Extruder Path Analysis in Fused Deposition Modeling Using Thermal Imaging.

Area of Science:

• Additive Manufacturing
• Materials Science
• Quality Control

Background:

• Fused Deposition Modeling (FDM) is a popular 3D printing method, but maintaining consistent quality and reliability is difficult.
• Accurate control of extruder head trajectories and speeds is crucial for high-quality FDM prints.

Purpose of the Study:

• To develop and validate a novel methodology for evaluating the fidelity of programmed FDM printing parameters against executed ones.
• To assess the potential of infrared thermography for in situ quality control in FDM processes.

Main Methods:

• The study integrated long-wave infrared (LWIR) thermography and image processing techniques.
• A polylactic acid (PLA) specimen was printed using FDM, with G-code data compared against kinematic variables from thermal imaging.
• The methodology focused on analyzing deviations in nozzle movement and layer deposition accuracy.

Main Results:

• The developed approach successfully detected deviations between programmed and executed extruder head trajectories and speeds.
• Thermal image analysis provided insights into layer deposition accuracy, indicating potential defect formation.
• The non-invasive monitoring method demonstrated its capability for in situ quality control.

Conclusions:

• The thermal imaging-based methodology offers a reliable tool for monitoring FDM processes and ensuring product quality.
• This approach can serve as an early indicator of defects, supporting process optimization in additive manufacturing.
• The findings advance smart sensing strategies for industrial additive manufacturing workflows.