论文标题
制造序列优化，以最大程度地减少多轴添加剂制造的失真
Fabrication Sequence Optimization for Minimizing Distortion in Multi-Axis Additive Manufacturing
论文作者
论文摘要
金属零件的添加剂制造涉及相变和高温梯度，从而导致不均匀的热膨胀和收缩，从而导致造成的组件变形。失真对结构性能和尺寸精度有很大影响，例如组装。因此，对建模，预测和最终减少失真至关重要。在本文中，我们提出了用于制造序列优化的计算框架，以最大程度地减少多轴添加剂制造中的失真（例如，机器人线弧添加剂制造），其中制造序列不仅限于平面层。我们通过连续的伪时间字段编码制造序列，并使用基于梯度的数值优化对其进行优化。为了证明这一框架，我们采用了一个可计算的可拖动但合理准确的模型来模仿金属添加剂制造中的材料收缩，从而预测了制造的组件的变形。数值研究表明，与平面相比，优化的弯曲层可以通过数量级来减少变形。
Additive manufacturing of metal parts involves phase transformations and high temperature gradients which lead to uneven thermal expansion and contraction, and, consequently, distortion of the fabricated components. The distortion has a great influence on the structural performance and dimensional accuracy, e.g., for assembly. It is therefore of critical importance to model, predict and, ultimately, reduce distortion. In this paper, we present a computational framework for fabrication sequence optimization to minimize distortion in multi-axis additive manufacturing (e.g., robotic wire arc additive manufacturing), in which the fabrication sequence is not limited to planar layers only. We encode the fabrication sequence by a continuous pseudo-time field, and optimize it using gradient-based numerical optimization. To demonstrate this framework, we adopt a computationally tractable yet reasonably accurate model to mimic the material shrinkage in metal additive manufacturing and thus to predict the distortion of the fabricated components. Numerical studies show that optimized curved layers can reduce distortion by orders of magnitude as compared to their planar counterparts.
