Prediction and optimization of mechanical properties of particles filled coir-polyester composites using ANN and RSM algorithms

Abstract

81-86Mechanical properties of coir-polyester composites filled with aluminium oxide and calcium carbonate particles have been evaluated. As the mechanical properties of coir-polyester composites mainly depend upon the fibre length, fibre diameter and filler content, the present study deals with the prediction of mechanical properties using artificial neural network and determination of optimum fibre parameters using response surface methodology algorithms. The particles filled coir-polyester composites exhibit better values of tensile strength, flexural strength, impact strength and abrasion loss properties of 21.39 MPa, 79 MPa, 37.28 kJ/m2 and 570 mm3 for 42.41 mm fibre length, 0.25mm fibre diameter and 2.5% filler content respectively