Identification and evaluation of defects in selective laser melted 316L stainless steel parts via in-situ monitoring and micro computed tomography
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 qualit...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2020
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| Online Access: | https://hdl.handle.net/10356/143850 |
| _version_ | 1811689108048707584 |
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| author | Lu, Qingyang Nguyen, Nhat V. Hum, Allen Jun Wee Tran, Tuan Wong, Chee How |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Lu, Qingyang Nguyen, Nhat V. Hum, Allen Jun Wee Tran, Tuan Wong, Chee How |
| author_sort | Lu, Qingyang |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T05:42:51Z |
| format | Journal Article |
| id | ntu-10356/143850 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:42:51Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ntu-10356/1438502021-01-27T08:29:47Z Identification and evaluation of defects in selective laser melted 316L stainless steel parts via in-situ monitoring and micro computed tomography Lu, Qingyang Nguyen, Nhat V. Hum, Allen Jun Wee Tran, Tuan Wong, Chee How School of Mechanical and Aerospace Engineering Singapore Centre for 3D Printing Engineering::Mechanical engineering Additive Manufacturing Powder Bed Fusion 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. National Research Foundation (NRF) Accepted version This work was supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme. 2020-09-28T02:07:40Z 2020-09-28T02:07:40Z 2020 Journal Article 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 2214-8604 https://hdl.handle.net/10356/143850 10.1016/j.addma.2020.101287 35 101287 en Additive Manufacturing © 2020 Elsevier B.V. All rights reserved. This paper was published in Additive Manufacturing and is made available with permission of Elsevier B.V. application/pdf |
| spellingShingle | Engineering::Mechanical engineering Additive Manufacturing Powder Bed Fusion Lu, Qingyang Nguyen, Nhat V. Hum, Allen Jun Wee Tran, Tuan Wong, Chee How Identification and evaluation of defects in selective laser melted 316L stainless steel parts via in-situ monitoring and micro computed tomography |
| title | Identification and evaluation of defects in selective laser melted 316L stainless steel parts via in-situ monitoring and micro computed tomography |
| title_full | Identification and evaluation of defects in selective laser melted 316L stainless steel parts via in-situ monitoring and micro computed tomography |
| title_fullStr | Identification and evaluation of defects in selective laser melted 316L stainless steel parts via in-situ monitoring and micro computed tomography |
| title_full_unstemmed | Identification and evaluation of defects in selective laser melted 316L stainless steel parts via in-situ monitoring and micro computed tomography |
| title_short | Identification and evaluation of defects in selective laser melted 316L stainless steel parts via in-situ monitoring and micro computed tomography |
| title_sort | identification and evaluation of defects in selective laser melted 316l stainless steel parts via in situ monitoring and micro computed tomography |
| topic | Engineering::Mechanical engineering Additive Manufacturing Powder Bed Fusion |
| url | https://hdl.handle.net/10356/143850 |
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