Computational Fabrication Approach to Extend the Softness Capabilities of 3D Printers
| Project/Area Number |
19K20321
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 61020:Human interface and interaction-related
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| Research Institution | Osaka University |
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Principal Investigator |
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| Project Period (FY) |
2019-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2020: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2019: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
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| Keywords | デジタルファブリケーション / 3Dプリンター出力 / 柔らかさ・硬さ / 柔らかさ / digital fabrication / 3D printing / human perception / user interface design / 3Dプリンター / 計算論的 / ヒューマンインタフェース / インタラクション |
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| Outline of Research at the Start |
Digital fabrication has enabled massive creativity in product design both personal and industrial. The reduction of price and increase of quality of 3D printer enable individual to fabricate every object that meets the personal need. However, these objects often lack the haptic softness desired by users. In this research, I seeking to enable feel variation of haptics 'softness' desired out from a limited number of available materials of 3D printing by leveraging knowledge of advanced materials, human perception, and fabrication techniques.
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| Outline of Final Research Achievements |
We found that in addition to the perception of roughness (note: previous research), the internal structure (when the filling rate is kept constant) and the surface microstructure affect the perception of hardness and softness when output by a 3D printer. However, the results also suggested that the surface microstructure had less influence on the perception of hardness and softness compared to the internal fill rate (e.g., infill ratio). These results were in agreement with perceived roughness and perceived softness when microstructure was manipulated, but not in strong agreement with perceived roughness. Based on these experimental results, we developed a computational model to estimate and predict the perceived softness of 3D printed objects according to their perceived roughness. Finally, we also verified the model with arbitrary parameters using inverse modeling method.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究の成果は、標準的な既製の3Dプリンターに加えて、同じ3Dプリンティング・フィラメントを使用して、知覚される材料特性（例えば、柔らかさや硬さ）を拡張するために使用することができます。したがって、本研究で提案した方法は、必要な柔らかさに応じて微細構造を操作することで、3Dプリンターに必要な代替材料の数を減らすことができます（例えば、数種類の柔らかい材料を印刷する場合など）。また、知覚された柔らかさと粗さの対応関係も示唆されており、今後も様々な研究分野での展開が期待されます。
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Report
(3 results)
Research Products
(8 results)
