Abstract

Co-continuous composites have potential in friction and braking applications due to their unique tribological characteristics. The present study involves Taguchi grey relational analysis-based optimization of wear parameters such as applied load, sliding speed and sliding distance, and their effect on dry sliding wear performance of AA6063/SiC co-continuous composite manufactured by gravity infiltration. A Taguchi L9 orthogonal array was designed and nine experimental runs were performed based on the designed experiments. The coefficient of wear and specific wear rate were recorded for each experiment. Based on the average responses computed from Taguchi grey relational analysis, an applied load of 60 N, sliding speed of 1 m/s and sliding distance of 1000 m were estimated to be the optimal parameters. An Analysis of Variance (ANOVA) was conducted to identify the predominant factor and established all the three factors as being significant. The sliding distance was found to have the highest significant influence of 61.05% on the wear of the C4 composite. Confirmation experiments conducted using the optimal parameters indicated an improvement of 35.25% in grey relational grade. Analysis of the worn surfaces of the confirmation experiment revealed adhesive and abrasive wear as the governing mechanisms.

Details

Title
Taguchi Grey Relational Analysis for Multi-Response Optimization of Wear in Co-Continuous Composite
Author
Sylajakumari, Prasanth Achuthamenon 1   VIAFID ORCID Logo  ; Ramakrishnasamy, Ramesh 2   VIAFID ORCID Logo  ; Gopalakrishnan Palaniappan 3 

 Department of Mechanical Engineering, PSG College of Technology, Coimbatore 641004, India 
 Department of Mechanical Engineering, PSG Institute of Technology and Applied Research, Coimbatore641062, India 
 Department of Metallurgical Engineering, PSG College of Technology, Coimbatore 641004, India 
First page
1743
Publication year
2018
Publication date
2018
Publisher
MDPI AG
e-ISSN
19961944
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2607322266
Copyright
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.