Global and local defect detection for 3D printout surface based on geometric shape comparison

A 3D printer produces parts from CAD models. The printout must be checked for defects. We present a surface defect detection algorithm that constructs a 3D mesh of the printout by multi-view scanning and compares it to the part CAD model. It computes and displays the distance from each vertex of the...

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Bibliographic Details
Published inPrecision engineering Vol. 82; pp. 324 - 337
Main Authors Ye, Byounghun, Kim, Ku-Jin, Sacks, Elisha P.
Format Journal Article
LanguageEnglish
Published Elsevier Inc 01.07.2023
Subjects
Additive manufacturing
Curvature
Point-to-mesh distance
Shape comparison
Surface defect
Surface roughness
Point-to-mesh distance
Shape comparison
Surface roughness
Additive manufacturing
Surface defect
Curvature
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Summary:A 3D printer produces parts from CAD models. The printout must be checked for defects. We present a surface defect detection algorithm that constructs a 3D mesh of the printout by multi-view scanning and compares it to the part CAD model. It computes and displays the distance from each vertex of the printout mesh to the closest point on the part model. These distances comprise the global deviation of the printout from the model. When the error is within a threshold, the algorithm compares the curvature at each printout vertex to that at the closest part point. Qualitative differences in curvature indicate local defects, such as blobs, cracks, surface roughness, and faded embossing and engraving. The results are grouped into local defect regions that are displayed. We demonstrate the algorithm on metal printing and on PLA 3D printing.
ISSN:0141-6359
1873-2372
DOI:10.1016/j.precisioneng.2023.04.005