Toolpath Optimization of Polymer Composite Additive Manufacturing AM Printed Mold to Improve Performance for Compression Molding Applications

Conference · Tue Jul 01 04:00:00 EDT 2025

OSTI ID:2587457

Limaye, Madhura ^[1]; Prabhune, Bhagya ^[1]; Jo, Eonyeon ^[1]; Ozcan, Soydan ^[1]; Bazid, Nuvin ^[1]; Vaidya, Uday ^[1]; Hassen, Ahmed ^[1]; Kim, Pum ^[1]

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1. ORNL

This study explores the optimization of toolpaths for short fiber polymer composite additive manufacturing (AM) printed molds in compression molding applications, an emerging trend driven by advancements in 3D printing technology. AM printed molds offer reduced tooling costs and greater design flexibility, particularly for prototyping and low-volume production. The proposed optimization approach evaluates mold performance using two key metrics: deformation and shape accuracy. Multiple toolpaths are generated, and finite element (FE) simulations capture fiber orientation and material properties, which are then integrated into a mechanical performance model. Shape accuracy is assessed by comparing the deformed mold shape with the original using surface normals as a descriptor. The analysis identifies the toolpath that delivers the best overall performance, establishing it as the most suitable option for achieving optimal mold characteristics in compression molding applications.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 2587457
• Country of Publication: United States
• Language: English