OPTIMIZATION OF CASTING PARAMETERS ON Al/RHA COMPOSITE USING TAGUCHI METHOD

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1 Advanced Materials Research Online: ISSN: , Vols , pp doi: / Trans Tech Publications, Switzerland OPTIMIZATION OF CASTING PARAMETERS ON Al/RHA COMPOSITE USING TAGUCHI METHOD S.D.Saravanan 1* and M.Senthilkumar 2 1 Department of Mechanical Engineering, 2 Department of Production Engineering PSG College of Technology, Coimbatore, INDIA. * 1 sdssaravanan@gmail.com, 2 msenthil_kumar@hotmail.com Keyword: Rice Husk Ash, Taguchi method, ANOVA, Tensile strength, Hardness. Abstract: In the present work, Taguchi method was employed to optimize tensile strength and hardness of the stir casted Al/RHA composite. The composites were prepared by varying stir casting parameters like stirring time (6, 9, 12 min), stirring speed (100,200,300 r.pm), and weight percentage of RHA reinforcement (6, 9, 12 %). All the experiments were conducted based on plan of experiments (L 9 Orthogonal array) generated through Taguchi Technique. The individual influence of each process parameters on the hardness and tensile strength was determined by using analysis of variance. The result implies that the wt. % of RHA reinforcement was found to be a highly influenced parameter followed by stirring time and stirring speed. Finally, confirmation test was done to verify predictive model with the experimental results. Introduction Aluminum based metal matrix composite exhibits many attractive material properties such as increased stiffness, wear resistance, specific strength, vibration damping and decreased coefficient of thermal expansion compared with the conventional aluminum alloys [1]. Al Si alloys are widely used composite for various automobile applications such as pistons, brake rotors, calipers and cylinder liners [2]. For making low cost composites, researchers utilized the silica rich waste materials as reinforcements. In this way, aluminum alloy was reinforced with agriculture waste such as rice husk ash (RHA) to fabricate a composite [3]. Also an extensive study was carried out to predict the tribological properties of aluminum alloy composite reinforced with RHA by varying the RHA particle size reinforcement [4]. Inorder to enhance the mechanical properties of Al/RHA composite, a casting parameters of the composite are to be optimized. Taguchi technique is a powerful tool for the design of high quality systems. It provides a simple efficient and systematic approach to optimize design for performance, quality and cost. The methodology is valuable when design parameters are qualitative and discrete [5]. In this method, influencing parameters are assigned in a specific orthogonal array to determine the optimal combination for given response [6]. So, the Taguchi method was effectively used to investigate the dry sliding wear behavior of aluminum based composite materials [7]. Also an attempt has been made to optimise the sintering process parameters of Al Si (12%) alloy/fly ash composite using taguchi method and reported that multi-response characteristics such as density and hardness can be improved effectively [8]. The green sand casting process parameters were optimized using taguchi method and observed the most significant process parameters [9]. Optimization of squeeze casting parameters for nonsymmetrical AC2A aluminium alloy castings was done through Taguchi method and found that squeeze pressure, die preheating temperature and compression holding time were the parameters making significant improvement in their mechanical properties [10]. In this paper, an attempt was made to find the influence of stir casting parameters such as stirring time, stirring speed and percentage of RHA reinforcement on tensile and hardness behaviours of Al-RHA composites using Taguchi s techniques [10]. The interaction effect of above mentioned parameters were investigated with ANOVA and a regression equation was developed for each response. Further, confirmation test have been conducted to validate the test result. All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of Trans Tech Publications, (ID: , Pennsylvania State University, University Park, USA-12/05/16,12:44:38)

2 292 Modern Achievements and Developments in Manufacturing and Industry Experimentation Composite Preparation: In this present study, aluminium alloy (AlSi10Mg) was used as a matrix material and agriculture waste such as rice husk ash was used as a reinforcement material. Initially, Al alloy was charged into the graphite crucible and heated to 800 ºC till the entire alloy in the crucible was melted (Figure 1). The reinforcement particles (RHA) were preheated to 600 C for three hours before dispersing into the melt. After the Al alloy was fully melted, a standard degassing agent (C 2 Cl 6 ) of 30 gm was added to reduce the porosity. Also, 1 wt% of magnesium was added arbitrarily into the molten melt to enhance the wettability between the rice husk particles and alloy melt. Figure 1 Stir casting equipment and SEM image of Al/RHA composite. A stainless steel stirrer was lowered into the molten melt slowly upto 2/3 of the height of the molten metal from the bottom of the crucible and it was stirred at a speed of 100 rpm. The preheated RHA particles were now added into the molten metal at a constant rate of 1-2 gm per shot by gradually increasing the stirrer speed from 100 to 300 rpm. The stirring action was continued for 5 minutes even after the completion of particle feeding. The mixture was poured into the mould which was also preheated to 500 ºC for 30 min to obtain the uniform solidification. Similar procedure was repeated next composite samples by varying stirring time as 10 & 15 min, stirring speeds as 400 & 500 rpm s and weight fraction as 9% and 12 % RHA reinforcements. Experimental procedure: The dimensions of the resulted casting samples are 30 mm diameter and 120mm length cylindrical rod. The fabricated composites were observed with scanning electron microscope (SEM). The SEM image as shown in Fig. 1 indicates the uniform distribution of RHA particles over aluminium alloy. The tensile tests were conducted on these samples according to ASTM E08 at room temperature, using a universal testing machine (INSTRON). The specimens used were of diameter 12 mm and Gauge length 40 mm, machined from the cast composites with the gauge length of the specimen parallel to the longitudinal axis of the castings. The hardness was measured using Brinell Hardness Tester at a load of 500 kg for a period of 15 sec in accordance with the ASTM E10. Taguchi technique: In the design of experiment, Taguchi method was used because it is a problem solving tool which can improve the performance of the product, process design and system. This method combines the experimental and analytical concepts to determine the most influential parameter on the result response for the significant improvement in the overall performance. Design of experiment is a technique of defining and investigating all possible conditions involving multiple factors, parameters and variables in an experiment. It establishes the method for drawing inference from observation, when these observations are not exact, but subject to variations and also used to

3 Advanced Materials Research Vols collect data. A three level L9 -orthogonal array with nine experimental runs was selected [12]. To observe the most influential process parameters in the preparation of composite namely stirring time, stirring speed and wt. % of RHA reinforcement each at three levels were considered and are shown in Table 1. Table 1 Factors and their Levels Table 2 Design matrix and their experimental results Level Stirring Time (T) min Stirring Speed (S) rpm Weight % of RHA Reinforcement (R) % Run T S R Hardness HB Tensile Strength (N/mm 2 ) Results and Discussions S/N ratio analysis: The design matrix, tensile strength and hardness values of the Al/RHA composites prepared with different stirring speeds, stirring times and weight fraction are given in Table 2. The S/N ratio values for tensile strength and hardness are calculated by taking into consideration larger the better quality considerations. The measured responses were analyzed by using a standard commercial statistical software package MINITAB 14. Table 3 Response S/N ratios of Hardness and Tensile Strength Level Hardness value Tensile strength T S R T S R Delta Rank The Hardness response table for the stirring time, stirring speed and weight fraction was created in the integrated manner and the results were shown in Table 3. Based on the analysis of the S/N ratio, the optimal casting parameters for maximizing the hardness values was obtained at 25 min stirring time (level 3), 500rpm stirring speed (level 2) and 12 % weight fraction of reinforcement (level 3). Fig. 1 shows the effect of the casting parameters on the hardness values and it was observed that the hardness of the composites increases with increase in stirring time and weight fraction of reinforced particles and shows negligible changes with increase in stirring speed.

4 Mean of SN ratios Mean of SN ratios 294 Modern Achievements and Developments in Manufacturing and Industry Main Effects Plot for SN ratios Data Means Main Effects Plot for SN ratios Data Means 37.0 T S T S R R Signal-to-noise: Larger is better 12 Signal-to-noise: Larger is better Fig. 1. Effect of casting parameters on Hardness value and Tensile strength The tensile strength response table for the stirring time, stirring speed and weight fraction was created in the integrated manner and the results were given in Table 3. Regardless of the category of the performance characteristics, a greater S/N value corresponds to a better performance. Therefore, the optimal level of the casting parameters is the level with the greatest S/N ratio value. Based on the analysis of the S/N ratio, the optimal casting parameters for maximizing the tensile strength was obtained at 25 min stirring time (level 3), 400 rpm stirring speed (level 1) and 12 % weight fraction of reinforcement (level 3). Fig. 2 shows the effect of the casting parameters on the tensile strength values. From Fig. 3 it is observed that the tensile strength of the composites increases with increase in stirring time and weight fraction of reinforced particles and decreases with increase in stirring speed. Analysis of variance: ANOVA results for hardness values of the composites were shown in the Table 4. ANOVA helps in formally testing the significance of all main factors and their interactions by comparing the mean square against an estimate of the experimental errors at specific confidence levels. The predicted residuals R 2 of is in reasonable agreement with the adjusted R 2 of It can observed that the stirring time (T), stirring speed (S) and weight fraction of reinforced particles (R) affect the hardness value by 42.9%, 0.17% and 53.4% in stir casting of Al/RHA composites. Table 4 ANOVA results for Hardness values Table 5 ANOVA results for Tensile Strength DF Seq SS SS MS F P Pr % T S R Error Total Source Source DF Seq SS SS MS F P Pr% T S R Error Total

5 Advanced Materials Research Vols ANOVA results for tensile strength were shown in Table 5. The predicted R 2 of 0.98 is in reasonable agreement with the adjusted R 2 of It can observed that the stirring time (T), stirring speed (S) and weight fraction of reinforced particles (R) affect the tensile strength by 35.69%, 1.17% and 61.58% in stir casting of Al/RHA composites. Multiple Linear Regression Model : A multiple linear regression model was developed using statistical software MINITAB 16. This model provides a relationship between an independent/predicted variable and a response variable by fitting a linear equation to the observed data. Among various regression models, a linear regression model was specially employed in mechanical properties study. The regression equation for hardness and tensile strength of Al/RHA composite were as follows Hardness = T S R (1) Tensile Strength = T S R (2) Conformation test: The confirmation test was conducted by selecting the set of parameters utilized with the levels of the optimal casting parameters T3S3R3 for hardness value and T3S2R3 for tensile strength value in the casting of Al/RHA composites. Based on data set, experiments were conducted and their results were noted. Then, a comparison was made between the experimental values and the computed values obtained from the regression model. Computed values from the regression equation and the experimental values for the hardness and tensile strength of the composites are nearly the same with the least error (±5%). The resulting regression equations seem to be capable of predicting the hardness and tensile strength to the acceptable level of accuracy. Table 6 Results of confirmation tests for hardness and tensile strength. Optimal Casting Parameters for Al/RHA composites Hardness Tensile strength Prediction Confirmation Prediction Confirmation T3S3R3 T3S2R Conclusions Based on this study, major conclusions are as follows: Rice Husk Ash, the agricultural waste generated from milling paddy can be successfully used as a reinforcing material to produce Metal-Matrix Composite. Thus the use RHA ash for the production of composites can turn agricultural waste into industrial wealth and inevitably solve the problem of storage and disposal of RHA. The optimum level of casting parameters to obtain maximum hardness and tensile strength for stir casting of Al/RHA composites are 12% weight fraction of RHA particles, 25 min stirring time and 500 rpm stirring speed. The weight percentage of RHA reinforcement (53.33%) has the highest influence on hardness followed by stirring time (42.90%) and stirring speed (0.17 %). For tensile strength, the contribution of wt. % reinforcement is 61.58%, stirring time is 35.69% and stirring speed is 1.57%. Confirmation experiment was carried out and a comparison was made between experimental values and computed values, showing an error associated with harness and tensile strength of composites was observed as less than 0.5 %. Thus, the Taguchi method was successfully used.

6 296 Modern Achievements and Developments in Manufacturing and Industry References [1] O'donnell, G., and L. Looney, Production of aluminium matrix composite components using conventional PM technology, Materials Sci. and Engg. 303 (2001) [2] Hemanth, Joel. Abrasive and slurry wear behavior of chilled aluminum alloy (A356) reinforced with fused silica (SiO 2 p) metal matrix composites, Composites Part B: Engg. 42 (2011) [3] Das, S., T. K. Dan, S. V. Prasad, and P. K. Rohatgi. Aluminium alloy-rice husk ash particle composites. J. of materials Sci. Letters, 5 (1986) [4] Saravanan, S. D., M. Senthilkumar, and S. Shankar, Effect of Particle Size on Tribological Behavior of Rice Husk Ash Reinforced Aluminum Alloy (AlSi10Mg) Matrix Composites, Tribology Transactions, 56 (2013) [5] Ross P.J, Taguchi Technique for Quality Engineering, McGraw Hill, NewYork, USA, 2nd edition1996. [6] Nalbant, M., H. Gökkaya, and G. Sur. Application of Taguchi method in the optimization of cutting parameters for surface roughness in turning, Materials & Design, 28(2007) [7] Basavarajappa, S and Chandramohan G., Application of Taguchi techniques to study dry sliding wear behaviour of metal matrix composites, Materials and Design, 28 (2007) [8] Jailani, H. S., Rajadurai, A., Mohan, B., Kumar, A. S., and Sornakumar, T., Multi-response optimisation of sintering parameters of Al Si alloy/fly ash composite using Taguchi method and grey relational analysis. Int. J. of Adv. Manuf. Tech., 45(2009) [9] Guharaja, S., A. Noorul Haq, and K. M. Karuppannan., Optimization of green sand casting process parameters by using Taguchi s method, Int. J. of Adv. Manuf. Tech., 30(2006) [10] Senthil, P and Amirthagadeswaran.K.S, Optimization of squeeze casting parameters for non symmetrical Al. alloy castings through Taguchi method. J. of mech. Sci. and tech. 26 (2012)

7 Modern Achievements and Developments in Manufacturing and Industry / Optimization of Casting Parameters on Al/RHA Composite Using Taguchi Method /