Optimization on Tribological Behaviour of AA7178/Nano Titanium Diboride Hybrid Composites Employing Taguchi Techniques

Chattoraj, Priyanka; Prabhakar, Parimala; Koti, Vishwanath; Natarajan, Suganya; Lakshminarayana, M.; Arul, K.; Venkatachalapathy, M. S.; Ahamed, Maqusood; Karnan, M.; Kumar, Suresh

doi:10.1155/2022/1619923

Cited by 14 publications

(3 citation statements)

References 23 publications

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“…The fabricated samples were polished with emery paper of different grades 600,800,1000, and 1500, using a disc polisher with a 1.5-micrometre diamond paste. Keller's reagent(Distilled water 190 ml, Nitric acid HNO 3 5 ml, Hydrochloric acid HCL 3 ml, Hydrofluoric acid HF 2 ml) [39] were used to etch the sample in order to reveal the grains and to eliminate the dirt from the surface. SEM (VEGA3 TESCAN) was used to analyze the nanocomposite's microstructure and type of wear.…”

Section: Characterizationmentioning

confidence: 99%

Optimization of tribological behaviour of TiO₂ nanoparticles reinforced AA7178 alloy matrix using ANN and Taguchi’s methodology

Bharat¹,

Bose²

2022

Surf. Topogr.: Metrol. Prop.

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The investigation of tribological behaviour of AA7178 base alloy matrix reinforced with varying weight percentage of nano TiO2 particles (0,1,2 and 3%) using artificial neural network (ANN) and Taguchi is presented in this paper. Scanning electron microscope(SEM) with Energy Dispersive Spectroscopy (EDAX) was used to study the microstructural as well as wear behaviour of the nanocomposite. The SEM image confirms that abrasive and adhesive wear was responsible for worn-out surface. ANN with Taguchi model was used to obtained the best values for input process parameters (sliding speed, distance, load and weight percentage) to minimize the output values (Coefficient of friction and wear rate). Coefficient of friction and wear rate was mainly affected by weight percentage of nano TiO2 by 60.95% and 57.33% respectively. The efficiency of ANN model was better compared to Taguchi model.

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Section: Characterizationmentioning

confidence: 99%

Optimization of tribological behaviour of TiO₂ nanoparticles reinforced AA7178 alloy matrix using ANN and Taguchi’s methodology

Bharat¹,

Bose²

2022

Surf. Topogr.: Metrol. Prop.

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“…This study [16] explored how varying nano-TiB 2 additions (2%, 4%, 6%) in stir-cast AA7178 affected its wear under different load, speed, and distance conditions. Nanoscale reinforcement effectively reduced friction and significantly improved wear resistance, suggesting promising potential for application in bearings and piston rings.…”

Section: Introductionmentioning

confidence: 99%

Wear performance of aluminium hybrid nanocomposites using Taguchi

Venkata Subbaiah,

2024

Eng. Res. Express

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This research explored AA 6351reinforced with varying amounts of nano silicon carbide (five wt%) and nanoZirconia powder (3to 9 in steps of three wt%) composites' wear performance using the powder metallurgy technique. Wear tests were conducted on the specimens in a dry, ambient environment utilizing a tribometer(pin-on-disc). The impact of three factors – Zirconia wt percentage, load, and sliding velocity - on the wear rate and friction coefficient was investigated. An experimental design based on the Taguchi-nine-level orthogonal array was employed, allowing for efficient analysis of parameter significance. Optimum conditions for minimum wear were identified through a main effect plot, indicating 9% wt reinforcement, 1.34m/s sliding velocity, and 10 N load. Sliding velocity emerged as the primary determinant of wear- rate in the ANOVA analysis, followed by the contributions of reinforcement and load. Optimization for the lowest friction coefficient, again via the main effect plot, pointed to 9% wt reinforcement, 30 N load, and 0.84m/s sliding velocity. ANOVA showed that reinforcement strongly influenced friction, with sliding velocity and load playing more minor roles.This investigation identified the optimal conditions for producing AA 6351 composites with minimal wear and friction using the powder metallurgy method and varying amounts of nano silicon carbide and nano zirconia powder.

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“…Te most urgent issues to be addressed include clustering, minimal wettability of ZrSiO 4 nanoparticles with aluminum, and the development of numerous distinct phases at 450 °C, such as aluminum carbide (Al 4 C 3 ) or aluminum oxides [8][9][10]. Aluminum-ZrSiO 4 nanoparticles interfacial bond strength, ZrSiO 4 aspect ratio, and nano ZrSiO 4 quality all play a vital role in the mechanical characteristics of ZrSiO 4 -reinforced aluminum alloys [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Investigation on the Mechanical Properties of Powder Metallurgy-Manufactured AA7178/ZrSiO4 Nanocomposites

Srinivasan¹,

Karunakaran

Hariprabhu³

et al. 2023

Advances in Materials Science and Engineering

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The versatility of metal matrix composites (MMCs) makes them a promising material for various industrial applications. The current study used a ball milling to mechanically AA7178 powder and strengthened with zirconium silicate (ZrSiO4) nanoparticles. In addition, the AA7178 matrix was ball-milled to distribute the ZrSiO4 nanoparticles throughout the material. The AA7178 reinforced with ZrSiO4 nanoparticles was compacted and consolidated using two distinct powder metallurgy (PM) sequences: double pressing, double sintering, and hot pressing. In tests measuring microhardness, compression strength, and elongational break, the new nanocomposites surpassed the AA7178. The adequate interfacial bonding and even distribution of ZrSiO4 nanoparticles throughout the AA7178 matrix were essential to the strengthening mechanism. With the use of hot pressing, the mechanical characteristics of the nanocomposites were enhanced. As reinforcement concentration increased beyond 2.5% by weight, mechanical properties drastically degraded due to ZrSiO4 nanoparticles clumping and unequal distribution. Improved mechanical parts attain through the uniform distribution of ZrSiO4 nanoparticles in the AA7178 and the maintenance of their mechanical properties.

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Optimization on Tribological Behaviour of AA7178/Nano Titanium Diboride Hybrid Composites Employing Taguchi Techniques

Cited by 14 publications

References 23 publications

Optimization of tribological behaviour of TiO₂ nanoparticles reinforced AA7178 alloy matrix using ANN and Taguchi’s methodology

Optimization of tribological behaviour of TiO₂ nanoparticles reinforced AA7178 alloy matrix using ANN and Taguchi’s methodology

Wear performance of aluminium hybrid nanocomposites using Taguchi

Investigation on the Mechanical Properties of Powder Metallurgy-Manufactured AA7178/ZrSiO4 Nanocomposites

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Optimization on Tribological Behaviour of AA7178/Nano Titanium Diboride Hybrid Composites Employing Taguchi Techniques

Cited by 14 publications

References 23 publications

Optimization of tribological behaviour of TiO2 nanoparticles reinforced AA7178 alloy matrix using ANN and Taguchi’s methodology

Optimization of tribological behaviour of TiO2 nanoparticles reinforced AA7178 alloy matrix using ANN and Taguchi’s methodology

Wear performance of aluminium hybrid nanocomposites using Taguchi

Investigation on the Mechanical Properties of Powder Metallurgy-Manufactured AA7178/ZrSiO4 Nanocomposites

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Product

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Optimization of tribological behaviour of TiO₂ nanoparticles reinforced AA7178 alloy matrix using ANN and Taguchi’s methodology

Optimization of tribological behaviour of TiO₂ nanoparticles reinforced AA7178 alloy matrix using ANN and Taguchi’s methodology