Experimental investigation and multi-objective optimization of multiple mechanical characteristics for chemically treated kenaf fibre reinforced epoxy composite using grey fuzzy logic

Abstract

In the present work, chemically treated kenaf fibre (10, 20 and 30 wt. %) reinforced epoxy resin composite formulations were fabricated using hand lay-up technique. The prepared composites were mechanically characterized using Taguchi L27 experimental design to examine the influence of varying kenaf fibre wt. %, NaOH concentration % for chemical treatment, and fibre immersion duration. The grey-fuzzy optimization approach was utilized for optimizing prepared formulations mechanical properties such as tensile strength, impact strength and flexural strength. Further, analysis of variance (ANOVA) tests and response graphs were utilized for delivering model significance and determining the percentage contribution of input variables. The NaOH concentration % was found to be most significant parameter followed by kenaf wt. % in providing best mechanical properties of chemically treated kenaf fibre reinforced epoxy composites.

Experimental analysis with grey relational analysis–analytic hierarchy process‐based hybrid optimization to analyze the effect of graphene nanoparticle reinforced ultra‐high molecular weight polyethylene/n‐HAp for hip joint

“…Optimization procedures based on experiments (DoE) design are efficient and use minimal data to estimate the best input values. [ 33 ] Grey relational analysis (GRA) is a multi‐objective optimization (MOO) tool that is widely used in the manufacturing sector. GRA's performance is heavily influenced by the weights provided to the input parameters.…”