The effects of printing parameters on shape transformation capability of 3D printed structures of smart material

This study investigates the effects of 3D printing parameters on the shape transformation capabilities of structures fabricated from a composite of 80% PCTG, PET, PTMG, and 20% additives with shape memory properties. Different values of printing speed, infill density, and water temperature after printing have significant effects on the structures of PCTG-based with SMPs that influence the shape memory behaviour. In order to improve the effectiveness and precision of shape recovery under heat stimuli, the research uses the shape memory polymer (SMP) principle to optimize three important parameters, which are printing speed, infill density, and water temperature after printing. Samples were created using fused deposition modeling (FDM) technology across 27 experiments, and their recovery functionality time and thermal responsiveness were then assessed. The project employs Taguchi analysis to analyse the results by using ANOVA method. The results showed that the most important factor influencing shape recovery was the water temperature after printing, which was followed by printing speed and infill density. While lower infill densities improved flexibility and shortened recovery time, higher temperatures led to faster recovery. On the other hand, slower printing speeds lengthened the print time but enhanced interlayer stability and adhesion. A printing speed of 40 mm/s, an infill density of 30%, and a post-printing water temperature of 100°C were found to be the optimal parameter combination, resulting in the quickest recovery time of 7.27 seconds. This study provides important insights for developing 4D printing technologies by highlighting the crucial interaction between printing parameters and external factors in determining the performance of 3Dprinted SMP structures. This study fills in gaps in the literature, laying the groundwork for the reliable design and production of smart materials with revolutionary potential