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Summary
This summary is machine-generated.

This study introduces an AI-powered quality control (QC) framework for semi-solid extrusion three-dimensional printing (SSE-3DP). Integrating colorimetry and AI machine vision enhances defect detection and structural accuracy in printed materials.

Keywords:
3D printingArtificial intelligenceMachine visionPharmaceutical applicationsQuality controlSemi-solid extrusion

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Area of Science:

  • Additive Manufacturing
  • Materials Science
  • Artificial Intelligence

Background:

  • Semi-solid extrusion three-dimensional printing (SSE-3DP) is a versatile technology with broad industrial applications.
  • Standardized quality control (QC) strategies are lacking, hindering routine implementation of SSE-3DP.
  • Post-processing inspection is difficult due to variations in material, geometry, and optical properties.

Purpose of the Study:

  • To develop a systematic and scalable QC framework for SSE-printed patches.
  • To integrate colorimetric analysis with AI-assisted machine vision for enhanced quality assessment.
  • To improve the reproducibility and automation of QC in SSE-3DP.

Main Methods:

  • Utilized three hydrogel ink classes (starch, pectin, gelatin) for printing model patches.
  • Quantified color contrast using CIEDE2000 metric and validated with image analysis.
  • Employed AI tools (ChatGPT-5, Perplexity Pro) for color prediction, image segmentation, and geometric comparison (IoU).

Main Results:

  • Optimized color combinations improved edge detection, segmentation accuracy, and defect identification.
  • AI-assisted workflow accurately quantified infill accuracy and structural deviations without specialized hardware.
  • Successfully differentiated between well-printed and defective patches using the developed QC strategy.

Conclusions:

  • The developed perception-driven, AI-powered QC strategy enhances reproducibility in SSE-3DP.
  • Automated inspection and defect identification are enabled through this integrated approach.
  • This framework offers a practical pathway toward standardized quality assurance in SSE-3DP.