Empowering Sustainability with Statistical Modelling of FDM-Printed Bamboo-Based Green Composites

Additive manufacturing (AM) is currently widely utilized across various industries due to its advanced capabilities compared to traditional manufacturing techniques. Among the many AM technologies, fused deposition modelling (FDM) stands out as one of the most economical methods, especially for small-scale vendors. FDM employs materials such as metals, ceramics, and polymers as feedstock. Among these, polymers are particularly suitable for small-scale applications and industrial use due to their cost-effectiveness and ease of processing. However, polymers inherently possess poor mechanical and thermal properties. This chapter presents a statistical analysis of FDM process parameters for printing polylactic acid (PLA) polymer reinforced with bamboo fibre as the feedstock material. The experiments were designed using an L 9 orthogonal array, considering FDM parameters such as infill density (ID), layer thickness (LT), nozzle temperature (NT), and fibre loading (FL) as input variables. The ultimate tensile strength (UTS) and Young’s modulus (E) of the printed samples were considered as response parameters. An analysis of variance was conducted to evaluate the statistical significance of the process parameters. The results revealed that the optimal parameter settings for achieving the highest UTS are ID of 80%, NT of 195°C, LT of 0.3 mm, and FL of 9 wt%. For maximizing Young’s modulus, the optimal settings are LT of 0.2 mm, ID of 80%, NT of 200°C, and FL of 6 wt%. The PLA-bamboo composite feedstock exhibited enhanced mechanical properties at these optimal FDM parameters, indicating its potential as a novel and effective material for FDM applications.