Dimensional Fidelity and Slicer Mass Prediction Bias in FFF-Printed UAV Micro-Frames: A Material-Dependent...

Objective: This study investigates the influence of selecting three thermoplastics as raw materials (PLA, PETG, and ABS) on dimensional accuracy, defect formation, and slicer-based mass prediction reliability in FFF 3D-printed UAV micro-frames. Methods: A factorial experimental design combining three materials, two micro-frame geometries, and two infill levels was implemented. Print quality was assessed through structured visual inspection of common FFF defects, while manufacturing reliability was evaluated by comparing slicer-predicted and experimentally measured mass. Dimensional fidelity was quantified at critical motor mount features using repeated micrometric measurements and dedicated accuracy and uniformity indices. Results: The results reveal strong material-dependent behaviour. PLA exhibited the highest dimensional consistency and near-zero mean mass prediction error, PETG showed intermediate performance, and ABS presented significant warping, together with a pronounced positive mass prediction bias. These findings indicate systematic discrepancies between predicted and measured mass values and highlight the need for material-dependent calibration of slicing software. Conclusions: Material selection and process calibration strongly affect dimensional fidelity and manufacturing reliability in FFF-printed UAV micro-frames. The findings provide practical guidance for material choice and slicing parameter adjustment in UAV fabrication and similar small-scale FFF applications.