Optimizing various parameters influencing mechanical properties of banana/coir natural fiber composites using grey relational analysis and artificial neural network models

The natural fibers of banana and coir from southern part of India was taken as the reinforcement material. Taguchi-based grey relational analysis was used for optimizing the factors influencing tensile, flexural and impact strength of banana/coir composites. Banana wt%, coir wt%, alkali treatment %, pressure and temperature during compression moulding process were the five major factors used for optimizing the mechanical strengths of epoxy-based composites. Grey relational analysis observed 20% banana/15% coir/3% alkali treatment/16 MPa pressure and 100°C temperature combination having the maximum mechanical properties in 16 trial combinations. The signal-to-noise ratio table of grey relational analysis showed combination with 20% banana /15% coir/5% alkali treatment/16 MPa pressure and 100°C temperature having optimized mechanical properties. Banana has the highest rank in improving the mechanical strength of natural composites, followed by coir, alkali treatment %, pressure and temperature. The graph between actual and artificial neural network computed results observed high correlation, proving that network topology of 5-3-1 with five factors, three hidden nodes and one response is the best method for analyzing the parameters in mechanical strength. Hybrid fiber composites with NaOH treatment showed hackles in interface with improved interfacial bonding during SEM analysis.