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

Area of Science:

• Additive Manufacturing
• Materials Science
• Robotics

Background:

• Fused Filament Fabrication (FFF) is widely used for rapid prototyping and manufacturing.
• Unmanned Aerial Vehicle (UAV) components require high dimensional accuracy and reliability.
• Material selection in FFF influences part performance and manufacturing predictability.

Purpose of the Study:

• To evaluate the impact of different thermoplastics (PLA, PETG, ABS) on FFF 3D-printed UAV micro-frames.
• To assess dimensional accuracy, defect formation, and mass prediction reliability.
• To provide guidance for material selection and process calibration in UAV fabrication.

Main Methods:

• Factorial experimental design with three materials, two geometries, and two infill levels.
• Structured visual inspection for FFF defects.
• Micrometric measurements for dimensional fidelity at critical features.
• Comparison of slicer-predicted versus experimentally measured mass.

Main Results:

• Material choice strongly influences dimensional consistency and defect formation.
• PLA demonstrated superior dimensional accuracy and minimal mass prediction error.
• ABS exhibited significant warping and a positive mass prediction bias, necessitating calibration.
• PETG showed intermediate performance characteristics.

Conclusions:

• Material selection and slicing software calibration are critical for dimensional fidelity and manufacturing reliability in FFF-printed UAV micro-frames.
• Findings offer practical insights for optimizing material choice and slicing parameters in UAV and small-scale FFF applications.
• Material-dependent calibration of slicing software is essential for accurate mass prediction.