Prediction modelling and process optimization for forming multi-layer cladding structures with laser directed energy deposition

Abstract

In the laser Directed Energy Deposition (DED) manufacturing of parts, severe deformation caused by the uneven geometric characteristics of a multi-layer deposition fusion area occurs extremely easily due to the complexity and insufficient understanding of the process. The above results in a significant decline in the overall geometric quality of the parts. To study the influence of the laser DED process parameters on the geometric characteristics of multi-layer cladding, a response surface method was used to carry out an experimental study of the multi-layer cladding structures. Statistical prediction models of multi-layer cladding manufacturing were established among the laser power, scanning speed, powder feeding rate, lap ratio and cladding width, cladding zone area, fusion zone area, and flatness ratio. The accuracy, adaptability and relevance of the models were verified. The influence of each process parameter on the geometric characteristics of the multi-layer cladding structure was analysed, and the laser DED process parameters were optimized. Experimental results show that the surface forming quality of specimens processed with optimized process parameters is good. Relative errors between the experimental and predicted values of the geometric characteristics of specimens are less than 9%; thus, the prediction models can suitably predict and control the geometric characteristics of a multi-layer cladding structure. The proposed optimization of process parameters can significantly improve the geometric quality of parts and has substantial value in engineering applications.