A SHAPE REGISTRATION METHODOLOGY FOR GEOMETRIC DEVIATION CORRECTION IN ADDITIVE MANUFACTURING

To reach the potential of additive manufacturing (AM) for accurate fabrication of complex geometries, extensive work has been done on developing prescriptive models for reducing shape deviations from the intended design. The efficacy of such models relies on proper alignment between the fabricated product and its intended design. However, the most popular registration procedures are extremely sensitive to local shape deformation and global distortion of the final product. This leads to incorrect assessments of the shape deviation patterns and making improvement efforts futile. This paper presents a new shape registration method robust to distortions to facilitate the correction or compensation of shape deviation in AM. It sequentially constrains rigid transformation parameters to reveal the true deformation of the product. A statistical control chart is adopted to filter the measurement data, which is later registered to the corresponding design for deviation identification. Simulation and case studies show that the proposed methodology provides consistent geometric quality assessments in the presence of global distortion compared to the existing methods.