There are no files associated with this item.
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.citation.endPage | 775 | - |
dc.citation.number | 6 | - |
dc.citation.startPage | 767 | - |
dc.citation.title | SMART STRUCTURES AND SYSTEMS | - |
dc.citation.volume | 29 | - |
dc.contributor.author | Lee, Jungeon | - |
dc.contributor.author | Baek, Adrian M. Chung | - |
dc.contributor.author | Kim, Namhun | - |
dc.contributor.author | Kwon, Daeil | - |
dc.date.accessioned | 2023-12-21T14:08:00Z | - |
dc.date.available | 2023-12-21T14:08:00Z | - |
dc.date.created | 2022-07-12 | - |
dc.date.issued | 2022-06 | - |
dc.description.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. | - |
dc.identifier.bibliographicCitation | SMART STRUCTURES AND SYSTEMS, v.29, no.6, pp.767 - 775 | - |
dc.identifier.doi | 10.12989/sss.2022.29.6.767 | - |
dc.identifier.issn | 1738-1584 | - |
dc.identifier.scopusid | 2-s2.0-85168903341 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/58851 | - |
dc.identifier.wosid | 000817083900002 | - |
dc.language | 영어 | - |
dc.publisher | TECHNO-PRESS | - |
dc.title | In situ monitoring-based feature extraction for metal additive manufacturing products warpage prediction | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.relation.journalWebOfScienceCategory | Engineering, Civil; Engineering, Mechanical; Instruments & Instrumentation | - |
dc.relation.journalResearchArea | Engineering; Instruments & Instrumentation | - |
dc.type.docType | Article | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | experimental validation | - |
dc.subject.keywordAuthor | feature extraction | - |
dc.subject.keywordAuthor | in situ monitoring | - |
dc.subject.keywordAuthor | metal additive manufacturing | - |
dc.subject.keywordAuthor | warpage prediction | - |
dc.subject.keywordPlus | TEMPERATURE DISTRIBUTION | - |
dc.subject.keywordPlus | RESIDUAL-STRESS | - |
dc.subject.keywordPlus | LASER | - |
Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Tel : 052-217-1404 / Email : scholarworks@unist.ac.kr
Copyright (c) 2023 by UNIST LIBRARY. All rights reserved.
ScholarWorks@UNIST was established as an OAK Project for the National Library of Korea.