Lattice structures with different desired physical properties are promising for a broad spectrum of applications. The availability of additive manufacturing (AM) technology has relaxed the fabricating limitation of lattice structures. However, manufacturing constraints still exist for AM-fabricated lattice structures, which have a significant influence on the printing quality and mechanical properties of lattice struts. In this paper, a design and optimization strategy is proposed for lattice structures with the consideration of manufacturability to ensure desired printing quality. The concept of manufacturable element is used to link the design and manufacturing process. A meta-model is constructed by experiments and the artificial neural network to obtain the manufacturing constraints. Sizes of struts are optimized by a bidirectional evolutionary structural optimization-based algorithm with these manufacturing constraints. An arm of quadcopter is redesigned and optimized to validate the proposed method. Its result shows that optimized heterogeneous lattice structures can improve the stiffness of the model compared to the homogeneous lattice structure and the original design. Both the Von-Mises stress and the maximum displacement are reduced without increasing the weight of designed part. And by considering the manufacturability constraints, the optimized design has been successfully fabricated by the selected additive manufacturing process. Note to Practitioners-Lattice structures might fail to be fabricated by the additive manufacturing technique if the designed model exceeds the processability of the machine. Our approach has the capability of considering the manufacturing constraints in the design and optimization process. We conducted experiments to investigate the manufacturability and proposed a method that can give the domain of the design variables for a selected manufacturing process. And we also designed an algorithm that can optimize the lattice structure inside the domain of design variables. It ensures that the lattice model can be successfully fabricated by the selected process and the performance is dramatically increased compared to the original design. Engineers can use our approach to optimize the lattice structure automatically without knowing the knowledge of optimization and manufacturability.

中文翻译：

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增材制造约束下的晶格结构设计和优化


具有不同所需物理性质的晶格结构有望获得广泛的应用。增材制造（AM）技术的出现放松了晶格结构的制造限制。然而，增材制造晶格结构仍然存在制造限制，这对晶格支柱的打印质量和机械性能有重大影响。本文提出了一种考虑可制造性的点阵结构设计和优化策略，以确保所需的打印质量。可制造元素的概念用于链接设计和制造过程。通过实验和人工神经网络构建元模型以获得制造约束。支柱的尺寸通过基于双向进化结构优化的算法在这些制造约束下进行优化。对四轴飞行器的手臂进行了重新设计和优化以验证所提出的方法。结果表明，与同质点阵结构和原始设计相比，优化的异质点阵结构可以提高模型的刚度。在不增加设计零件重量的情况下，Von-Mises 应力和最大位移都降低了。通过考虑可制造性限制，优化的设计已通过所选的增材制造工艺成功制造。从业人员注意——如果设计的模型超出了机器的可加工性，则增材制造技术可能无法制造晶格结构。我们的方法能够在设计和优化过程中考虑制造约束。 我们进行了实验来研究可制造性，并提出了一种可以给出选定制造工艺的设计变量范围的方法。我们还设计了一种可以在设计变量域内优化晶格结构的算法。它确保可以通过所选工艺成功制造晶格模型，并且与原始设计相比，性能显着提高。工程师可以使用我们的方法自动优化晶格结构，而无需了解优化和可制造性知识。