Evaluating the effects of pineapple fiber, potato waste filler, surface treatment, and fiber length on the mechanical properties of polyethylene composites for biomedical applications

This study investigates the development of a biocompatible polyethylene composite incorporating natural fiber (pineapple fiber) and potato waste filler for potential use in biomedical applications. The composite was fabricated using compression molding and optimized through Taguchi-based grey relational analysis (GRA), TOPSIS, and artificial neural network (ANN) prediction models. The hybrid combination of these materials has been minimally explored in the biomedical field. Fourier Transform Infrared (FTIR) analysis of the potato filler revealed a peak at 1336 cm⁻ 1 , indicating asymmetric deformation of C-H and C-O functional groups, contributing to enhanced compatibility with the polyethylene matrix. The natural fiber showed uniform distribution, improving stress transfer and flexural properties. The ANN model demonstrated high accuracy, with an r-value of 0.9972. Multi-response optimization identified the best configuration as 3 % NaOH treatment, 3 wt% potato filler, 30 wt% natural fiber, and a fiber length of 1.5 cm, yielding a tensile strength of 22.3 MPa, flexural strength of 23.8 MPa, and impact strength of 18.3 kJ/m 2 . This fabricated composites were lightweight and biocompatible materials, suitable for biomedical applications. • Optimization showed better results at treatment, filler (3 wt %)/30 wt % fiber and 1.5 cm fiber length. • The ANN model performs well in all stages, with remarkable overall r value of 0.9972. • The final combination results from GRA and TOPSIS gained better mechanical properties than all other Taguchi results.