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Smart Structures and Systems Volume 29, Number 6, June 2022 , pages 767-775 DOI: https://doi.org/10.12989/sss.2022.29.6.767 |
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In situ monitoring-based feature extraction for metal additive manufacturing products warpage prediction |
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Jungeon Lee, Adrian M. Chung Baek, Namhun Kim and Daeil Kwon
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| Abstract | ||
| Metal additive manufacturing (AM), also known as metal three-dimensional (3D) printing, produces 3D metal products by repeatedly adding and solidifying metal materials layer by layer. During the metal AM process, products experience repeated local melting and cooling using a laser or electron beam, resulting in product defects, such as warpage, cracks, and internal pores. Such defects adversely affect the final product. This paper proposes the in situ monitoring-based warpage prediction of metal AM products with experimental feature extraction. The temperature profile of the metal AM substrate during the process was experimentally collected. Time-domain features were extracted from the temperature profile, and their relationships to the warpage mechanism were investigated. The standard deviation showed a significant linear correlation with warpage. The findings from this study are expected to contribute to optimizing process parameters for metal AM warpage reduction. | ||
| Key Words | ||
| experimental validation; feature extraction; in situ monitoring; metal additive manufacturing; warpage prediction | ||
| Address | ||
| Jungeon Lee, Daeil Kwon: Department of Industrial Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea Adrian M. Chung Baek, Namhun Kim: Department of Mechanical Engineering, Ulsan National Institute of Science and Technology, 50, UNIST-gil, Eonyang-eup, Ulsan 44919, Republic of Korea | ||