In this study, the design for additive manufacturing of shoe molds with complex and precise patterns was performed to achieve rapid prototyping. Low alloy steels such as AISI4340 and SAE1524 were selected to make shoe molds to apply to the conventional chemical etching process. A lattice-oriented design and optimization of toolpath was tested to reduce the processing time. A reduction of 60% in processing time and pattern precision of 0.3 ㎜ was been achieved. Moreover, to improve the reliability of pattern formation, single-layer image analysis with computer vision and machine learning was developed and non-destructive analysis by X-ray CT was been performed. It was found that the quality of shoe molds can be decreased with a single defective layer.

In this study, design for additive manufacturing (DfAM) of release agent injection manifold for hot forging has been performed to achieve weight reduction and flow path optimization. The weight reduction of 53.5% was achieved, thereby enabling the application of stainless steel 316L, which has high strength and corrosion resistance. Lightweight manifolds using Al-Mg-10Si and SUS316L materials were fabricated by PBF-type metal 3D printer. The feasibility test showed that mold life was improved by 14% by solving residual release agent problem. In addition, the flow path optimization results suggested that the flow standard deviation of each outlet dropped sharply from 264 to 75 ㎤/s. This approach demonstrated that DfAM for release agent manifold could be applied to increase mold life and improve product quality and productivity for hot forging.