Surface based variable thickness slicing modeling for laser metal deposition

Abstract

Laser metal deposition (LMD) has been a promising additive manufacturing technology widely used in mold rapid manufacturing. In order to improve the capacity of LMD for complex curved surface structures, a surface based variable thickness slicing (S-VTS) model is proposed to adaptively generate the LMD process based on the geometric characteristics of structures. Two deposition strategies in scanning and overlapping directions are designed to enable variable thickness of each cladding layer by dynamically adjusting the scanning speed and overlapping rate. To improve the surface quality and forming efficiency, the discrete particle swarm optimization (DPSO) algorithm is adopt to optimize the process parameters of S-VTS model, including the number of cladding layer, scanning pass, and segment per pass. Several experiments are conducted to form the cuboid samples with wavy and freeform surface and verify the feasibility of the S-VTS model. The results demonstrate that under the open-loop control condition, the geometric accuracy, surface quality, and efficiency of the proposed method is improved in comparison with uniform thickness slicing (UTS) deposition. Moreover, heterogeneous microstructure is always generated by the S-VTS method in terms of grain size and growth direction.