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In 3D printing, stiff fibers (e.g., carbon fiber) can reinforce thermoplasticpolymers with limited stiffness. However, existing commercial digitalmanufacturing software only provides a few simple fiber layout algorithms,which solely use the geometry of the shape. In this work, we build an automatedfiber path planning algorithm that maximizes the stiffness of a 3D print givenspecified external loads. We formalize this as an optimization problem: anobjective function is designed to measure the stiffness of the object whileregularizing certain properties of fiber paths (e.g., smoothness). Toinitialize each fiber path, we use finite element analysis to calculate thestress field on the object and greedily "walk" in the direction of the stressfield. We then apply a gradient-based optimization algorithm that uses theadjoint method to calculate the gradient of stiffness with respect to fiberlayout. We compare our approach, in both simulation and real-world experiments,to three baselines: (1) concentric fiber rings generated by Eiger, a leadingdigital manufacturing software package developed by Markforged, (2) greedyextraction on the simulated stress field (i.e., our method withoutoptimization), and (3) the greedy algorithm on a fiber orientation fieldcalculated by smoothing the simulated stress fields. The results show thatobjects with fiber paths generated by our algorithm achieve greater stiffnesswhile using less fiber than the baselines--our algorithm improves the Paretofrontier of object stiffness as a function of fiber usage. Ablation studiesshow that the smoothing regularizer is needed for feasible fiber paths andstability of optimization, and multi-resolution optimization helps reduce therunning time compared to single-resolution optimization.

More Stiffness with Less Fiber: End-to-End Fiber Path Optimization for 3D-Printed Composites