Working Paper Article Version 1 This version is not peer-reviewed

In-Situ Layer-Wise Quality Monitoring for Laser-Based Additive Manufacturing Using Image Series Analysis

Version 1 : Received: 27 January 2021 / Approved: 29 January 2021 / Online: 29 January 2021 (11:59:58 CET)

How to cite: Esfahani, M.; Bian, L.; Tian, W. In-Situ Layer-Wise Quality Monitoring for Laser-Based Additive Manufacturing Using Image Series Analysis. Preprints 2021, 2021010615 Esfahani, M.; Bian, L.; Tian, W. In-Situ Layer-Wise Quality Monitoring for Laser-Based Additive Manufacturing Using Image Series Analysis. Preprints 2021, 2021010615

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.

Subject Areas

Additive Manufacturing; 3D printing

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