ASSESSMENT OF TRIBOLOGICAL PERFORMANCE OF AL/CSA COMPOSITES USING RSM

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1 International Journal of Mechanical Engineering and Technology (IJMET) Volume 9, Issue 13, December 2018, pp , Article ID: IJMET_09_13_046 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed ASSESSMENT OF TRIBOLOGICAL PERFORMANCE OF AL/CSA COMPOSITES USING RSM P. Thimothy Associate Professor, Department of Mechanical Engineering, Miracle Engineering College, Vizianagaram, Andhra Pradesh, India Ch. Ratnam Professor, Department of Mechanical Engineering, Andhra University, Visakhapatnam, Andhra Pradesh, India Siva Sankara Raju Assistant Professor, Department of Mechanical Engineering, Aditya Institute of Technology and Management, Tekkali, Andhra Pradesh, India ABSTRACT In this study, the evaluation of tribological behaviour of aluminium metal matrix composites (AMC) reinforced with coconut shell ash (CSA) using response surface methodology (RSM). The effort is anticipated to optimize the variable process parameters such as load (N), % of CSAp (% of vol.), Sliding distance (m) and sliding velocity (m/s), with wear rate (WR) (mm 3 /m) and coefficient of friction (COF) have been considered as a response in this study. Thirty numbers of experiments are designed based on face centered composite (CCF) and held on Pin-On-Disc wear testing machine. The ANOVA result revealed load is the most influenced parameter which followed by % of CSAp, sliding distance and sliding velocity. Key words: AMCs, Wear rate, Coefficient of Friction, CSA, and RSM. Cite this Article: P. Thimothy, Ch. Ratnam and Siva Sankara Raju, Assessment of Tribological Performance of AL/CSA Composites Using RSM, International Journal of Mechanical Engineering and Technology 9(13), 2018, pp INTRODUCTION Solar In the modern decades, the expert of designers and researchers are concentrated prominence on finding lighter in weight, ecological responsive, low-cost, high superiority, and best performance materials. Now a day s Aluminium based Metal Matrix Composites (AMC) has traditional growing attention as engineering materials due to their lightness, high specific strength and superior wear resistance. Abundance of an appropriate combination of editor@iaeme.com

2 Assessment of Tribological Performance of AL/CSA Composites Using RSM matrix with various reinforcing materials has grown to be an interesting area of manufacturing discipline in MMCs [1] [3]. Most of the investigation has lifted based on the traditional crude reinforcement like SiC, Al2O3, B4C, BN and TiC etc., but those were disastrous; concentrate on convenient and economic aid crudes in the environment. Metal Matrix Composites (MMCs) are formulated by the supplement of an aid aspect to the matrix by the work of several approaches such as and Liquid Metallurgy and Powder Metallurgy (PM). Particulate reinforced alloy matrix composites have started economic value in many forms and they can be built by traditional refining approaches [4] [7]. Many analysts have done attempts towards developing natural reinforcement particulates and usage of by-works from corporations/rural by-products such as coconut shell, apricot grains, sugarcane bagasse, nutshells, forest residues and tobacco stems, fly ash, red mud, colliery shale from coal mines[8] [13]. Alloy matrix composites (AMCs), are utilized owing to interfacial attitude and moderate density as correlated to aluminium alloys. Therefore, AMCs becomes suppressed in manufacture on a massive modern scale viz. automotive production for formation of different segments, such as cylinders, motor lid, connecting shafts and separate casts, have done owing to their excellent castability, and excessive erosion protection [3], [14]. The amount of wear volume loss decreased due to addition of graphite in MMC. This may be caused due to the fact that graphite is used as a solid lubricant. Sliding distance increases with increase wear volume loss, due to ploughing affect and fractured particles between tribo surfaces. Addition of Gr particles increases, the wear resistance [15]. The hardness values of coconut shell ash (CSA) composites increased with an increasing percentage of CSA particle [16] [18]. The wear mechanism changes from abrasive and adhesive wear, with decreased reinforcement in composite. An addition of fly ash, composite s hardness increases that material becomes less ductile, increasing addition of fly ash, specific wear rate increases[19]. The coefficient of friction and consequently, the wear rate of the composites were observed to increase with an increase in rice husk ash white. % and wear mechanism of the composites was observed to transform from predominant abrasive wear to adhesive wear with an increase in RHA with. Percentage reported by [11], [20]. Wear and coefficients of friction for Al-Gr composites tend to decrease with increasing the graphite content due to the formation of graphite film on the surface [21] [23]. The dry sliding wear resistance of Al-fly ash composite is almost similar to that of Al 2 O 3 and SiC reinforced Al-alloy [24]. Effect of applied pressure on the tribological behavior of SiCp reinforced aluminium alloy was investigated under varying applied pressure ( Mpa) and a sliding speed of 3.35 m/s, and reported that wear and friction of representative materials are well explained in terms of roughness effect, hardness effect, ductility effect, oxide film effect, reaction layer effect and transfer effect[25]. The objective of this study is to utilize coconut shell ash, which is an agro waste, easily available at low cost and possess many ecological problems, as an effective filler material for the preparation of Al MMCs. The present study is to investigate the dry sliding behaviour of Coconut shell ash particulates (CSA) reinforced in aluminium composites produced with various %Volume of 5%, 10% and 15% of weights. A quadratic correlation for WR and COF is developed in terms of control parameters. ANOVA revealed optimal condition of WR and COF on composite has been investigated. 2. EXPERIMENTAL SETUP Cast Al-CSA composites contain in-situ produced CSA particulates has been developed by stir casting route varying amount of CSA volume in the molten melt, the procedures sequences for preparation of reinforced particulates (i.e., CSA) and composite preparation are detailed in elsewhere[9], [12], [17], [26] [29]. Hardness test (Model: DHV 1000) has been performed with load of 0.1N. The tensile properties of Al-CSA have been tested with Hounsfield tensometer (Model: ETM-ER3/772/12). Pin-on-Disc tester (Model; DUCOM editor@iaeme.com

3 P. Thimothy, Ch. Ratnam and Siva Sankara Raju LE-PHM-400) has been used for identification of dry sliding wear behaviour of cast Al-CSA composites. The in-situ cast composites were slided against a steel counter face (EN-31, 62 HRC) with constant track of 50 mm. Wear rate is the ratio of volume loss per unit sliding distance. Volume loss is calculated from weight loss to density of sample[9], [12], [29]. Coefficient of friction is measured as frictional forces per unit normal load [13], [28], [30]. Table 1 Processes Parameters and Their Levels Levels Variable Factors Symbol Unit Load A N %of CSA B % of Vol Sliding Distance C m Sliding Velocity D m/s This CCF study carries experimentation of four factors among resulted of two responses. In this design of the experiment, sixteen (16) factorial points, eight axial points (2x4) and six centre runs, a total of 30 experimental runs have been considered [31], [32]. The complete experimental range with levels of independent variables is listed in Table 1. The design of matrix along with the experimental results of wear rate (WR) and coefficient of friction (COF) is represented as Table 2. A randomized experimental run has been carried out to minimize the responses. Analysis of variance (ANOVA) has been used to investigate the individual, interaction and square effects of the process variables on the response. Table 2 Design of Experiments Test Combinations WR(*10-3) COF Test Combinations WR(*10-3) COF M abcd a Aa b Aa ab Ab c Ab ac Ac bc Ac abc Ad d Ad ad Zero bd Zero abd Zero cd Zero acd Zero bcd Zero RESULTS AND DISCUSSION 3.1. Mechanical properties of Al-CSA MMC The hardness of Al-CSA composites increased due to the hard phase of CSA particle in addition to the uniform distribution in the composite. The tensile strength increases with increase in volume fraction of CSA particle, even as the elongation decrease with increase in the addition of CSA particles. Hardness and percentage of elongation inversely proportional character, with an increase in reinforcement as observed in Figure 1, which is due to strain hardening of the composite. Reinforcement particles are harder due to the presence of reinforced CSA, which increases load bearing capability, with constraints dislocation editor@iaeme.com

4 Assessment of Tribological Performance of AL/CSA Composites Using RSM movement of the matrix, reduces interspacing and particle movement has been critical [26], [33], [34]. Figure 1 Mechanical Properties of CSA composites 3.2. Development of regression equations using RSM based CCF Regression analysis has been performed to fit the response function of wear loss and coefficient of friction. The final experimental models in terms of code factor (apart of the insignificant terms) for WR (Y1) and COF (Y2) are shown in Equations 1 and 2 respectively. (1) The F-values are (Eqs. 1 and 2) found to be and respectively, which implies that the correlations obtained are significant. There is only 0.01% chance that a Model F- Value this large could occur due to noise. Probability value is less than 0.05 specify model terms are significant. Thus, wear rate (WR) of model terms A, B, C, AB, AC and C 2 are significant, where as for coefficient of friction (COF) A, B, C, D, AC, A 2 and B 2 are significant. Table 3 ANOVA for Wear rate Source SS DF MS F Value Prob > F Contrib.%. Remark Model < % significant A < % significant B % significant C < % significant D % AB % significant AC % significant AD % BC % BD % CD % A % (2) editor@iaeme.com

5 P. Thimothy, Ch. Ratnam and Siva Sankara Raju B % C < % significant D % Residual % LoF % significant Error % Total R2 AdjR2 Pred R2 Adeq Precision From the Table 3 and Table 4, the values of R 2 and R 2 adj have been found to be & and & for WR and COF respectively. The predicted R 2 is in reasonable agreement with the R 2 adj. Adequate precision measures the signal to noise ratio. A ratio greater than 4 is desirable. The ratio of and for WR and COF respectively obtained in the present study indicates an adequate signal. Thus, the developed correlations can be used to navigate the design space. Table 4 ANOVA Coefficient of friction Source SS DF MS F Value Prob > F Contrib.%. Remark Model 2.56E E < % significant A 2.08E E < % significant B 6.65E E % significant C 4.87E E % significant D 6.01E E % significant AB 1.30E E % AC 6.16E E % significant AD 2.07E E % BC 6.40E E % BD 4.41E E % CD 1.26E E % A E E % significant B E E % significant C E E % D E E % Residual 7.72E E % LoF 7.49E E % significant Error 2.28E E % Total R 2 AdjR 2 Pred R 2 Adeq Precision Interactions effect for Coefficient of friction From Figure 2 (a), the interaction effect of load and % of CSAp on coefficient of friction of constant sliding distance 2000m and sliding velocity 1.5m/, it is clear that as the load increases coefficient of friction increases due to increase in plastic deformation which in turn due to increase in the hardness of composite. Similarly, with an increase in CSA reinforcement up to 11%, the coefficient of decreases and then it increases. The decrease may be due to the reformation of graphitic nature or may be due to mechanically mixed layer, whereas the increase is because of a decrease in the binding properties of CSA editor@iaeme.com

6 Assessment of Tribological Performance of AL/CSA Composites Using RSM Figure 2(a) combined effect of % of reinforcement and load (b) sliding distance and load velocity and load on coefficient of friction (c) sliding Figure 2 (b), the combined effect of sliding distance and load at constant sliding velocity 1.5 m/s for 10% CSAp reinforced MMC; it is clear that with an increase in load coefficient of friction increases. Wear increases with increases in load, the oxide film formation effect on the counter surface. At lower loads, oxide film remains intact due to low ductility and shear strength which prevent for reduction of friction between the pin and disc. It causes for low wear and coefficient of friction. While the load increases oxide film has no longer capable of restricting higher stresses which causes increases wear and coefficient of friction. Simultaneously, with an increase in sliding distance up to 1800m, coefficient of friction increases and then decreases. At the initial instant of period motion between two bodies is difficult which offers more friction between components (pin and disc), after certain sliding distance coefficient of friction decreases due to formation of the protective oxide layer which prevent in the reduction of friction between the pin and counter face. Figure 3 Combined effect of sliding distance and % of reinforcement on coefficient of friction Figure 4 Combined effect of sliding velocity and % of reinforcement on coefficient of friction The combined effect of load and sliding velocity on coefficient of friction with 10% of CSAp and sliding distance 2000m is shown in Figure 2 (c). As the load increases, coefficient of friction increases, whereas with an increase in sliding velocity coefficient of friction decreases, which may be due to the reinforced CSAp in the composites are squeezed out onto the mating surfaces forming MML [38-40] and also the smeared particles formed the layer in contact interface. The layer prevents a shorter period due to increased sliding velocity. This editor@iaeme.com

7 P. Thimothy, Ch. Ratnam and Siva Sankara Raju results in increased coefficient of friction at increasing sliding speed. While a combination of sliding distance and sliding velocity increase the pin thermally stable and protective layer withstand more time. So that coefficient of friction decreases with increases of sliding velocity as constant sliding distance. The interaction effect of a % of CSAp and sliding distance on coefficient of friction at constant load of 30N and sliding velocity of 1.5m/s (Fig 3), represents the coefficient of friction decreases up to 11% of CSAp then increases whereas it increases with increase in sliding distance up to 2000m and then decreases. The combined effect of a % of CSAp and sliding velocity on coefficient of friction at constant load 30 N and sliding distance 2000m is presented as Fig. 4. Figure 5 Combined effect of sliding velocity and sliding distance on COF It is clear that the coefficient of friction decreases with increase in CSAp reinforcement up to 11% and then increases due to decrease in wear. While the addition of hard reinforced particle matrix becomes harder. Similarly below of the pin surface form a protective layer which prevent the surface from the shear of planes at higher loads. This reduces coefficient of friction. Similarly, the combined effect of sliding distance and sliding velocity on coefficient of friction at constant load of 30N and a % of CSAp 10% is shown in Fig. 5. As the sliding velocity increases coefficient of friction decreases while it increases with the increase in sliding distance up to 2000m and then decrease. Figure 6 (a) Optimized region for WR (b) optimized region for COF editor@iaeme.com

8 Assessment of Tribological Performance of AL/CSA Composites Using RSM 4. OPTIMIZATION OF RESPONSE BY USING RSM An essential aspiration of this investigation is to identify the optimum process parameters to underestimate both wear rate (WR) and coefficient of friction (COF) from the analytical model equations generated. Quadratic model equations have been developed using quadratic programming (QP) to minimize the responses within the empirical range considered. Optimum region for WR and COF on the load and the pct. of CSA is shown in Figure 6 (a) and Figure 6(b). The optimum conditions for WR and COF for CSA reinforced composite is illustrated in Table 8, to obtain values is and respectively. Table 5 Optimal condition for responses Parameters Wear rate Coefficient Of Friction A (N) B (% of vol.) C (m) D(m/s) CONCLUSIONS In the present work, Al-CSAp composites are prepared with stir casting route. The tribological performance of composites is carried-out via process parameters such as load, % of CSA, sliding velocity and sliding distance to determine the optimal condition. The experiments are model by using RSM. The proposed conclusions have been listed below. Tensile strength, hardness values are increased with increasing pct. of CSA, whereas elongations and density decreased. The experiments are designed using Response surface methodology (RSM) based CCF. Quadratic Programming has been used to model and optimize the influence of four process parameters on responses such as wear rate (WL) and coefficient of friction (COF) of CSAp reinforced MMC. The ANOVA result revealed the load is the most influence parameter which followed by % of CSAp, sliding distance and sliding velocity. F-values of quadratic equation for WR and COF are found to be and respectively. 3D response surface plots are simulated from the models presented to describe the effect of the process variables on the responses The optimum conditions for WR and COF for CSA reinforced composite is and respectively. The developed regression equation was tested and obtained least error which indicates model has good adequacy. REFERENCES [1] C. A. Rodopoulos, Metal Matrix Composites, in Advanced Materials by Design, 2004, pp [2] P. K. Rohatgi and B. Schultz, Lightweight Metal Matrix Nanocomposites - Stretching the Boundaries of Metals, Mater. Matters, vol. 2, no. 4, pp. 1 6, [3] P. K. Rohatgi, Metal-matrix Composites, Def. Sci. J., vol. 43, no. 4, pp , [4] A. Baradeswaran, S. C. Vettivel, A. Elaya Perumal, N. Selvakumar, and R. Franklin Issac, Experimental investigation on mechanical behaviour, modelling and optimization of editor@iaeme.com

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