High-Speed Alumina Stereolithography
The additive manufacturing of ceramics offers a reliable and repeatable method for fabricating parts with complex geometries. To compete with conventional ceramic forming methods, the time and cost associated with material and process optimization for ceramic stereolithography should be improved. Co...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-09-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/12/19/9760 |
| _version_ | 1797480656768335872 |
|---|---|
| author | Fiona Spirrett Tatsuya Ito Soshu Kirihara |
| author_facet | Fiona Spirrett Tatsuya Ito Soshu Kirihara |
| author_sort | Fiona Spirrett |
| collection | DOAJ |
| description | The additive manufacturing of ceramics offers a reliable and repeatable method for fabricating parts with complex geometries. To compete with conventional ceramic forming methods, the time and cost associated with material and process optimization for ceramic stereolithography should be improved. Computational analysis methods can be utilized to reduce the number of experimental steps required for material and process optimization. This work used the discrete element method and ray tracing analyses to predict suitable material parameters and processing conditions for ceramic stereolithography. The discrete element method was used to create alumina particle dispersion models to predict suitable paste compositions, and ray tracing was used to predict suitable laser power and scan speed to achieve a sufficient curing depth for stereolithography processing. The predicted conditions of paste composition and processing parameters were comparable to experimental values, reducing the number of experimental iterations required for process optimization. Furthermore, suitable processing parameters for high-speed fabrication by stereolithography was predicted, achieving a processing speed much faster than previously reported ceramic stereolithography. The reduction in process optimization timeline, and the increase in fabrication speed, could increase the appeal of ceramic stereolithography to industry. |
| first_indexed | 2024-03-09T22:03:12Z |
| format | Article |
| id | doaj.art-0ee184e373d04ef1945b3595a14c815f |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T22:03:12Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-0ee184e373d04ef1945b3595a14c815f2023-11-23T19:45:18ZengMDPI AGApplied Sciences2076-34172022-09-011219976010.3390/app12199760High-Speed Alumina StereolithographyFiona Spirrett0Tatsuya Ito1Soshu Kirihara2Joining and Welding Research Institute, Osaka University, Osaka 567-0047, JapanJoining and Welding Research Institute, Osaka University, Osaka 567-0047, JapanJoining and Welding Research Institute, Osaka University, Osaka 567-0047, JapanThe additive manufacturing of ceramics offers a reliable and repeatable method for fabricating parts with complex geometries. To compete with conventional ceramic forming methods, the time and cost associated with material and process optimization for ceramic stereolithography should be improved. Computational analysis methods can be utilized to reduce the number of experimental steps required for material and process optimization. This work used the discrete element method and ray tracing analyses to predict suitable material parameters and processing conditions for ceramic stereolithography. The discrete element method was used to create alumina particle dispersion models to predict suitable paste compositions, and ray tracing was used to predict suitable laser power and scan speed to achieve a sufficient curing depth for stereolithography processing. The predicted conditions of paste composition and processing parameters were comparable to experimental values, reducing the number of experimental iterations required for process optimization. Furthermore, suitable processing parameters for high-speed fabrication by stereolithography was predicted, achieving a processing speed much faster than previously reported ceramic stereolithography. The reduction in process optimization timeline, and the increase in fabrication speed, could increase the appeal of ceramic stereolithography to industry.https://www.mdpi.com/2076-3417/12/19/9760discrete element methodray tracingstereolithographyaluminaadditive manufacturingceramics |
| spellingShingle | Fiona Spirrett Tatsuya Ito Soshu Kirihara High-Speed Alumina Stereolithography Applied Sciences discrete element method ray tracing stereolithography alumina additive manufacturing ceramics |
| title | High-Speed Alumina Stereolithography |
| title_full | High-Speed Alumina Stereolithography |
| title_fullStr | High-Speed Alumina Stereolithography |
| title_full_unstemmed | High-Speed Alumina Stereolithography |
| title_short | High-Speed Alumina Stereolithography |
| title_sort | high speed alumina stereolithography |
| topic | discrete element method ray tracing stereolithography alumina additive manufacturing ceramics |
| url | https://www.mdpi.com/2076-3417/12/19/9760 |
| work_keys_str_mv | AT fionaspirrett highspeedaluminastereolithography AT tatsuyaito highspeedaluminastereolithography AT soshukirihara highspeedaluminastereolithography |