Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Tian, Wenmeng (Meg)
Committee Member
Morshedlou, Nazanin
Committee Member
Ma, Junfeng
Date of Degree
8-7-2020
Original embargo terms
Worldwide
Document Type
Graduate Thesis - Open Access
Major
Industrial Engineering
Degree Name
Master of Science
College
James Worth Bagley College of Engineering
Department
Department of Industrial and Systems Engineering
Abstract
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.
URI
https://hdl.handle.net/11668/18439
Recommended Citation
Noroozi Esfahani, Mehrnaz, "Advanced in-situ layer-wise quality control for laser-based additive manufacturing using image sequence analysis" (2020). Theses and Dissertations. 402.
https://scholarsjunction.msstate.edu/td/402