Dry Sliding Wear Characteristics of SiC and Al2O3 Nanoparticulate Aluminium Matrix Composite Using Taguchi Technique

被引：0
作者：
Kiran Kumar Ekka
S. R. Chauhan
机构：
[1] National Institute of Technology,Department of Mechanical Engineering
来源：
Arabian Journal for Science and Engineering | 2015年 / 40卷
关键词：
Metal matrix nano-composites (MMNCs); Wear; Taguchi; Neural network;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper investigates the sliding wear behaviour of nanoparticle-filled aluminium matrix nano-composites (AMNCs). Two different nano-reinforcements undertaken for this study are SiC and Al2O3. The percentage reinforcement is also varied from 0.5 to 1.5 wt%. For investigating the wear behaviour, factors such as applied normal load, sliding speed and sliding distance are considered. Also Taguchi design of experimental technique is employed for the study and analysis of sliding wear. Findings showed that nano-SiC particulate-reinforced AMNCs show better wear resistance than nano-Al2O3-reinforced AMNCs. Also regression and artificial neural network are used to develop a model to predict the wear rate of these composites.
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页码：571 / 581
页数：10
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