Computational Fabrication Approach to Extend the Softness Capabilities of 3D Printers

2020 Fiscal Year Final Research Report

• Project/Area Number: 19K20321
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 61020:Human interface and interaction-related
• Research Institution: Osaka University
• Principal Investigator: PUNPONGSANON PARINYA 大阪大学, 基礎工学研究科, 助教 (90812222)
• Project Period (FY): 2019-04-01 – 2021-03-31
• 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

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.

Free Research Field

ヒューマン・コンピュータ・インタラクション

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。