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            Chapter Real-Time Geometry Assessment Using Laser Line Scanner During Laser Powder Directed Energy Deposition Additive Manufacturing of SS316L Component with Sharp Feature

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            Author(s)
            Liu, Peipei
            Yang, Liu
            Wang, Boyu
            Cheng, Jack C. P.
            Sohn, Hoon
            Language
            English
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            Abstract
            Directed energy deposition (DED) is a major metal additive manufacturing (AM) technology that is increasingly used in many industries due to its ability to manufacture complex components of arbitrary shapes and sizes. However, a lack of timely geometry assessment and the consequent geometry control hinders the development of DED towards zero defect manufacturing. In this study, a real-time geometry assessment methodology is developed for laser pow-der directed energy deposition (LP-DED). A geometry assessment system is developed using a laser line scanner capable of inspecting the melt pool area, the just solidified area, as well as layer-wise inspection. An image processing method with an encoder-decoder based profile completion network was developed to obtain accurate track profile in images from real-time inspection. Experiments have been conducted to validate the proposed methodology by depositing multi-layer X-shape objects
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/191083
            Keywords
            Additive Manufacturing; Directed energy deposition; Real-time geometry assessment; Laser line scanning; thema EDItEUR::U Computing and Information Technology
            DOI
            10.36253/979-12-215-0289-3.97
            ISBN
            9791221502893
            Publisher
            Firenze University Press
            Publisher website
            www.fupress.com/
            Publication date and place
            Florence, 2023
            Series
            Proceedings e report,
            Pages
            12
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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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