Issue
Metall. Res. Technol.
Volume 118, Number 6, 2021
Article Number 614
Number of page(s) 11
DOI https://doi.org/10.1051/metal/2021086
Published online 06 December 2021

© EDP Sciences, 2021

1 Introduction

Hybrid metal matrix Al6061 composites are technology materials that are found use in aerospace, automobile, marine, and other applications owing to their improved physical and mechanical properties like lower density, higher specific strength, when compared to the base aluminum material. The extended business needs for lightweight materials have high specific strength seen in aerospace and automotive industries have triggered a change in favor of Al alloy based composites [1]. High strength, hardness and wear resistance, aluminum-based MMCs found worldwide used stir casting method among the all other processing techniques. They involve prolonged liquid-reinforcement contact and increasing attention in recent years as much sought after engineering materials. Aluminum-based MMCs are the preferred engineering materials as they possess high quality, hardness and wear resistance properties. The wear and hardness properties can be upgraded by increasing the volume fraction of SiC. The examination disclosed that the tribology of AMMCs as factors of the nature of reinforcing phase, sliding velocity and distance, applied load, and reinforcement volume fraction [24]. Material is held back from wear through the use of ceramic particles for attaining high wear resistance for particle reinforced AMMC’s, which could be increased the particle content and improving wear resistance [5]. Fenghong et al. [6] studied the SiC particle reinforcement with aluminum metal matrix and proved that this composite was more important than any other material used in automobiles. The focus of earlier researchers [7] was on the purpose of the application of the aluminum-graphite composite. Such reports from research have indicated the trend of the aluminum-graphite composite containing a small quantity of graphite showing better wear properties than base alloys. A solid lubricant, namely, graphite present in aluminum-graphite composite, tends to reduce its strength but improves the lubrication effect [8,9]. Among the ceramic materials B4C is considered exceptional as it has high strength, low density (2.52 g/cm3), high hardness and excellent chemical stability [10,11]. Manufactured Al matrix compound was used with boron carbide and silicon carbide particles through liquid metallurgy route and under the indistinguishable conditions for the purpose of assessing the effects of the tensile properties of the composites [12]. From these composite with 2% in weight Al2O3 with a hardness value, tensile strength 123 Hv and of 505 MPa over that of unreinforced metal matrix alloy was found [13]. Chelladurai et al. [14] showed improvement in wear resistance in the range 22–30% differentiated and the system compound with the use of cast composites of aluminum alloy (LM13 and LM6) consisting of 2.8% and 2% powder particles that were considered in liquid metallurgy. Graphite is a commonly used lubricant material. It is noteworthy solid lubricants but fails acts in the vacuum. Hence talc was found to be a new lubricant which is a eco-friendly, perfect solid lubricant with a smaller moderate cost when compared to graphite.

Usually Taguchi technique will decrease the varieties in a procedure through of robust design of experiments. The investigation of results dealing with the determination of the best output process design uses the signal to noise ratio. The Taguchi technique was found effective use by analysts as a part of their research, in wear behavior of aluminum metal matrix composites [15]. Taguchi utilized a standard orthogonal array to define the design of experiment and to help the impact of several factors on the desired value [16]. The investigations described the wear rate and friction in metal matrix graphite composites were reduced in matrix alloys, because of the inclusion of graphite particles. At the point when the graphite substance of metal matrix composites surpasses around volume percentage [17]. The study was developed based on MMC aluminum alloy AA7075 by design of experiment using Taguchi method. The objective is to predict the optimized parameter values that give the best tensile strength and hardness by Taguchi method. The final Confirmation test with the optimum levels of preparing parameters was done so as to expose the adequacy of the Taguchi [18]. An Experiments were conducted to investigate the impact of the expansion of micro- and nano-boron carbide particles for the combination of Al/B4C nanocomposite (and small-scale/nearing nano) utilizing gravitational friction stir processing method which analyzed the impact of typical load sliding wear and friction of the composite. The outcome revealed less coefficient of friction and more wear rate for Al/B4C nanocomposite related to Al/B4C micro composite [19]. Fly ash particle reinforced aluminum matrix composite (AMC) had been prepared using stir cast furnace using compo casting technique. The influence of fly ash particulate content (0, 4, 8 and 12 wt.%) and temperature (40, 80, 120, 160, 200 and 240 °C) on wear rate and worn surface of the AMCs were observed. In the present work, hard fly ash particle reinforcement is successfully made to enhance the wear protection of the compo cast AMCs at all temperatures. In this composite adhesion, metal flow and oxidation were found affecting wear process [20]. Similarly, Jagadeesan et al. [21] have done an optimization study on MQL nanofluid machining behavior with biochar content. According to the author the Taguchi technique was the most powerful tool in order to find the most influential process parameter. Moreover, optimizing the abrasive water jet process parameters in the machining study was the research of Mohamed Sahibulla et al. [22]. Author concluded that the Taguchi tool was the instrumental for finding out the most optimum process parameter in any process, which has more than 2 input process variables.

Based on the previous studies there are more research studies are done in the aluminum MMC with graphene or graphite as solid lubricant. However using talc as solid lubricant based aluminum metal matrix composites and studying the wear behavior based research are fairly done. Based on this research gap the current research was conducted. In this investigation, Al 6061was reinforced with weight percentage (3%) B4C particulate and weight percentages (2%) talc particulate kept constant, however with development of the varying range of (5%, 10%, 15%) of SiC particulate composites. A test was conducted to examine the result of factors that included load, sliding speed, sliding distance and percentage of reinforcement on the dry sliding wear behavior of the particulate reinforced Al6061/SiC/B4C/talc composites. The experiment conducted using Taguchi’s technique was based on the L27 orthogonal array. Applying distinctive parameters like applied load, sliding speed, sliding distance and percentage of reinforcement by Grey relational analysis method helped to get the optimized content. The use of ANOVA helped for determination of the percentage of several process parameters and also their relationship on dry sliding wear of the hybrid composite materials.

2 Experimental procedure

2.1 Material selection

Al6061/SiC/B4C/talc composite fabricated by liquid metallurgy route (stir casting which is a low-cost method) [23]. The chemical composition of Al6061was indicated in Table 1. The matrix material selected was available at a fair price pure Al6061 is while reinforcement was SiC of average size (30–40 microns) and B4C (20–30 microns) and talc (0–10 microns). Hybrid Al6061/SiC/B4C/talc composite was prepared by using constant weight of B4C 3%, talc of 2 wt.% and different range of SiC weight percentage as 5, 10 and 15.

Table 1

Chemical composition of matrix material Al6061.

2.2 Preparation of composites

The composites made with a steady weight percentage of both (3 wt.%) B4C particulate and (2 wt.%) talc particulate, then fluctuating range (5%, 10%, and 15%) weight of SiC particulate composites. The fabrication of Al6061/SiC/B4C/talc composites done using the stir casting method helped establishment of the reinforcement as a uniform basis. Al 6061 alloy, which is an ingot, was cut into little pieces for a graphite crucible in the electric furnace (Fig. 1). Al6061 was liquefied in an electric furnace. Magnesium (0.5 wt.%) was added to the slurry for enhancement of wettability of reinforcements. Instantaneously the (B4C/SiC/talc) powder was preheated to a temperature of approximately 300 °C and a preheated mixture of (B4C/SiC/talc) was added to the Al6061 liquid metal and mixed consistently. Then 3 g of degassed tablet (C2Cl6-Solid hexa-chloro ethane) was added to the composite slurry. The slag was let off from the composite slurry and stirring was done at 500 rpm/min for 10 min. The Al6061/SiC/B4C/talc composite slurry filled into steel mold die was preheated (300°C) and cooled in air and got cast as composite samples (Fig. 2). This specimen prepared from the cast of Al6061/SiC/B4C/talc composites was used for a further test to be conducted [2426].

thumbnail Fig. 1

Electrical stir furnace.

thumbnail Fig. 2

Casted samples.

2.3 Plan of experiments

The design of experiments needs meticulous planning, careful layout of the experiment and expert investigation of outcomes. The experiment was conducted based on the basis of wear testing conditions as the process parameters that included applied load (A), Sliding speed (B), Sliding distance (C) and percentage of reinforcement. The experiment was conducted on the hybrid MMC composite for the purpose of analyzing the influence of specific wear rate and co-efficient of friction. The experimental plan included 3 levels and 4 factors these are detailed in Table 2. Taguchi experimental plan representing L27 orthogonal array contained 27 rows and 13 columns selected as the basis of the degree of the result of the trial experiment was converted into an S/N (signal-to-noise) ratio. The-higher-the value the better is the attribute chosen for a specific wear rate and friction coefficient from dry sliding wear test. The pin-on-disc device did the assessment of the wear characteristics of three different sliding distances of 1000 m, 1200 m, and 1500 m. The results of the specific wear rate and the friction coefficient are represented in Table 3.

Table 2

Process parameters and their levels.

Table 3

Normalized values and overall grey relational coefficient of each performance characteristic with S/N ratios.

2.4 Grey relational analysis (GRA)

The Taguchi technique is meant to optimize a single response characteristic though the GRA optimization methodology can be utilized for multi-response optimization [27,28] as appeared in the next step (i) Regularizing the results of the experiment. (ii) Execution of Grey relational that creates and calculates the GRC. (iii) Manipulative the Grey relational grade through the procedure of normal the Grey relational coefficient. (iv) Carrying out the numerical (ANOVA) for the input parameters with the Grey relational grade and which parameter has a significant influence on the method. (v) Decisive on the optimal levels of the process parameters. By conducting the factual examination of difference (ANOVA) for the info parameters with the Grey social review and which parameter affects the strategy. A grey relational analysis may create enormous result when the aim of the factors and directions are different. Hence there is need for preprocessing of identified data with a gathering of arrangements referred to as “Grey relational generation” from the-lower-the-better and higher-the-better quality characteristics data preprocessing calculated by equations mention as below (1) and (2) (1) (2)

where expressed the lower experimental value of (Xij), represents the upper experimental value of is the normalized value after grey generation of the higher is better; is the normalized value after grey generation of the lower is better.

The maximum of the normal values calculated by using the formula(3)where R is the absolute difference between each normalized and the reference value.

The response variable, trials, and replications were assessed using the example(4)

The grey relational coefficients calculated for the every performance characteristic by(5)for i = 1, 2, 3, …, p, j = 1, 2, 3, …, q and k = 1, 2, 3, …, r, ζ is the recognizing coefficient is 0 to 1 (0.5) is typically utilized.

The grey relational grades were computed using the formula(6)p × r for j = 1, 2, 3,…, 9.

Taguchi formula has been gotten on overall grey relation grade to obtain the condition of the optimal parameters.(7)where ‘n’ is represented as the number of measurements then yIth measured the ith particular value of the ith quality. The higher-is-better measure of Taguchi was taken in with the thought of maximizing the overall grey relation grade. Table 3 details the overall grey relational grade and represents the Taguchi implemented for evaluating the optimal parameters on the multi-performance characteristic and seen from the predicted S/N ratio. Tables 3 and 4 and Figure 3a and 3b show the optimum value of the overall relational grade regarding the minimum Specific wear, Minimum coefficient of friction and the load obtained. The investigational values were changed over into S/N ratios with the assistance of software MINITAB 16 used.

Table 4

Response table for GRG for each optimum level for wear parameters.

3 Results and discussions

3.1 Microstructure

Microstructure plays a significant role in the general execution of a composite. Reinforcement, particle size, shape, and appropriation in the alloy were the physical properties seen in microstructure. Scanning Electron Microscope (SEM) for determining the distribution pattern of SiC, B4C and talc in the matrix of the prepared samples. The micrographs provided the microstructure of a SiC, B4C and talc particles in reinforced Al6061. The distribution behavior of reinforcements with respect to different magnification of SEM are indicated in Figures 4a-c, 5a-c and 6a-c). Figure 4 deals the microstructure of composite made using Al6061+SiC (5%)+B4C(3%)+talc(2%), Figure 5 indicated the microstructure of composite contains Al6061 + SiC(10%) + B4C(3%) + talc(2%) and Figure 6 shows the microstructure of composite contains Al6061 + SiC(15%) + B4C(3%) + talc(2%). The uniform distribution of SiC, B4C and talc particles without any void and discontinuities were seen from these micrographs. They also found a significant holding between the matrix material and SiC, B4C and talc particles. But, no fracture is seen between the molecules and the matrix. Finally the EDX investigation (Fig. 7) confirmed that the existence of SiC, B4C and talc particles in the composites. Similarly, the peaks confirmed the presence of Si, C, B, O, Fe and Al in the composites. SEM structure is, therefore the confirmation of successful incorporation of hybrid Al6061/SiC/B4C/talc composites. In the event of indication of homogeneity with cast composites, saw the getting of good mechanical properties of uniform size.

thumbnail Fig. 3

(a) Response graph. (b) Response graph.

thumbnail Fig. 4

SEM image of Al6061 composite with 5wt.% of SiC.

thumbnail Fig. 5

SEM image of Al6061 composite with 10wt.% of SiC.

thumbnail Fig. 6

SEM image of Al6061 composite with 15wt.% of SiC.

3.2 Wear result

The pin on disc machine (DUCOM) make was utilized for the computation of the wear and coefficient of friction response to sliding surface and wear specimens (pin) of the size 8mm diameter and 50 mm height machined from cast samples and cleaned on the basis of metallography. The tests were carried out under dry conditions, according to ASTM standard G99. The wear of composite materials appeared to be simple. The removal of material is a very complicated process due to a substantial influence from wear. The test was accomplished through apply loads of 9.81 N, 19.62 N and 29.43 N and was kept running for the other sliding distance of 1000 m, 1500 m and 2000 m and varying a sliding speed of 1.0 m/s.1.5 m/s and 2.0 m/s. The disc material was made of EN31 steel. The load applied during the pressing of pin over the disc acted as a counterweight. The pin was at first weighed precisely utilizing a digital electronic balance. Weight loss of the specimen was seen after the end of each test and the difference was weighed to measure the weight reduction arising from wear. The result obtained in this test and computed utilizing standard equations indicated.

3.3 Analysis of variance

When the ANOVA method is utilized for examining design parameters that fundamentally involve equality, that experimental design is termed as orthogonal. In such case, there is the likelihood of a distinct impact of each process parameter as the % reinforcement on wear about load, sliding speed and sliding distance at different levels. The grey relational grade for each level of the combining parameters, which resulted in the multi-response performance (ANOVA) of the response quality characteristics, is indicated in Table 5. Sliding distance is also seen as the significant factor for minimizing specific wear rate, and coefficient of friction. Because higher the sliding distance induce adhesion and three body abrasion. Moreover the removed material may weld with the parent material and increased the wear volume. A study was made at a level of 5% connotation that is up to the confidence level of 95%. The values of the sum mean Grey relational grade (GRG) by giving equation (8), help computing the sum of the squared deviations SST. Therefore m is the number of experiments in the orthogonal array then γj is the Grey relational grade for the jth experiment and γm is the total of the mean Grey relational grade at the optimum level. (8)

Table 5

Result for analysis of variance of GRG.

3.4 Multiple linear regression model analysis

In the multiple linear regression investigation examination display was utilized to demonstrate the association between in any event predictor factors and a response variable by fitting a linear equation to the tentatively studied data. The experimental out results, a multiple regression models expose to produce by help of software MINITAB 16. Regression equations which help to develops relationship between’s critical terms tended to from ANOVA, to be Load (N), Sliding Speed (m/s), Sliding Distance (m) and % of reinforcement and their interactions. The regression equation (9) helped for GRG (wear rate and coefficient of friction) is: (9)

From that equation helps to predict wear rate and coefficient of friction of the hybrid Aluminum metal matrix (Al6061/ SiC/B4C/Talc) composites.

4 Conformation experiment

(10)

where Ƞmean is the total mean S/N ratio, Ƞi is the mean S/N ratio at the optimum level; n is the no of main design parameters that influence that quality characteristic. The experimental result showed the optimum parameters, Figure 7a, b and response (Tab. 4), show the variables at level A1-B1-C2-D2 to Load 9.81N, Sliding Speed 1.0 m/s, Sliding Distance 1500 m and 10% of reinforcement. The talc 2% reinforcement in composites is the optimum parameter for achieving the minimum wear rate and coefficient of friction. This improvement is the reason for effective lubricity of talc in the aluminum matrix. The addition of talc increased the sliding force of the work piece material against to the abrasion disc and improves the wear resistance. The above said equation (10) used grey relational grade predicted for the optimal combination of parameters (L1- SS1–SD2 − % Ref 2) and it was valued 0.63058, Table 6 represents a comparison of the predicted characteristic (GRG) with the actual one. The GRG for the confirmation experiment was determined as 0.6264.

thumbnail Fig. 7

EDX spectrum of Al6061/SiC/B4C/talc composites.

Table 6

Confirmation experiment for GRG.

5 Conclusions

The examination of the tribological conduct of the composites, SiC, B4C and talc particle reinforced with aluminum hybrid composites leads to the conclusion that it exhibits better strength and hardness when compared to the base alloy. At the same time, SiC and B4C caused to increase the strength and hardness of composite materials, whereas the soft particles like talc present in the composites caused decrease in wear resistance and also decrease in the coefficient of friction for the wear application purpose. The wear rate was also reduced, thereby improve the machining capability. Aluminum 6061 matrix reinforced by a constant weight percentage of (3 wt.%) B4C and (2 wt.%) talc particulate after that varying the range of addition to (5%, 10%, and 15%) weight of SiC particulate composites which was effectively developed by the stir-casting process. The abrasive wear of different composite specimens was conducted in a pin-on-Disc machine and the results were optimized using L27 orthogonal array on working variables.

  • A load is the most influencing parameter and had a significant impact on GRG-ANOVA values of the composites. Load of 83.910% trailed by Sliding speed of 6.2920%, Percentage of reinforcement of 1.3816% and Sliding distance of 1.2763.

  • Optimum benefits of wear properties were achieved from Load of 9.81N, Sliding Speed 1.0 m/s, Sliding Distance 1500 m and 10% of reinforcement in hybrid composite.

  • The Enhancement of GRG from the initial wear parameters to the optimal wear parameters was 0.10878 and S/N ratio for wear parameters is 0.09603. Under the normal from Load 9.81, Sliding Speed 1.0 m/s, Sliding Distance 1500 m and 10% of reinforcement the operating wear mechanisms are driven to plastic deformation led to mild abrasion. Similar kinds of future research could be done by using other reinforcements such as CBN, Alumina and biochar and varying the input process parameters such as sliding speed, interference temperature, applied load and sliding time.

Nomenclature

: Normalized S/N ratio

i: ith performance characteristic

j: jth experiment

Δij: Replications evaluated formula

ζij: Gray relational coefficient

yj: Gray relational grade

: S/N ratio

ssT: Sum of the squared deviations

γj: Grey relational grade for the jth experiment

γm: The total of the mean Grey relational grade at the optimum level

ηmean: The total mean S/N ratio

ηi: The mean S/N ratio at the optimum level

ηpredicted: Gray relational grade predicted for the optimal combination of parameters

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Cite this article as: Chellamuthu Ramesh kumar, Subramanian Baskar, Ganesan Ramesh, Pathinettampadian Gurusamy, Thirupathy Maridurai, Process optimization using grey relational analysis in dry sliding wear behavior on SiC/B4C/Talc reinforced Al 6061 hybrid metal matrix composite, Metall. Res. Technol. 118, 614 (2021)

All Tables

Table 1

Chemical composition of matrix material Al6061.

Table 2

Process parameters and their levels.

Table 3

Normalized values and overall grey relational coefficient of each performance characteristic with S/N ratios.

Table 4

Response table for GRG for each optimum level for wear parameters.

Table 5

Result for analysis of variance of GRG.

Table 6

Confirmation experiment for GRG.

All Figures

thumbnail Fig. 1

Electrical stir furnace.

In the text
thumbnail Fig. 2

Casted samples.

In the text
thumbnail Fig. 3

(a) Response graph. (b) Response graph.

In the text
thumbnail Fig. 4

SEM image of Al6061 composite with 5wt.% of SiC.

In the text
thumbnail Fig. 5

SEM image of Al6061 composite with 10wt.% of SiC.

In the text
thumbnail Fig. 6

SEM image of Al6061 composite with 15wt.% of SiC.

In the text
thumbnail Fig. 7

EDX spectrum of Al6061/SiC/B4C/talc composites.

In the text

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