Corner path optimization strategy for wire arc additive manufacturing of gap-free shapes

Wire Arc Additive Manufacturing (WAAM) is a promising method to build large metal structures through multi-pass multi-layer deposition. However, during WAAM processing of complex structures using traditional contour paths, filling gaps are easily left at sharp corners due to excessive self-overlapping and under-filling. This study focuses on the development of a corner path optimization strategy in order to improve the capability of the WAAM process in producing gap-free metal components. Firstly, based on the traditional contour paths, an innovative corner path optimization method was developed to generate multi-pass paths with varying centre distances and extra gap-fill paths at corners which avoid excessive self-overlapping and under-filling. Then an Artificial Neural Networks (ANNs) bead model was established to select the welding parameters which are adaptive to the modified multi-pass paths at corners. The capability of WAAM to deposit the welding bead with varying widths but a constant height was verified experimentally. Finally, a set of corners were produced by multi-pass multi-layer deposition in accordance with the proposed corner paths, and the optimum parameter for the corner path planning was discussed. Gap defects at corners can be controlled through using the proposed strategy of corner path modification and adaptive welding parameters selection. This is critical in process planning to achieve gap-free deposition in the WAAM of structures with sharp corners.