More Stiffness with Less Fiber: End-to-End Fiber Path Optimization for 3D-Printed Composites
Xingyuan Sun, Geoffrey Roeder, Tianju Xue, Ryan P. Adams, Szymon, Rusinkiewicz

TL;DR
This paper introduces an automated fiber path optimization method for 3D-printed composites that significantly enhances stiffness while reducing fiber usage, outperforming existing commercial solutions.
Contribution
It formalizes a novel optimization framework for fiber layout that maximizes stiffness using stress analysis and gradient-based methods, surpassing current simple algorithms.
Findings
Optimized fiber paths increase stiffness more than baseline methods.
The approach reduces fiber usage while maintaining or improving stiffness.
Multi-resolution optimization decreases computational time.
Abstract
In 3D printing, stiff fibers (e.g., carbon fiber) can reinforce thermoplastic polymers with limited stiffness. However, existing commercial digital manufacturing software only provides a few simple fiber layout algorithms, which solely use the geometry of the shape. In this work, we build an automated fiber path planning algorithm that maximizes the stiffness of a 3D print given specified external loads. We formalize this as an optimization problem: an objective function is designed to measure the stiffness of the object while regularizing certain properties of fiber paths (e.g., smoothness). To initialize each fiber path, we use finite element analysis to calculate the stress field on the object and greedily "walk" in the direction of the stress field. We then apply a gradient-based optimization algorithm that uses the adjoint method to calculate the gradient of stiffness with respect…
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