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|Title:||Identification and evaluation of defects in selective laser melted 316L stainless steel parts via in-situ monitoring and micro computed tomography||Authors:||Lu, Qingyang
Nguyen, Nhat V.
Hum, Allen Jun Wee
Wong, Chee How
|Keywords:||Engineering::Mechanical engineering||Issue Date:||2020||Source:||Lu, Q., Nguyen, N. V., Hum, A. J. W., Tran, T., & Wong, C. H. (2020). Identification and evaluation of defects in selective laser melted 316L stainless steel parts via in-situ monitoring and micro computed tomography. Additive Manufacturing, 35, 101287-. doi:10.1016/j.addma.2020.101287||Journal:||Additive Manufacturing||Abstract:||Additive manufacturing has opened doors for the efficient fabrication of individually tailored and complicated functional parts. However, the three-dimensional (3D) printing process is vulnerable to defects generation, necessitating the need for in-situ monitoring and control technologies for quality assessment of parts. An in-situ monitoring system (IMS) based on optical imaging was developed in-house for implementation on the selective laser melting process. A digital single lens reflex camera, mirror and several sets of light emitting diode strip lights formed the main constituents of the IMS. Cylindrical samples of 316L stainless steel were printed with variations in their energy density. Features taken in optical images were extracted and evaluated via image processing. Micro computed tomography (CT), which is capable of assessing the internal defects and recovering the 3D representation of a structure, was used as a validation method to correlate the features identified in the optical images. Results have shown that features captured in-situ were correlated to defects detected by micro CT, revealing the potential of using optical images captured during printing as an indicator to the extent of defects present in selective laser melted parts.||URI:||https://hdl.handle.net/10356/143850||ISSN:||2214-8604||DOI:||10.1016/j.addma.2020.101287||Schools:||School of Mechanical and Aerospace Engineering||Research Centres:||Singapore Centre for 3D Printing||Rights:||© 2020 Elsevier B.V. All rights reserved. This paper was published in Additive Manufacturing and is made available with permission of Elsevier B.V.||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SC3DP Journal Articles|
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