it presents the adequate model discrimination. The same procedure is applied to deal with the other responses, the coefficient of friction of composites, and the resulting ANOVA for the reduced quadratic model, which is shown in Table 6. The significant model terms include the main effect of factor L (applied load), factor V (reciprocating velocity) and factor S (silicon content in composites), the second order effect of factor L (applied load) and the interaction effect of factor D (sliding distance) with factor V (reciprocating velocity). The reduced model results reveal that the model is still significant and the test of lack-of-fit is also insignificant. The R2 value calculated in Table 6 is 0.83, close to 1. The adequate precision value of this reduced model is still well above 4.

Through the backward elimination process, the final quadratic models of response equation in terms of coded factors are presented as follows: Wear, W = 8.84 + 2.39 L+ 4.66D - 2.37V + 0.23T -1.37S + 2.35V2 + 2.08LD - 0.91DV - 1.58TS (1)

Coefficient of friction, f = 0.25 - 0.041L + 0.002561D �0.013 V +0.002356T - 0.014S+0.057L2+0.017DV (2) In terms of actual factors the final quadratic models of response equation are as follows:

Wear, W = 20.24187 - 0.059120L + 0.00454444D - 146.69246V+ 0.067917T + 0.56192S + 235.15873V2

+0.0002775LD- 0.036250DV - 0.00527083TS (3) Coefficient of friction, f = 1.05046 - 0.012849L - 0.000196981D - 0.47871V + 0.0000471111T - 0.00235463S+0.0000637328L2+0.00069075DV (4)

The above model obtained can be used to predict the values of wear and coefficient of friction of composites within the limits of the factors studied. Figures 3 and 4 display the normal probability plot of the residuals for both the wear and coefficient of friction, respectively. Notice that the residuals generally fall on a straight line implying that the errors are normally distributed. Further, it adequately supports the least-square fit.

Fig. 3 Normal probability plot residuals for the wear

Fig. 4 Normal probability plot residuals for the

coefficient of friction

4.2. Effect of experimental parameters on wear and coefficient of friction of composites.

The effect of variation of single parameter on wear and coefficient of friction of the composites are shown in Fig.5 to Fig.9. The fixed factors in these figures are at its middle level (0-level value).

4.2.1. Effect of variation of applied load The effect of applied load on wear and friction

characteristics of the composites is shown in Fig. 5(a) and (b). It is observed from Fig. 5(a) that an increase in applied load increases wear and is attributed to the increased metallic intimacy with increase in load. Increase in applied load from 60-120 N results in major decrease in coefficient of friction and reaches to minimum and then increases as observed from Fig. 5(b). Quadratic variation exists between the applied load and the measured coefficient of friction (Fig. 5(b)). During fabrication of the composite specimens, the machined surface gets smeared by aluminum alloy, with the SiC particles inside. The initial rubbing process was therefore effectively between cast iron and the aluminum alloy. The cast iron, being harder, removed the outer layer of the aluminum alloy by the process of delamination and chipping and exposed the SiC particles to the wear surface, resulting in the observed increase in the wear (Fig. 5(a)). With the increase in load the coefficient of friction shows an initial decrease, reaching a minimum at about 100N and increasing subsequently (Fig. 5(b)). This may be due to the fact that at lower loads, the transfer film is found to be more stable than at higher loads, because transfer film is destroyed at faster rate with increase in load. This corresponds to the increase in coefficient of friction in the load range 100 N to 120 N as observed in Fig. 5(b).


DOI 4.2474/trol.4.115


Table 5 The ANOVA table for wear of composites

Source Sum of squares

Degrees of

freedom

Mean square �-value Prob.>F Remarks

Model 795.96 9 88.44 43.17 <0.0001 Significant L 102.72 1 102.72 50.14 <0.0001 D 391.07 1 391.07 190.87 <0.0001 V 101.29 1 101.29 49.44 <0.0001 T 0.98 1 0.98 0.48 0.4964 S 33.89 1 33.89 16.54 0.0005 V2 43.55 1 43.55 21.26 0.0001 LD 69.31 1 69.31 33.83 <0.0001 DV 13.14 1 13.14 6.41 0.0190 TS 40.01 1 40.01 19.53 0.0002

Residual 45.07 22 2.05 Lack of fit 30.95 17 1.82 0.64 0.7731 Not significant Pure Error 14.12 5 2.82 Corr. total 841.03 31

Standard deviation = 1.43 Mean = 10.17 Cofficient of variation = 14.08 Predicted residual error of sum of squares (PRESS) = 108.62 R2 = 0.9464 R2 adjusted = 0.9245 Predicted R2 = 0.8708 Adequate precision = 30.933

Table 6 The ANOVA table for the coefficient of friction

Source Sum of squares

Degrees of

freedom

Mean square

�-value Prob.>F Remarks

Model 0.068 7 0.009773 16.73 <0.0001 Significant L 0.031 1 0.031 52.58 <0.0001 D 0.0001181 1 0.000..81 0.20 0.6571 V 0.0032 1 0.0032 5.48 0.0279 T 0.0000998 1 0.0000998 0.17 0.6829 S 0.003593 1 0.003593 6.15 0.0206 L2 0.026 1 0.026 44.35 <0.0001

DV 0.004771 1 0.004771 8.17 0.0087 Residual 0.014 24 0.0005842

Lack of fit 0.012 19 0.0006419 1.76 0.2770 Not significant Pure Error 0.001825 5 0.000365 Corr. total 0.082 31

Standard deviation = 0.024 Mean = 0.28 Cofficient of variation = 8.54 Predicted residual error of sum of squares (PRESS) = 0.026 R2 = 0.8299 R2 adjusted = 0.7803 Predicted R2 = 0.6896 Adequate precision = 14.629



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(a)

(b)

Fig. 5 Effect of applied load on (a) wear and (b) coefficient of friction

4.2.2. Effect of variation of sliding distance The effect of sliding distance on wear and friction

characteristics of the composites is shown in Fig. 6(a) and (b). It is generally known that with an increase in sliding distance the wear of composites increases due to more intimate contact time of the specimen with the reciprocating plate [Fig. 6(a)]. Increase in sliding distance from 250-750m results in slight increase in coefficient of friction [Fig. 6(b)]. This may be attributed to more chances of entrapment of wear particles in between the contacting surfaces with increased sliding distance which in turn causes three body abrasive wear and increases the frictional forces.

(a)

(b)

Fig. 6 Effect of sliding distance on (a) wear and (b) coefficient of friction

4.2.3 Effect of reciprocating velocity The effect of reciprocating velocity on wear and friction characteristics of the composites is shown in Fig. 7(a) and (b). It is observed that an increase in reciprocating velocity results in different trend of variation of coefficient of friction and wear depending on the range of the reciprocating velocity (0.2-0.4 m/s) investigated. The results indicate that the wear of composite initially decreases with increasing reciprocating velocity, reaches a minimum and then increases. Quadratic variation exists between the reciprocating velocity and the measured wear of the composites. This is due to the fact that an increase in reciprocating velocity increases the strain rate (rate of indentation) which in turn increases the hardness or flow strength. This increase in the flow strength reduces the true area of contact and thus results in a lower wear of the composites as reciprocating velocity changes from 0.2 m/s to 0.35 m/s. Further increase in




reciprocating velocity from 0.35 to 0.4 m/s causes gradual increase in wear. This may be attributed to another important effect of increasing reciprocating velocity which is the rise in temperature due to frictional heat, which softens the material. This result in a higher wear of composites owing to increased true area of contact. Hence, it is observed that the strain rate effect is more predominant than the temperature effect up to the critical reciprocating velocity of 0.35 m/s above which the temperature effect dominates [Fig. 7(a)]. It is observed that increase in reciprocating velocity decreases coefficient of friction [Fig. 7(b)].

(a)

(b)

Fig. 7 Effect of reciprocating velocity on (a) wear and (b) coefficient of friction

4.2.4. Effect of Counter surface temperature The effect of counter surface temperature on wear

and friction characteristics of the composites is shown in Fig. 8(a) and (b). It is observed that an increase in counter surface temperature from 100 to 200°C investigated in this work results in a marginal increase of both coefficient of friction and wear. Increase in

counter surface temperature causes softening of the contacting surfaces which in turn results in intimate contact between the mating surfaces and hence increases both wear and coefficient of friction of the composites10).

(a)

(b)

Fig. 8 Effect of counter surface temperature on (a) wear and (b) coefficient of friction.

4.2.5. Effect of variation of silicon content in composites

The effect of silicon content in composites on wear and friction characteristics is shown in Fig. 9(a) and (b). It is observed that an increase in silicon content from 6wt. % to 18wt. % lowers both wear and coefficient of friction of the composites investigated in this work. The reason is attributed to the fact that increase in silicon percentage increases the resistance to thermal softening and ability to support the surface oxide film owing to higher hardness18). Also silicon reduces the tendency to form adhesion welds with the counterface19). It is also observed that the wear resistance of A390/15%SiCp composite is the better of



the other two (A319/15%SiCp and A336/15%SiCp) composites.

(a)

(b)

Fig. 9 Effect of silicon content in composites on (a) wear and (b) coefficient of friction.

5. Conclusions

Mathematical models of the wear and coefficient of friction have been carried out to correlate the dominant wear parameters of the reciprocating wear behavior of aluminum alloy composites. The conclusions of the research are as follows:

1. The results of ANOVA show that the quadratic models of the wear and coefficient of friction of composites are fairly well fitted with the experimental values. The influences of all the wear parameters on the wear and friction characteristics of composites have been analyzed by the obtained mathematical models.

2. The effect of five wear and friction test parameters on wear and coefficient of friction of composites were studied independently by using the developed mathematical model and experimental results.

3. Applied load, sliding distance, reciprocating velocity and silicon content in composites were the four main controlling parameters and exerted a very strong effect on the wear of composites; while counter surface temperature had marginal effect in the wear of the investigated material under dry condition.

4. The three main controlling parameters which exert a very strong effect on the friction of composites are the applied load, reciprocating velocity and silicon content in composites while the counter surface temperature and sliding distance had minor effect on the friction of investigated composites.

5. For the friction of the composites nonlinearity effect is more pronounced with applied load (Quadratic variation) compared to the other four factors. Also quadratic variation is obtained for reciprocating velocity with wear of composites. This clearly indicates nonlinear behavior of the composites is predominant under severe wear conditions.

6. Statistical analysis of the wear data of the composite revealed that A390/SiCp composite is having better wear resistance than A336/SiCp and A319/SiCp composites.

As an extension of the present work, multi response optimization of wear and coefficient of friction of composites and sensitivity analysis for friction and wear test parameters in wear of composites should be carried out.

Acknowledgment

The authors would like to acknowledge the financial support received to the first author as scholarship from AICTE, Government of India. The technical assistance from Mr. Jasbir Singh and Mr. Harishankar is also appreciated.

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Documents

Effect of Experimental Parameters on Reciprocating Wear