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DC Field | Value | Language |
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dc.contributor.author | Chung, Haseung | - |
dc.contributor.author | Lee, Nanum | - |
dc.contributor.author | Ko, Jeonghan | - |
dc.contributor.author | Lee, Taebong | - |
dc.contributor.author | Lee, Pil Ho | - |
dc.contributor.author | Choi, Jin Young | - |
dc.date.issued | 2019-06-01 | - |
dc.identifier.uri | https://dspace.ajou.ac.kr/dev/handle/2018.oak/30735 | - |
dc.description.abstract | In functionally graded materials (FGM), material property gradually changes within a product. To manufacture FGM by additive manufacturing (AM) using polymer powders, precise deposition of different powder materials is crucial. The powder deposition, however, is challenging, because process control and material choices are complicated. This paper presents a newly developed laser-based AM system using the direct deposit of poly-lactic acid powders on the target surface. This direct-writing AM system can facilitate material change even within a layer for superior material property variation. This study characterizes the optimal process conditions for deposition consistency by statistical methods. This study also identifies suitable statistical models by examining the model characteristics such as lack-of-fit and curvature. In addition, this study finds an appropriate statistical method to handle process abnormality such as no powder flow. Through these analyses, this study characterizes the optimal combination of process conditions and material choices for stable powder deposition, and verifies the best conditions for the new AM system. This study will help develop a new AM system with the optimal deposition for each material composition to produce novel material structure for FGM. | - |
dc.description.sponsorship | Acknowledgements This work was supported in part by the US National Science Foundation (NSF) (CMMI #1331633), National Research Foundation of Korea (NRF) Grants funded by the Korea government (MSIP) (NRF-2017R1D1A1B03035703, NRF-2014R1A2A2A03006993, NRF-2014R1A1A2058955, NRF-2011-0011932), Hongik University and Ajou University Research Fund. | - |
dc.language.iso | eng | - |
dc.publisher | SpringerOpen | - |
dc.subject.mesh | Direct write | - |
dc.subject.mesh | Functionally graded material (FGM) | - |
dc.subject.mesh | Material compositions | - |
dc.subject.mesh | Novel materials | - |
dc.subject.mesh | Optimal combination | - |
dc.subject.mesh | Poly lactic acid | - |
dc.subject.mesh | Powder deposition | - |
dc.subject.mesh | Process condition | - |
dc.title | Optimal Powder Deposition Process to Develop a New Direct-Write Additive Manufacturing System | - |
dc.type | Article | - |
dc.citation.endPage | 1067 | - |
dc.citation.startPage | 1057 | - |
dc.citation.title | International Journal of Precision Engineering and Manufacturing | - |
dc.citation.volume | 20 | - |
dc.identifier.bibliographicCitation | International Journal of Precision Engineering and Manufacturing, Vol.20, pp.1057-1067 | - |
dc.identifier.doi | 10.1007/s12541-019-00129-6 | - |
dc.identifier.scopusid | 2-s2.0-85066461601 | - |
dc.identifier.url | http://www.springerlink.com/content/2234-7593/ | - |
dc.subject.keyword | Additive manufacturing | - |
dc.subject.keyword | Direct-write | - |
dc.subject.keyword | Functionally graded materials | - |
dc.subject.keyword | Powder deposition | - |
dc.subject.keyword | Process optimization | - |
dc.subject.keyword | Statistical analysis | - |
dc.description.isoa | false | - |
dc.subject.subarea | Mechanical Engineering | - |
dc.subject.subarea | Industrial and Manufacturing Engineering | - |
dc.subject.subarea | Electrical and Electronic Engineering | - |
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