Fabrication sequence optimization for minimizing distortion in multi-axis additive manufacturing

Additive manufacturing of metal parts involves phase transformations and high temperature gradients which lead to uneven thermal expansion contraction, and, consequently, distortion the fabricated components. The has a great influence on structural performance dimensional accuracy, e.g., for assembly. It is therefore critical importance model, predict ultimately, reduce distortion. In this paper, we present computational framework fabrication sequence optimization minimize in multi-axis additive (e.g., robotic wire arc manufacturing), not limited planar layers only. We encode by continuous pseudo-time field, optimize it using gradient-based numerical optimization. To demonstrate framework, adopt computationally tractable yet reasonably accurate model mimic material shrinkage thus Numerical studies show that optimized curved can orders magnitude as compared their counterparts.