Automated Qualification of 3D-Printed Products for Personalized Manufacturing

Product qualification is typically performed by specifying features or regions of interest (ROIs) during design, conducting shape registration of the inspected product to establish correspondence with its design counterpart, and measuring discrepancies for compliance assessment. However, qualification of complex freeform products often requires human intervention to ensure accuracy, particularly in personalized manufacturing through 3D printing. Geometric variety and complexity can induce operator-to-operator variability due to heterogeneous spatial distributions of geometric distortions. To enable automated product qualification, we propose to identify and represent ROIs as surface patches using geometric descriptors indicative of their intrinsic deviation patterns. ROI specification via shape space dimension reduction, non-rigid intrinsic shape registration, and intrinsic deviation representation can therefore be conducted for product qualification. Finite types of ROIs or surface patches can be extracted based on their intrinsic deviation patterns, independent of covariates such as size and location. A MATLAB software suite has been developed to implement the entire process, demonstrating its effectiveness in the qualification of complex dental models.