Quality assurance has been one of the major challenges in laser-based additive manufacturing
(AM) processes. This study proposes a novel process modeling methodology for layer-wise in-situ
quality monitoring based on image series analysis. An image-based autoregressive (AR) model
has been proposed based on the image registration function between consecutively observed
thermal images. Image registration is used to extract melt pool location and orientation change
between consecutive images, which contains sensing stability information. Subsequently, a
Gaussian process model is used to characterize the spatial correlation within the error matrix.
Finally, the extracted features from the aforementioned processes are jointly used for layer-wise
quality monitoring. A case study of a thin wall fabrication by a Directed Laser Deposition (DLD)
process is used to demonstrate the effectiveness of the proposed methodology.Mechanical Engineerin
