Multi-material topology optimization for additive manufacturing considering maximum build volume and assembly process
Yukun Feng, Takayuki Yamada
Abstract
While topology optimization is promising for additive manufacturing structures, challenges arise in designing multi-material assemblies. The size often surpasses additive manufacturing build volumes, hindering successful manufacturing. Additionally, intricate topology-optimized structures complicate the assembly and decomposition of multiple material components. Addressing the aforementioned issues can be achieved by incorporating dimensional and assembly constraints into the optimization process. So far, these constraints have only been studied and implemented separately, leading to suboptimal solutions. Simply applying these two constraints together can also lead to excessive computational complexity. This paper introduces a multi-material topology optimization framework that considers both dimensional and assembly constraints. We propose an assembly direction-aligned method for dimensional constraints to reduce computational costs and an adaptive weighting factor for assembly constraints to enhance numerical stability. Validation through numerical examples and successful fabrication and assembly of a 3D-printed prototype underscore the framework’s efficacy in ensuring the manufacturability and assemblability of structures designed via topology optimization.