Dry sliding wear behaviour of SiCp reinforced Zn-Mg-Cu based aluminium matrix composite

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ScienceDirect Materials Today: Proceedings 4 (2017) 2965–2974

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5th International Conference on Materials Processing and Characterization (ICMPC 2016)

Dry sliding wear behaviour of SiCp reinforced Zn-Mg-Cu based aluminium matrix composite Diptikanta Dasa,*, Swati Pattanaika, Bharat Chandra Routaraa, Purna Chandra Mishraa and Chandrika Samalb a

School of Mechanical Engineering, KIIT University, Bhubaneswar-751024, India b Department of Mechanical Engineering, GITA, Bhubaneswar-752054, India

Abstract Silicon carbide particulate (SiCp) reinforced Aluminium Matrix Composite (AMC) was fabricated using stir casting method and then heat treated to T6 condition. Distribution pattern of the reinforcement was observed through optical microscopy. Density, percentage of porosity and hardness were determined. Dry sliding wear tests were conducted using Taguchi L9 Design of Experiments (DOE) to investigate the effect of load and spindle speed on specific wear rate. Morphology of worn surfaces was studied. Wear process parameters were optimized using Taguchi method and their significance was determined through Analysis of Variance (ANOVA). Linear regression equation was developed and its adequacy was verified. ©2017 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of Conference Committee Members of 5th International Conference of Materials Processing and Characterization (ICMPC 2016). Keywords:Aluminium matrix composite, Specific wear rate, Taguchi, ANOVA, Regression analysis

1. Introduction Hard ceramic particulate reinforced AMCs are being proved as potential engineering materials for critical applications which demand light weight materials with highly wear resistant property, such as connecting rods, pistons, brake drums and cylinder liners etc. Presence of hard particles in the AMCs protects them from severe wear conditions and results lesser wear and lower friction coefficient than those of their monolithic alloys [1].T6 condition of heat treatment improved the fretting wear resistance of SiCp reinforced Al 356 matrix composites [2]. While investigating the dry sliding wear behaviour of silicon particle reinforced Al–Cu–Mg alloy matrix composites, Zhiqiang et al. [3] reported decreased wear loss in AMCs than the monolithic alloy. Increase of load and sliding speed increased the wear loss of the alloy and AMCs. During tribological tests of SiCp reinforced Al 2618, Al 6082, Al 7012 and Al 7075 matrix composites in presence of air and distilled water, Mindivan et al. [4] observed two modes of wear progression, i.e. mild and severe. In mild wear the reinforcement particulates remained on the worn surface, whereas those were removed from the worn surface in severe wear conditions. Rao et al. [1], during dry sliding wear test of SiCp reinforced Al–Zn–Mg alloy composites at constant sliding speed, reported

* Corresponding author. Diptikanta Das Tel.: +91 674 6540805; E-mail address:[email protected] 2214-7853©2017 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of Conference Committee Members of 5th International Conference of Materials Processing and Characterization (ICMPC 2016).

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increase of wear rate with applied pressure and the wear resistance shows significant improvement in the composites than the corresponding matrix alloy. However, the wear resistance decreases with increase in SiCp concentration. While investigating dry sliding wear behaviour of LM 25-Gr-SiC hybrid Metal Matrix Composites (MMCs), Suresha and Shridhar [5] reported that the Gr reinforcement was beneficial in reducing wear due to its solid lubricant property, but simultaneously it reduced the mechanical strength. Addition of SiCp improved both strength and wear resistance of the MMCs. However, addition of excessive amount of SiCp caused machining difficulty and the MMCs became brittle. Rao and Das [6] reported that the wear coefficient of SiCp reinforced Al–Zn–Mg–Cu alloy matrix composites was lower than that of its monolithic alloy. It reduced to a minimum value on increasing the applied pressure and on further increase of applied pressure it increased.During dry sliding wear tests on Al–SiC–Gr hybrid MMCs, Suresha and Shridhar [7] reported that the load, sliding speed and wt.% of reinforcement affected the coefficient of friction, where as the sliding distance had no effect on it. While studying tribological propertiesof T6 conditioned SiC-Al2O3 reinforced Al 6061 hybrid MMCs, Umanath et al. [8] reported that the resistance to wear was better for the MMCs with higher reinforcement content. High counterface hardness, low rotational speed and low applied load were the favourable conditions for reduced wear. Ganesh et al. [9], during dry sliding wear tests of SiCp reinforced Al 2219 AMCs fabricated by powder metallurgy process, observed better wear performance for the AMCs with smaller size, high wt.% of reinforcement and higher sintering temperature. During investigation of wear properties of Al 6082-Si3N4 MMC in dry sliding condition,Sharma et al. [10] observed reduction of wear rate with increase of sliding speed and wt.% of reinforcement. However, the wear rate increased with increase of load and sliding distance. Sarada et al. [11], while investigating wear characteristics of activated carbon and mica reinforced LM 25 hybrid MMC and mica reinforced LM 25 MMC reported that the wear resistance increased by addition of dual reinforcements instead of single reinforcement. Sharma et al. [12], during dry sliding wear investigation of Al 6082-Gr MMCs reported that wear resistance of the cast Al 6062 alloy was more than that of the developed MMCs. Wear rate of the MMCs increased with increasing load and sliding distance, but reduced with increase of sliding speed and wt.% of reinforcement. While investigating the wear behaviour of AA 6063-milled B4C-in situ TiB2 hybrid surface composite and AA6063in situ TiB2 mono surface composite produced by Friction Stir Processing (FSP), Narimani et al. [13] reported that the hardness and wear resistance of the hybrid surface composite were more than the FSPed AA6063. Highest hardness and best wear resistance were observed for AA6063-100% in situ TiB2 mono surface composite. The major challenge during fabrication of AMCs is to maintain uniformity in dispersion ofreinforcements in the matrix phase which greatly influences the material properties. Though there are various methods available for fabrication of the AMCs, liquid metallurgy stir casting process is widely used. It may be because of this method can produce the composites on mass scale economically [14], near net shaped AMC casts can be produced and verities of reinforcements can be used due to fluidity of metals [15]. Accordingly, liquid metallurgy stir casting process is used for fabrication of AMC in the present research. High strength-to-weight ratio of Zn-Mg based Al alloys makes them potential for aerospace structural applications. However, due to poor weldability these alloys are joined by bolting or riveting that leads to vibration and dry sliding wearin these regions. It is therefore essential to investigate their dry sliding wear behaviour [1]. Moreover, addition of hard SiCp in these alloys and heat treatment improves their strength and hardness [16-19]. Since the SiCp reinforced AMCs are replacing their monolithic alloys, both in static and dynamic engineering applications, study of their tribological behaviour is essential for their safe application in the critical areas. Accordingly, dry sliding wear behaviour of heat treated SiCp reinforced Zn-Mg-Cu based Al alloy (equivalent to Al 7075) matrix composite is investigated in terms of specific wear rate in the present work. Morphology of worn surfaces is studied and wear process parameters are optimized using Taguchi method 2. Materials and Methods Zn-Mg-Cu based Al alloy (equivalent to Al 7075), supplied by Bharat Aerospace Metals, Mumbai was used as matrix and SiC particles of 100 mesh, supplied by Geologists Syndicate Pvt. Ltd., Kolkata were used as reinforcement for fabrication of the AMC. Chemical composition test result of the Al alloy is presented in Table 1. Table 1 Chemical composition test result of the Al alloy Name of Element Si Fe Weight %

0.1

0.21

Cu

Mn

Mg

Zn

Ti

Cr

Al

1.5

0.12

2.0

4.6

0.04

0.24

Rest

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2.1 Fabrication and heat treatment Irregular shaped SiCp (15 wt.%) reinforced AMC was fabricated using liquid metallurgy stir casting method. A Jay Crucible make 440 V, 50 Hz, 7.5 kW, 3-phase electrical resistance type vertical chamber furnace (Fig. 1-a) of maximum working temperature 11000C and temperature control accuracy ±100C was used for melting the Al alloy and preparation of the composite slurry. To record the temperature a K-type thermocouple was inserted in the crucible. A speed regulated motorized stirring system (maximum speed 800 RPM) with stirring rod and stirring blades, both made of mild steel, was mounted to the furnace to provide adequate mixing of preheated SiC particles in the molten aluminium. A Carbolite make STF 10/75 2x 400 V, 50 Hz, 6 kW, 3-phase high temperature Singlezone tube furnace (Fig. 1-b) with maximum working temperature 16000C and temperature control accuracy ±10C was used for preheating the SiC particles, before adding into the molten alloy.

Fig. 1 Photographic images of (a) vertical chamber furnace (Jay Crucible); and (b) Single-zone tube furnace (Carbolite STF 10/75 2x)

Distilled water cleaned and acetone ringed sliced Al alloy ingots were charged into the steel crucible of the vertical chamber furnace and heated up to 900 ± 100C. During melting, all cover flux was added to prevent oxidation. SiC particles, preheated to 900 ± 10C were then added at very slow rate (approximately 20 g/min) using a spatula, into the vortex of molten alloy, created by motorized stirring. After complete addition of SiC, stirring was continued for 10 minutes more at 400 rpm. About 10 grams of solid hexachloroethane (degassing agent) was then dipped into the molten metal with the help of a plunger to prevent hydrogen contamination. The molten composite slurry was then poured into a split type steel mold and air cooled to room temperature. The fabricated AMC was heat treated to T6 condition which involved two steps, i.e. (a) solution annealing at 483 ± 10C for 2 hours, followed by water quenching; and (b) precipitation hardening or aging at 122 ± 10C for 24 hours, followed by air cooling to room temperature [17, 20-23]. The Carbolite make STF 10/75 2x Single-zone Tube Furnace (Fig. 1-b) was used for heat treatment of the AMC. 2.2 Optical microscopy Metallographic specimen of the AMC was prepared as per ASTM E3-95 standard for optical microscopy. Pattern of distribution of reinforcements in the matrix alloy was observed through Leica-DMI3000 M inverted optical microscope and the micrograph (Fig. 2) reveals uniform distribution of SiC particulates with some local agglomeration. Dendritic microstructure in the matrix alloy is also observed in the micrograph.

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Fig. 2 Optical micrograph of heat treated AMC

2.3 Density, percentage of porosity and hardness Density was measured using an Archimedes principle apparatus fitted to a Mettler Toledo make precision balance, taking three times average and it was observed to be 2.8 g/cm3, 3.2 g/cm3 and 2.4 g/cm3 for the Al alloy, SiC particles and the fabricated AMC sample respectively. Theoretical density of the AMC was then calculated using rule of mixtures [24], from Eq. (1) and its value was 2.85 g/cm3. Percentage of porosity in the AMC sample was determined using Eq. (2) and it was found to be 15.7%. Lower density value of the AMC than that of the matrix alloy may be due to the presence of higher porosity level in the composite.

100 m r = + rt rm rr

(1)

æ r P = çç1 - e rt è

(2)

ö ÷÷.100 ø

rt

and r e are theoretical and experimental densities of the composites respectively, r m and r r are densities of matrix alloy and reinforcements respectively, m and r are weight percentages of matrix alloy and reinforcements respectively and P is percentage of porosity in the composites. Hardness of the heat treated AMC sample was measured using an ASI make Rockwell hardness tester of capacity 187.5 Kgf, taking three times average and it was found to be 82 HRB. 2.4 Wear test Ducom-TR 25 multi-tribotester consisting EN 31 steel disc of hardness 58 HRC and diameter (D) 60 mm (Fig. 3) was used for wear test of the finely polished heat treated AMC samples. Dimension of the test specimens was 6.5 mm x 6.5 mm x 9.0 mm, as shown in Fig. 4. All the tests were conducted in dry sliding condition for a constant duration (t) of 30 minutes. Weight of the test samples was measured before and after the tests, using a highly sensitive Mettler Toledo make weighing balance with least count 0.001 g. Wear tests were conducted following Taguchi L9 DOE to investigate the influence of load and spindle speed of the tribotester on specific wear rate of the AMC samples. Accordingly, three levels were assigned to each of the two parameters, as shown in Table 2. Specific wear rate was calculated using Eq. (3) [22]. where

Fig. 3Multi-tribotester (Ducom-TR 25)

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Fig. 4Image of wear test samples Table 2 Process parameters and their levels Factor

Notation

Unit

Level 1

Level 2

Level 3

Normal load

W

N

30

40

50

Spindle speed

N

rpm

200

300

400

1000 * Dw r* L * W p* D * N * t L= 1000 where, s = specific wear rate (mm3/Nm), Dw = weight loss due to friction (g),

(3)

s=

(4)

r = density of AMC (g/cm3) and

L = sliding distance (m), which can be calculated using Eq. (4).

3. Results and Discussion Experimental results of dry sliding wear behaviour of the heat treated AMC in terms of specific wear rate is presented in Table 3. Influence of normal load and sliding distance (which is a function of spindle speed of the tribotester) on specific wear rate of the AMC during dry sliding wear tests is discussed in section 3.1. Table 3Experimental results Run no.

W

N

L

Δw

s

1 2 3 4 5 6 7 8 9

30 30 30 40 40 40 50 50 50

200 300 400 200 300 400 200 300 400

1130.976 1696.464 2261.952 1130.976 1696.464 2261.952 1130.976 1696.464 2261.952

0.013 0.019 0.023 0.026 0.038 0.050 0.068 0.071 0.089

0.000158 0.000154 0.000140 0.000245 0.000231 0.000228 0.000504 0.000348 0.000329

3.1 Influence of normal load and sliding distance on specific wear rate Influence of normal load on specific wear rate of the test samples at different spindle speeds is presented in Fig. 5. It is observed that specific wear rate increases with load, but reduces with increasing the spindle speed. This result is in agreement with the observations of Kumar and Dhiman [22]. With the increase of load, frictional force between the contact surfaces increases that causes more wear and hence more material loss from the surface of softer material. As in these wear experiments surface of hard EN 31 steel disc was sliding with comparatively softer surface of the AMC in dry condition, more material was removed from the later one, hence by increasing the specific wear rate with increase of load. Further, influence of sliding distance on specific wear rate at different loads is presented in Fig. 6that reveals the specific wear rate reduces with increasing sliding distance. Work hardening of the AMC contact surface may be the cause of reduction of specific wear rate with the increase of sliding distance [25].

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Specific wear rate (mm3/Nm)

0.0006 0.0005 0.0004

N=200 rpm

0.0003

N=300 rpm

0.0002

N=400 rpm

0.0001 0 0

20

Load (N)

40

60

Fig. 5 Influence of normal load on specific wear rate

Specific wear rate (mm3/Nm)

0.0006 0.0005 0.0004

W=30N

0.0003

W=40N

0.0002

W=50N

0.0001 0 0

500

1000 1500 Sliding distance (m)

2000

2500

Fig. 6 Influence of sliding distance on specific wear rate

3.2 Morphology of worn surfaces Morphology of worn surfaces of the AMC test specimens at different wear parameters was studied through Leica-DMI3000 M inverted optical microscope. Optical micrographs of some worn surfaces are shown in Fig. 7 (ac), as illustration. At low load condition (Fig. 7-a), grooves are observed on the damaged surface, which may be due to plastic deformation of the AMC sample during sliding in dry condition. But as the load increases (Fig. 7-b), the wear becomes severe and crack formation starts along the groves. Due to severity of wear, prominent cracks are observed at the highest level of load (Fig. 7-c), i.e. at 50 N. The wear was abrasive in nature and ploughing was the principal wear mechanism at low load conditions. However, at higher loads the abrasive wear was the combined effect of ploughing and cracking (brittle fracture).

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Fig. 7 Optical micrographs of worn surfaces of AMC specimens at 200 rpm of spindle speed and normal load of (a) 30 N; (b) 40 N; and (c) 50 N

3.3 Optimization of wear process parameters Taguchi method is an effective tool for optimization problems, which is widely applied to engineering, biotechnology, marketing and advertising [26]. The method is based on orthogonal array of experiments which gives much reduced variance with optimum setting of control parameters to achieve 'best' results. Taguchi's Signal-toNoise (SN) ratios serve as objective functions for optimization, help in data analysis and prediction of optimum results [27]. In the present experiments this method is used to optimize wear process parameters for specific wear rate. The influence of control parameters (i.e. load and spindle speed) on dry sliding wear behaviour of the AMC for a constant sliding time of 30 minutes has been evaluated using SN ratio response analysis. Process parameter settings with the highest SN ratio implies that signal is much higher than the random effects of noise factors and always yield the optimum quality with minimum variance. "Smaller is better" type of quality characteristic is selected for specific wear rate. SN ratios (dB) for the response are calculated using Eq. (5), which are presented in Table 4. é1 n ù ( S / N )SB = -10 log10 ê å yi2 ú (5) ë n i =1 û where

n

is the number of experiments, and

y i is the experimental value of the i th quality characteristic [28].

Table 5 presents response table of SN ratios and Fig. 8 represents main effects plot of SN ratios for specific wear rate of the AMC under study. From Table 4, the highest value of SN ratio is obtained for run no. 3, i.e. for load 30 N and spindle speed 400 rpm. Also from Table 5 and Fig. 8, the highest values of mean SN ratios are obtained for the level 1 of load and level 3 of spindle speed, which reveal that W1-N3 is the optimal combination of control parameters for specific wear rate of the AMC in dry sliding condition. Table 4Experimental results and SN ratios for specific wear rate Run no. 1 2 3 4 5 6 7 8 9

W 30 30 30 40 40 40 50 50 50

N 200 300 400 200 300 400 200 300 400

s 0.000158 0.000154 0.000140 0.000245 0.000231 0.000228 0.000504 0.000348 0.000329

SN ratio 76.02686 76.24959 77.07744 72.21668 72.72776 72.8413 65.95139 69.16842 69.65608

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Table 5 Response table for SN ratios Level 1 2 3 Delta Rank

W 76.45 72.6 68.26 8.19 1

N 71.4 72.72 73.19 1.79 2

Fig. 8 Main effects plot of SN ratios for specific wear rate

3.4 Confirmation tests Some confirmation wear tests were conducted to predict and verify the improvement of the performance characteristic using the optimal combination of process parameters. For the optimal levels of the process parameters, the predicted SN ratio ( gˆ ) was calculated using Eq. (6) to compare with that of its experimental value. o

ˆg = g m + å (g i - g m ) i =1

Where

gm

is the total mean SN ratio, g i is the mean of the SN ratio at the optimal level and

(6)

o

is the number of

process parameters that significantly affects the performance characteristics. Results of confirmation tests, using the optimal and initial process parameters are presented in Table 6. Good agreement exists between predicted and optimal SN ratios. Improvement of SN ratio for the optimal process parameters than the initial process parameters is 1.2303 dB. Table 6 Confirmation test results Optimal cutting parameters Initial cutting parameters Prediction Experiment Level W1-N1 W1-N3 W1-N3 S 0.000159 0.000138 SN ratio 75.9721 77.2078 77.2024 Improvement of SN ratio = 1.2303 dB

3.5 Analysis of variance To determine significance of individual wear process parameters on the specific wear rate of the AMC under dry sliding condition, ANOVA is conducted at 95% confidence level using MINITAB mathematical software.For this case a response is statistically significant when the probability of significance (P-value) of its input source is less than 0.05 [28-30]. Results of the study (Table 7) indicate that load is highly significant process parameter for the specific wear rate as its P-value is sufficiently lower than 0.05, however the effect of spindle speed is insignificant. Moreover, the Ftable value for DF1: DF6 at 95% confidence level is 5.99 [28], which is sufficiently lower than Fcalculated value for W and more than Fcalculated value for N. It is another justification[31] for the parameter W to be significant and N to be insignificant.

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Table 7 ANOVA for specific wear rate Source W N Error Total

Degree of freedom 1 1 6 8

Sum of squares 0.0000001 0.0000000 0.0000000 0.0000001

Mean square 0.0000001 0.0000000 0.0000000

F-value 37.3 3.1

P-value 0.001 0.129

3.6 Regression analysis Relation between a response variable and two or more predictor variables can be modeled using linear regression analysis by fitting a linear equation to the observed data [32]. In order to establish the correlation between the wear parameters and specific wear rate, a linear regression model (Eq. 7) is generated with uncoded units using least square method of regression analysis.

s = 0.000121333 + ( 1.215 E - 05 ) * W - ( 3.5 E - 07 ) * N R 2 = 87.07%, R 2 ( adj ) = 82.76%

(7)

Adequacy of the model is verified through high determination coefficient (R2 = 87.07%). Further, the predicted value of R2 is in reasonable agreement with the adjusted R2 of the model, indicating fitness to the sample data. The normal probability plot of residuals for specific wear rate (Fig. 9) depicts the residuals lie reasonably close to the normal probability line, implying that residuals are distributed normally and the terms mentioned in the regression model are significant and adequate [33]. Fig. 10 shows plot for residuals versus fitted values of specific wear rate, in which the points representing the residuals are randomly scattered. So, the predicted regression model for the response is adequate.

Fig. 9Normal probability plot for residuals

Fig. 10 Residuals versus fitted values

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4. Conclusions · · ·

· ·

Density of SiCp reinforced AMC was lower than that of the Al matrix alloy, which may be due to high porosity content in the AMC. Specific wear rate increased with load and reduced with spindle speed (or sliding distance). Grooves were observed on the worn surface due to plastic deformation of the AMC sample at low load condition. The wear became severe and crack formation started along the groves with increase of load. Due to severity of wear, prominent cracks were observed at the highest level of load condition. At low load conditions the wear was abrasive in nature and ploughing was the principal wear mechanism. However, at higher loads the abrasive wear was the combined effect of ploughing and cracking (brittle fracture). Application of Taguchi method revealed that normal load of 30 N and spindle speed of 400 rpm were the optimized combination of wear process parameters for specific wear rate. ANOVA results indicated that load was highly significant for the specific wear rate, however the effect of spindle speed was insignificant. Linear regression model was generated for specific wear rate using least square method of regression analysis. The adequacy and fitness of the model were confirmed from the high value of determination coefficient. Normal probability plot depicts that the residuals lie reasonably close to the normal probability line, implying that residuals are distributed normally and the terms mentioned in the regression model are significant and adequate. The adequacy of the model was also verified through the plot for residuals versus fitted values.

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