Optimization of tribological properties of aluminum hybrid composites using Taguchi design

Veličković, Sandra; Stojаnović, Blaža; Babić, Miroslav; Bobić, Ilija

doi:10.1177/0021998316672294

Cited by 51 publications

(36 citation statements)

References 17 publications

(19 reference statements)

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“…SN relations can be divided into three type characteristics, i.e. smalleris-better, larger-is-better and nominal-is-best [15][16][17]. In this study, smaller-is-better-type characteristic was taken, and SN ratio is calculated by using the following equation:…”

Section: Experimental Designmentioning

confidence: 99%

Parametric optimization of the aluminium nanocomposites wear rate

Veličković

Stojаnović

Babić

et al. 2018

J Braz. Soc. Mech. Sci. Eng.

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The optimization of wear rate of the nanocomposites with A356 aluminium alloy matrix, reinforced with silicon carbide nanoparticles, was performed through the analysis of the following influences: wt% of the reinforcement, normal load and sliding speed. The nanocomposites were produced by the compocasting process with mechanical alloying preprocessing (ball milling). Three different amounts of SiC nanoparticles, with the same average size of 50 nm, were used as reinforcement, i.e. 0.2, 0.3 and 0.5 wt%. Tribological tests were performed on block-on-disc tribometer (line contact) under lubricated sliding conditions, at two sliding speeds (0.25 and 1 m/s), two normal loads (40 and 100 N) and at sliding distance of 1000 m. Analysis of variance (ANOVA) was applied to determine the influence of different parameters on wear value of tested nanocomposites. It was noticed from ANOVA analysis that normal load, with 33.39%, is the most significant factor affecting the wear rate of nanocomposites. The amount of reinforcement, with 28.90%, also has a significant influence on the wear rate, while the influence of sliding speed, with 23.82%, is smaller. It was found that the prediction of wear rate, by using regression model and Taguchi analysis, were close to the experimental values.

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Section: Experimental Designmentioning

confidence: 99%

Parametric optimization of the aluminium nanocomposites wear rate

Veličković

Stojаnović

Babić

et al. 2018

J Braz. Soc. Mech. Sci. Eng.

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“…The authors have also successfully used the Taguchi method in tribological optimization of hybrid composites with aluminum base [29][30][31]. In the field of mechanical construction and mechanization, the Taguchi method can be used, as example, for selecting the ideal toroidal pump and gear power transfer parameters [32,33].…”

mentioning

confidence: 99%

Determination of tribological properties of aluminum cylinder by application of Taguchi method and ANN-based model

Milojević

Stojаnović

2018

J Braz. Soc. Mech. Sci. Eng.

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Energy losses due to friction and wear in reciprocating machines could be potentially reduced by applying new surface, materials and lubrication technologies for friction reduction and wear protection. In this paper, the tribological properties of ferrous-based reinforcements are tested and compared with aluminum alloy (EN AlSi10Mg) as a base material for cylinder of air compressor. The ball-on-plate CSM tribometer is used to carry out these tests under dry sliding conditions and constant sliding distance, for three different values of sliding speed and normal load. The wear factor is analyzed by using Taguchi method as well as artificial neural network-based model, with the aim of finding the optimal parameters. The result of signal-to-noise ratio and analysis of variance shows that the best tribological properties were achieved with reinforcements. Material has the greatest impact on the wear factor (35.54%), followed by load (22.16%) and sliding speed (6.01%). A good superposition was reached of the results obtained by the Taguchi method with the results of the artificial neural network-based model. According to the analysis of surface micrographs, it can close that the bonding material is the most dominant mechanism of wear for both tested materials.

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“…The interaction of the factors does not have a significant impact on the wear rate. Sandra Veličković et al (2016) analyzed the influence of graphite reinforcement, load and sliding speed with constant sliding distance on tribological behavior of A356 aluminum matrix composites reinforced with 10 wt. % silicon carbide and graphite using the Taguchi design.…”

Section: Literature Reviewmentioning

confidence: 99%

Experimental investigation of Wear Characteristics of Aluminium Metal Matrix Composites reinforced with MoS2 and SiC Particles using Taguchi Method

A¹,

Sundaram²,

Krishnan³

et al. 2020

IJRTER

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This paper is investigated the dry sliding wear behavior of Al Metal Matrix Composites reinforced with MoS 2 and SiC particulates. Taguchi's Method is applied to study the effects of reinforcement, load, sliding speed and distance of Al-SiC-MoS 2 hybrid composite made by Stir Casting Method. It is found that addition of SiC particles increases the mechanical strength and wears resistance of Al alloy significantly. In addition to that increase in hardness of the composite resulting the machining a difficult one is reduced by the addition of MoS 2 particles and also results wear reduction.

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Optimization of tribological properties of aluminum hybrid composites using Taguchi design

Cited by 51 publications

References 17 publications

Parametric optimization of the aluminium nanocomposites wear rate

Parametric optimization of the aluminium nanocomposites wear rate

Determination of tribological properties of aluminum cylinder by application of Taguchi method and ANN-based model

Experimental investigation of Wear Characteristics of Aluminium Metal Matrix Composites reinforced with MoS2 and SiC Particles using Taguchi Method

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