The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Statistical Modeling and Analysis of Dry Sliding Wear of SiC Reinforced Aluminum MMCs
|
|
Author(s): S. Rajesh (Department of Mechanical Engineering, S.R.K.R. Engineering College, Bhimavaram, Andhra Pradesh, India), A. Gopala Krishna (Department of Mechanical Engineering, University College of Engineering, JNTUK, Kakinada, Andhra Pradesh, India), P. Rama Murthy Raju (Department of Mechanical Engineering, S.R.K.R. Engineering College, Bhimavaram, Andhra Pradesh, India)and M. Duraiselvam (Department of Production Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India)
Copyright: 2013
Volume: 1
Issue: 1
Pages: 14
Source title:
International Journal of Surface Engineering and Interdisciplinary Materials Science (IJSEIMS)
Editor(s)-in-Chief: J. Paulo Davim (University of Aveiro, Portugal)
DOI: 10.4018/ijseims.2013010105
Purchase
|
Abstract
The dry sliding wear behavior of SiC reinforced aluminum alloy composites produced by liquid metallurgy was studied by means of a pin-on-disc type wear set up. Dry sliding wear tests were carried out on SiC reinforced Metal Matrix Composites (MMCs) and its matrix alloy sliding against a steel counterface. Different contact stresses, reinforcement percentages, sliding distances and sliding velocities were selected as control factors and the response selected was Wear Volume Loss (Y1) and Coefficient of Friction (Y2) to evaluate the dry sliding performance. An L25 orthogonal array was employed for the experimental design. Initially empirical relations were deduced for Y1 and Y2 in terms of control factors. Further, the optimal combination of the testing parameters was determined for Y1 and Y2 responses by implementing Taguchi method for the experimental observations. Finally, Analysis of Variance (ANOVA) was performed to know the impact of individual factors on Y1 and Y2. The results indicated that the sliding distance for Y1 and Y2 responses is found to be the most effective factor among the other control parameters on dry sliding wear. The study also shows that the Taguchi method is applicable to solve this type of problem with minimum number of trials compared with a full factorial design.
Related Content
|
Meng-Ting Chiang, Pei-Ing Lee, Ang-Ying Lin, Tung-Han Chuang.
© 2024.
11 pages.
|
|
.
© 2024.
|
|
Jean Claude Mallia, Anthea Agius Anastasi, Sophie Marie Briffa.
© 2023.
20 pages.
|
|
Manik Barman, Tapan Kumar Barman, Prasanta Sahoo.
© 2022.
26 pages.
|
|
Vinod Kumar V. Meti, G. U. Raju, I. G. Siddhalingeshwar, Vinayak Neelakanth Gaitonde.
© 2022.
13 pages.
|
|
Sandeep Kumar Khatkar, Rajeev Verma, Suman Kant, Narendra Mohan Suri.
© 2022.
19 pages.
|
|
Basant Lal, Abhijit Dey, Mohamamd Farooq Wani.
© 2022.
12 pages.
|
|
|