Optimization of dry sliding wear parameters of AA336 aluminum alloy‐boron carbide and fly ash reinforced hybrid composites by stir casting process

Arunachalam, S.; Chelladurai, Samson Jerold Samuel

doi:10.1002/mawe.201900069

Cited by 13 publications

(7 citation statements)

References 26 publications

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“…Whereas, load, sliding speed, and sliding distance were chosen as input parameters [58,71,72]. The sliding wear parameters range were selected as load: 10-50 N; sliding distance: 500-1,500 m; sliding speed: 0.5-1.5 m/s, based on previous literature [29,39,44,58,70,73]. Further, five levels of each factor were calculated as per the central composite design based on the rotability value (α = 1.682), which was obtained using Minitab 19 software (detailed discussion in experimental design section) [62,73,74].…”

Section: Dry Sliding Wear Testmentioning

confidence: 99%

“…Fly-ash is very rich in SiO 2 and Al 2 O 3 contents compared to red mud. Moreover, reinforcing fly-ash with Al alloys reduces the density and enhances the mechanical and tribological properties of the composite without increasing the cost [9,37,38,43,44]. This makes fly-ash suitable for use as secondary reinforcements for the hybrid composites.…”

Section: Introductionmentioning

confidence: 99%

“…However, weight loss decreased with an increase in sliding velocity. The optimal values were found as 18.1 N of load, 905.4 m of sliding distance, and 4.18 m/s of sliding distance [44]. Reddy et al investigated the mechanical and tribological aspects of Al7075/B 4 C/fly-ash composite and concluded that the incorporation of B 4 C and fly-ash into the Al7075 alloy tremendously enhances the micro-hardness, tensile strength, and wear resistance.…”

Section: Introductionmentioning

confidence: 99%

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Experimental Investigation, Modeling, and Optimization of Wear Parameters of B4C and Fly-Ash Reinforced Aluminum Hybrid Composite

Sahu

2020

Front. Phys.

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Lightweight and high-wear performance materials are currently in demand for various advanced applications in areas such as aerospace and automobiles. These demands can be achieved by hybrid aluminum matrix composites (HAMCs), as they possess excellent mechanical and tribological properties which can be customized using more than one reinforcement. Boron carbide (8 wt.%) and fly-ash (2 wt.%) reinforced hybrid aluminum 7075 composite was successfully fabricated using a stir-casting route. Wear is a crucible phenomenon that occurs over the interaction of surfaces and affects the performance of the material. To investigate wear behavior of developed HAMC, dry sliding wear tests were conducted based on the central composite design, taking the specific wear rate as a response parameter. Modeling of wear parameters is crucial, as it helps to predict the value of the wear response at the given set of input parameters without performing experimentation. Response surface method (RSM) was used for the modeling of wear parameters to develop an empirical model of specific wear rate in terms of load, sliding speed, and sliding distance. The high value of the coefficient of determination (R 2 = 0.9894) illustrates the goodness of fit of the developed model. Moreover, the optimal condition of wear parameters was determined as 20 N load, 1.5 m/s sliding speed, and 500 m sliding distance; the predicted value of specific wear rate in this set of parameters is 0.2 × 10 −5 mm 3 /N-m. The validation test at optimal conditions was performed and the specific wear rate was found to be 0.205 × 10 −5 mm 3 /N-m, which shows good agreement with the predicted value. The worn-out surface and debris were analyzed using scanning electron microscope (SEM) images and electron dispersive spectrums (EDS) to completely explore the mechanism of wear.

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Section: Dry Sliding Wear Testmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Experimental Investigation, Modeling, and Optimization of Wear Parameters of B4C and Fly-Ash Reinforced Aluminum Hybrid Composite

Sahu

2020

Front. Phys.

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“…Moreover, composites exhibited a lower wear rate and enhanced mechanical properties than base alloy. Arunachalam and Chelladurai [10] fabricated 10 wt.% B4C and 5 wt.% FA reinforced AA356 hybrid composites by stir casting process. RSM was used for experimental design and prediction of wear rate and optimization of wear parameters.…”

Section: Introductionmentioning

confidence: 99%

Dry Sliding Wear Behaviour of Al6061 Hybrid Metal Matrix Composites using Response Surface Methodology

Singh

Gupta

2022

IOP Conf. Ser.: Mater. Sci. Eng.

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This paper presents an investigation of the dry sliding wear behaviour of Al6061 hybrid metal matrix composites reinforced with B4C (3 wt.%) and eggshell ash (3, 6, 9 and 12 wt.%) fabricated through the stir casting process. A four factors and five-level central composite design (CCD) were used for experiments through response surface methodology. The factors considered for design were eggshell ash (0-12 wt.%), load (10-50 N), sliding speed (0.8-4 m/s) and sliding distance (300-1500 m). The experiments were performed using a pin-on-disc tribometer according to the ASTM G99 standard at room temperature for 30 combinations. Based on experimental results, a regression model was developed to predict the wear rate, and its adequacy was checked with analysis of variance (ANOVA) and confirmation tests. The ANOVA results showed that sliding speed was the most significant factor followed by the load, which significantly influences the response. Wear rate increased with the increase in load and sliding distance, whereas it decreased with the increase in wt.% of eggshell ash and sliding speed. The increase in wear rate with the increase in load can be caused by the increase in tip pressure, and in case of sliding distance it may be due to increase in contact time. Whereas, decrease in wear rate with the increase in sliding speed can be caused by the decrease in contact time and higher wt.% of eggshell also reduced the wear rate and it may be due to the increase in composites hardness.

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“…Similarly, sliding wear modeling of A336-SiC-fly ash composites was carried by RSM where the wear loss was increased with an increase in the applied load and sliding distance whereas a reduction trend was observed with sliding velocity. 22 In addition to the above approaches, the optimization of wear parameters was also carried out with the help of RSM for Al/SiC composites. 23 The reinforcement content and sliding distance were found to be influential factors in statistical modeling.…”

Section: Introductionmentioning

confidence: 99%

Multi-response modeling for sliding wear behavior of AA5052/TiC composites by stir casting: A comparative analysis using response surface methodology and fuzzy logic system

Samal

Vundavilli

Meher

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part E:

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The present research deals with the modeling of wear performance of AA5052 metal matrix composites (MMCs) reinforced by in-situ formed TiC particles using two methods, namely statistical-based non-linear regression and fuzzy logic system. A pin-on-disc apparatus is employed to obtain the wear data of the composites. Three different process parameters, namely weight percentage of TiC, sliding distance, and applied load are considered as the input variables, and the volumetric wear loss and coefficient of friction are taken as output variables of the wear process. Regression models are formulated to study the output responses based on the wear results. To check the significance and contribution of the various control parameters, analysis of variance method was performed. Further, confirmatory tests were also conducted to validate both the models. It has been observed that the sliding distance and applied load have shown a substantial effect on the volumetric wear loss. It is also observed that the coefficient of friction is found to be increased with the rise in the sliding distance. The novelty of the work lies in using fuzzy logic to establish the wear model for aluminum 5052 MMC. A comparative study is performed to analyze the prediction accuracy of the models for the wear characteristics of the aluminum composites. Consequently, this wear modeling investigation will give a better understanding the effect of parameters and the responses influence of wear phenomena of Al 5052/TiC composites, which further will help in developing wear components for industrial applications.

show abstract

Optimization of dry sliding wear parameters of AA336 aluminum alloy‐boron carbide and fly ash reinforced hybrid composites by stir casting process

Cited by 13 publications

References 26 publications

Experimental Investigation, Modeling, and Optimization of Wear Parameters of B4C and Fly-Ash Reinforced Aluminum Hybrid Composite

Experimental Investigation, Modeling, and Optimization of Wear Parameters of B4C and Fly-Ash Reinforced Aluminum Hybrid Composite

Dry Sliding Wear Behaviour of Al6061 Hybrid Metal Matrix Composites using Response Surface Methodology

Multi-response modeling for sliding wear behavior of AA5052/TiC composites by stir casting: A comparative analysis using response surface methodology and fuzzy logic system

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