We introduce a simulation-based approach to specify tool trajectories for micromachining the molds that are used to create directional gecko-inspired adhesives. A challenge is that the final feature geometries are different from the corresponding tool-paths. Therefore, the process of designing molds for different applications has previously required empirical iteration. Large plastic strains and sensitivity to material parameters and friction also make it difficult to apply conventional finite element analyses (FEAs), with only approximate agreement between predicted and observed cutting forces. The solution reported here uses a plane-strain FEA specialized for metal working, with a customized material model to accommodate the strain rates and strain hardening effects. The analysis was conducted for wax and soft aluminum molds with a variety of wedge-shaped features. Predicted and measured microscopic feature geometries match to within 2.8%.

Simulation-Guided, Application-Specific Manufacturing of Gecko-Inspired Adhesives

Hajj-Ahmad, Amar
;
Gharibi, Armin;Lanzetta, Michele;Cutkosky, Mark R.
2025-01-01

Abstract

We introduce a simulation-based approach to specify tool trajectories for micromachining the molds that are used to create directional gecko-inspired adhesives. A challenge is that the final feature geometries are different from the corresponding tool-paths. Therefore, the process of designing molds for different applications has previously required empirical iteration. Large plastic strains and sensitivity to material parameters and friction also make it difficult to apply conventional finite element analyses (FEAs), with only approximate agreement between predicted and observed cutting forces. The solution reported here uses a plane-strain FEA specialized for metal working, with a customized material model to accommodate the strain rates and strain hardening effects. The analysis was conducted for wax and soft aluminum molds with a variety of wedge-shaped features. Predicted and measured microscopic feature geometries match to within 2.8%.
2025
Hajj-Ahmad, Amar; Gharibi, Armin; Lanzetta, Michele; Cutkosky, Mark R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1319107
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