In this paper, we present a topology optimization (TO) framework to enable automated design of mechanical components while ensuring the result can be manufactured using multi-axis machining. Although TO improves the part’s performance, the as-designed model is often geometrically too complex to be machined and the as-manufactured model can significantly vary due to machining constraints that are not accounted for during TO. In other words, many of the optimized design features cannot be accessed by a machine tool without colliding with the part (or fixtures). The subsequent post-processing to make the part machinable with the given setup requires trial-and-error without guarantees on preserving the optimized performance. Our proposed approach is based on the well-established accessibility analysis formulation using convolutions in configuration space that is extensively used in spatial planning and robotics. We define an inaccessibility measure field (IMF) over the design domain to identify non-manufacturable features and quantify their contribution to non-manufacturability. The IMF is used to penalize the sensitivity field of performance objectives and constraints to prevent formation of inaccessible regions. Unlike existing discrete formulations, our IMF provides a continuous spatial field that is desirable for TO convergence. Our approach applies to arbitrary geometric complexity of the part, tools, and fixtures, and is highly parallelizable on multi-core architecture. We demonstrate the effectiveness of our framework on benchmark and realistic examples in 2D and 3D. We also show that it is possible to directly construct manufacturing plans for the optimized designs based on the accessibility information.

在本文中，我们提出了一种拓扑优化（TO）框架，以实现机械零件的自动化设计，同时确保可以使用多轴加工来制造结果。尽管TO可以提高零件的性能，但设计时的模型通常在几何形状上过于复杂而无法进行加工，并且由于在TO期间未考虑到加工限制，因此制造时的模型可能会发生显着变化。换句话说，如果不与零件（或固定装置）碰撞，机床无法访问许多优化的设计特征。为了使零件可以使用给定的设置进行加工，随后的后处理需要反复试验，而不能保证保持最佳性能。我们提出的方法基于在配置空间中使用卷积的公认的可访问性分析公式，该公式在空间规划和机器人技术中广泛使用。我们定义一个设计领域的不可访问性度量字段（IMF），以识别不可制造的特征并量化其对不可制造性的贡献。IMF被用来惩罚绩效目标和约束的敏感领域，以防止形成无法进入的区域。与现有的离散公式不同，我们的IMF提供了TO收敛所需的连续空间场。我们的方法适用于零件，工具和固定装置的任意几何复杂性，并且在多核体系结构上具有高度可并行性。我们在2D和3D中的基准和实际示例上证明了我们框架的有效性。我们还表明，可以根据可访问性信息直接为优化设计构建制造计划。