In-process measurement of the surface quality for a novel finishing process for polymer additive manufacturing
In the last decade, there has been considerable growth in the production of end-use polymer parts and components using additive manufacturing methods. A wide range of polymers, from Nylon-12 to thermoplastic polyurethane polymers, can be processed with complex geometry tailored to specific function....
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Published: |
Elsevier
2018
|
| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/52583/ |
| _version_ | 1848798760280260608 |
|---|---|
| author | Syam, Wahyudin P. Leach, Richard K. Rybalcenko, Konstantin Gaio, Andrȇ Crabtree, Joseph |
| author_facet | Syam, Wahyudin P. Leach, Richard K. Rybalcenko, Konstantin Gaio, Andrȇ Crabtree, Joseph |
| author_sort | Syam, Wahyudin P. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | In the last decade, there has been considerable growth in the production of end-use polymer parts and components using additive manufacturing methods. A wide range of polymers, from Nylon-12 to thermoplastic polyurethane polymers, can be processed with complex geometry tailored to specific function. However, due to the nature of the layer-by-layer process used in additive manufacturing, high roughness surfaces remain on the parts. To reduce the roughness of the surfaces, a proprietary post-processing method, developed by Additive Manufacturing Technologies, is applied to the surfaces. To monitor and control the finishing of the surfaces, an in-process surface detection instrument has been developed based on machine vision and machine learning. This paper presents the machine learning approach and the effectiveness of the instrument for in-process measurement of the finished surfaces. |
| first_indexed | 2025-11-14T20:24:53Z |
| format | Article |
| id | nottingham-52583 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:24:53Z |
| publishDate | 2018 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-525832020-05-04T19:33:45Z https://eprints.nottingham.ac.uk/52583/ In-process measurement of the surface quality for a novel finishing process for polymer additive manufacturing Syam, Wahyudin P. Leach, Richard K. Rybalcenko, Konstantin Gaio, Andrȇ Crabtree, Joseph In the last decade, there has been considerable growth in the production of end-use polymer parts and components using additive manufacturing methods. A wide range of polymers, from Nylon-12 to thermoplastic polyurethane polymers, can be processed with complex geometry tailored to specific function. However, due to the nature of the layer-by-layer process used in additive manufacturing, high roughness surfaces remain on the parts. To reduce the roughness of the surfaces, a proprietary post-processing method, developed by Additive Manufacturing Technologies, is applied to the surfaces. To monitor and control the finishing of the surfaces, an in-process surface detection instrument has been developed based on machine vision and machine learning. This paper presents the machine learning approach and the effectiveness of the instrument for in-process measurement of the finished surfaces. Elsevier 2018-09-03 Article PeerReviewed Syam, Wahyudin P., Leach, Richard K., Rybalcenko, Konstantin, Gaio, Andrȇ and Crabtree, Joseph (2018) In-process measurement of the surface quality for a novel finishing process for polymer additive manufacturing. Procedia CIRP, 75 . pp. 108-113. ISSN 2212-8271 In-process measurement; Additive manufacturing; Machine learning; Machine vision https://www.sciencedirect.com/science/article/pii/S221282711830605X doi:10.1016/j.procir.2018.04.088 doi:10.1016/j.procir.2018.04.088 |
| spellingShingle | In-process measurement; Additive manufacturing; Machine learning; Machine vision Syam, Wahyudin P. Leach, Richard K. Rybalcenko, Konstantin Gaio, Andrȇ Crabtree, Joseph In-process measurement of the surface quality for a novel finishing process for polymer additive manufacturing |
| title | In-process measurement of the surface quality for a novel finishing process for polymer additive manufacturing |
| title_full | In-process measurement of the surface quality for a novel finishing process for polymer additive manufacturing |
| title_fullStr | In-process measurement of the surface quality for a novel finishing process for polymer additive manufacturing |
| title_full_unstemmed | In-process measurement of the surface quality for a novel finishing process for polymer additive manufacturing |
| title_short | In-process measurement of the surface quality for a novel finishing process for polymer additive manufacturing |
| title_sort | in-process measurement of the surface quality for a novel finishing process for polymer additive manufacturing |
| topic | In-process measurement; Additive manufacturing; Machine learning; Machine vision |
| url | https://eprints.nottingham.ac.uk/52583/ https://eprints.nottingham.ac.uk/52583/ https://eprints.nottingham.ac.uk/52583/ |