Selection And Optimization Of Kenaf/Epoxy Composite As An Alternative Friction Material

• Main Author: Mustafa, Ashafi'e
• Format: Thesis
• Language: English; English
• Published: 2017
• Subjects: T Technology (General); TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utem.edu.my/id/eprint/20712/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=106145

This research consists of the selection and optimization of the alternate materials which represent asbestos, using the Cambridge Engineering Selector (CES). The design and selection of potential materials are according to the friction material‟s suggested specifications and performances. Comparative and verification studies were performed using the Pugh and Weighted Decision Matrix (WDM) methods in order to select the best material to represent asbestos from among all potential materials such as jute, ramie and kenaf. As for the result, kenaf (Hibiscus Cannabinus) was chosen as the best material that meets the criteria and design constrains. The tribological performances of the kenaf epoxy (KE) composite were conducted according to the L18 arrays design. A 10 mm diameter cylindrical pin of KE composite was fabricated using a hot-cold compression machine and tested on a pin-on-disk tribometer according to ASTM G99. The signal to noise (S/ N), analysis of variance (ANOVA) and correlation between factors were employed in order to determine the optimal combination between controlled factors and levels. The optimal combination parameters of the KE composite were verified upon the confirmation test, and then compared with conventional friction material. The confirmation test verified that an optimized KE composite result falls within confidence intervals of 95%; which sounds promising to be included in friction material formulations which also exhibit friction coefficient (0.4 - 0.44) within the range suggested. The predominant wear mechanisms from worn surfaces are studied using Scanning Electron Microscopy (SEM) images revealed signs of predominant wear mechanisms such as abrasive, adhesive and fatigue mechanisms and a profilometer to measure the surface roughness.