Modeling and simulation of metal selective laser melting process: a critical review

As a technology of additive manufacturing (AM), selective laser melting (SLM) is widely used in metal printing, such as super-alloys, stainless steel. Also, the SLM is considered the most potential metal additive manufacturing technology. It is difficult to build a process-performance relationship using traditional physical model, since SLM process is multi parameter and multi-scale. Also, the experimental method takes a long time and is expensive, which requires proposal of a new accurate analytical model and simulation method. The uniqueness of this review includes discussions on the model and simulation model based on physical theory and data driven. The analytical model based on physical model in SLM is discussed. In order to solve the nonlinear equation in the physical model, the numerical method that used FEM software is summarized. With the development of machine learning method, the machine learning based on data driven is used in SLM process optimization. The discussion and future trends of three methods are proposed in order to solve the gap between laboratory and industry.

Automated summary

This paper discusses the application of selective laser melting in metal printing and highlights the challenges in establishing the relationship between SLM process and performance. The paper also discusses the analytical and simulation models based on physical theory and data driven approach, as well as the use of finite element software for solving nonlinear equations and the application of machine learning in SLM process optimization.