Mechanical and abrasive wear behavior of cenosphere filled carbon reinforced epoxy composites using Taguchi-Grey relational analysis. (15th October 2018)

• Record Type: Journal Article
• Authors: Vinu kumar, S M; Suresha, B; Rajamurugan, G; Megalingam, A
• Is Part Of: Materials research express. Volume 6:Number 1(2019)
• Publication Date: 2018-10-15
• Subjects: carbon epoxy -- cenosphere (CSP) -- Grey relational analysis -- optimization -- COF -- SWR -- ASTM; Materials science -- Research -- Periodicals; Materials science -- Periodicals; 620.11
• DOI: 10.1088/2053-1591/aae5dc
• Languages: English
• ISSNs: 2053-1591

Abstract

Abstract: Carbon fabric reinforced Epoxy (C-E) composites filled with different weight percentage of silane treated flyash cenosphere (CSP) particles were synthesized using hand layup process followed by compression moulding method. The fabricated samples were subjected to mechanical tests and two body multipass abrasive wear test (2BMAW) in accordance with American society for testing and materials (ASTM). Mechanical results showed addition of CSP particles in C-E composites tends to improve property such as density, hardness, flexural and impact strength. Meanwhile Taguchi method with Grey relational analysis (GRA) was implemented for 2BMAW test to optimize the wear process parameters with multi-response characteristics. Filler wt% (Filler content), Grit size of abrasive (emery paper), sliding distance (m) and Load (N) were selected as wear process parameters for which responses were coefficient of friction (COF), specific wear rate (SWR) and hardness (BH) of the composites. Analysis of variance (ANOVA) result based on grey relational grade (GRG) revealed that filler wt% (filler content) and sliding distance were found as most significant process parameter influencing the wear performance of the composites by 55% and 19% respectively followed by Grit size of emery paper and applied load. Finally microstructure analysis of the fractured and worn sample has been studied using scanning electron microscope to understand the mode of failure mechanism.