Dimensional Accuracy Evaluation of Single-Layer Prints in Direct Ink Writing Based on Machine Vision.

Area of Science:

• Additive Manufacturing
• Metrology
• Computer Vision

Background:

• Direct Ink Writing (DIW) technology implementation is limited by the lack of standardized dimensional accuracy evaluation methods.
• Precision non-contact assessment is crucial for advancing DIW fabrication processes.

Purpose of the Study:

• To develop a novel machine vision-based framework for precise, non-contact dimensional accuracy evaluation in DIW.
• To establish a quantitative quality control solution for DIW applications and support process optimization.

Main Methods:

• An optimized hardware configuration with integrated image processing algorithms was established.
• Camera calibration, advanced image preprocessing, and high-precision contour extraction were investigated.
• An iterative closest point (ICP) algorithm-enhanced evaluation system was developed.

Main Results:

• The machine vision system achieved 0.04 mm × 0.04 mm spatial resolution.
• An 80% improvement in measurement accuracy (0.001 mm) was demonstrated compared to conventional methods.
• At least 76.3% enhancement in printed layer dimensional accuracy was observed through process parameter optimization.

Conclusions:

• The proposed non-contact evaluation solution provides a robust framework for quantitative quality control in DIW.
• This method offers critical insights for process optimization and standardization in additive manufacturing.
• The developed system addresses the need for precision assessment in DIW fabrication.