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<p>Fiber-reinforced additive manufacturing (FRAM) enables highly anisotropic material behavior that can be exploited through numerical optimization; however, existing methods typically constrain fiber orientations to user-defined print planes, limiting attainable anisotropic configurations and reducing their effectiveness in topology optimization. This work presents a novel optimization framework that concurrently performs print orientation optimization (POO), stacking sequence optimization (SSO), and topology optimization (TO) for FRAM components. The proposed formulation introduces domain-level orientation design variables that define the full 3D orientation of the print plane and the configuration of in-plane fiber reinforcements, thereby significantly expanding orientation design freedom beyond conventional plane-constrained approaches. The framework further decouples orientation optimization from density-driven topology effects, ensuring that anisotropic material properties remain influential throughout the design space. Efficient analytical sensitivities are derived for all orientation variables and integrated with gradient-based optimization algorithms to solve compliance minimization problems for anisotropic structures. The methodology is demonstrated through an academic benchmark to assess robustness and repeatability, and through a complex industry-scale case study involving an electric all-terrain vehicle (eATV) rear assembly. Results show that the proposed approach identifies non-intuitive anisotropic material property configurations and optimized material distributions, achieving up to a 92% reduction in structural compliance compared to an equal-mass metallic baseline. The framework provides a practical and scalable pathway for fully exploiting anisotropy in FRAM-enabled structural optimization.</p>

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Concurrent optimization of print orientation, stacking sequence, and topology for fiber-reinforced additively manufactured components

  • 期刊论文

  • 发表日期：

    2026年4月4日

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  • Noah Ray,
  • Il Yong Kim

摘要

Fiber-reinforced additive manufacturing (FRAM) enables highly anisotropic material behavior that can be exploited through numerical optimization; however, existing methods typically constrain fiber orientations to user-defined print planes, limiting attainable anisotropic configurations and reducing their effectiveness in topology optimization. This work presents a novel optimization framework that concurrently performs print orientation optimization (POO), stacking sequence optimization (SSO), and topology optimization (TO) for FRAM components. The proposed formulation introduces domain-level orientation design variables that define the full 3D orientation of the print plane and the configuration of in-plane fiber reinforcements, thereby significantly expanding orientation design freedom beyond conventional plane-constrained approaches. The framework further decouples orientation optimization from density-driven topology effects, ensuring that anisotropic material properties remain influential throughout the design space. Efficient analytical sensitivities are derived for all orientation variables and integrated with gradient-based optimization algorithms to solve compliance minimization problems for anisotropic structures. The methodology is demonstrated through an academic benchmark to assess robustness and repeatability, and through a complex industry-scale case study involving an electric all-terrain vehicle (eATV) rear assembly. Results show that the proposed approach identifies non-intuitive anisotropic material property configurations and optimized material distributions, achieving up to a 92% reduction in structural compliance compared to an equal-mass metallic baseline. The framework provides a practical and scalable pathway for fully exploiting anisotropy in FRAM-enabled structural optimization.