Tribological behavior on stir casted metal matrix composites of Al 6070 and TiC reinforcement with Taguchi S/N ratios

被引：0

作者：

Sivakumar V.R. ^{[1
]}

Kavitha V. ^{[1
]}

Sri Saravanan N. ^{[1
]}

Nanjundamoorthi T.T. ^{[1
]}

Chanakyan C. ^{[1
]}

机构：

[1] Department of Mechanical Engneering, R.V.S. College of Engineering and Technology, Kannampalayam, Tamilnadu, Coimbatore

来源：

Materials Today: Proceedings | 2023年 / 77卷

关键词：

Artificial neural network; Nanoparticle; Regression analysis; Scanning electron microscopy;

D O I：

10.1016/j.matpr.2022.11.222

中图分类号：

学科分类号：

摘要：

Al 6070 alloy is used in various heavy-duty applications like pipelines and welding structures. The wear resistance of the Al 6070 alloy should be enhanced for the enhancement of the lifetime in the application. Due to uniform dispersion, research shows that adding nanoparticles as an alloying element increases the strength and properties. Hence in this research, Al 6070 alloy is reinforced with 2%, 4% and 6% TiC. The signal-to-noise ratio analysis is done to optimise the experimental outcome. The interaction analysis in this research finds that the increase in the percentage of nanoparticles reduces the wear rate. The same result is confirmed with scanning electron microscopy images, which identify the higher rate of wear at 2% and lesser at 6%. The regression model is developed to predict the output responses, and the regression equation predicts the output with an accuracy of 93 %. Also, Artificial Neural Network (ANN) model is developed to predict the responses. The model finds the outcome with an accuracy of 99.99%. © 2022

引用

页码：455 / 461

页数：6

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