Online quality monitoring in material extrusion additive manufacturing processes based on laser scanning technology

This paper proposes an online quality monitoring system based on laser scanning technology for defect detection in material extrusion additive manufacturing processes. The proposed method, which is based on a combination of existing efficient algorithms, can detect and identify defects by comparing the surface point cloud obtained by laser scanning with the ideal surface extracted from the CAD model. In addition, a three-dimensional model of the identified defect can be reconstructed by the monitoring system for feedback control of the system. Experimental studies show that the proposed method not only effectively identifies overfill and underfill defects but also accurately reconstructs the three-dimensional model of both types of defects. These data are used for feedback control of 3D printers to determine whether the 3D printer should be eventually shut down to reduce material and time waste.