Bending-active structures are composed of elastic elements that deform to achieve a desired target shape. To support effective design, inverse algorithms have been proposed that optimize the geometry of each element specifically for each design. This makes it difficult to reuse elements across designs or gain efficiency in fabrication through mass production.
We address this issue and propose a computational framework to rationalize bending-active structures into a sparse kit of parts. Our method solves for the optimal part geometry such that multiple input designs can be faithfully realized with the same kit of parts. Assigning parts to different assemblies leads to a combinatorial explosion that makes exhaustive search intractable. Instead, we propose a relaxed continuous optimization incorporating a physics-based simulation in its inner loop to model the elastic deformation of the bending-active structure accurately. Our algorithm allows analyzing different design trade-offs of a kit of parts to tune the balance between fabrication complexity and fidelity to the original designs. We demonstrate our method on three different classes of bending-active structures, showcasing the effectiveness of our approach for part reuse and sustainable practices in fabrication-driven design.