Process Modeling of Laser-Based Metal Additive Manufacturing of Metal Alloy

Abstract

AbstractMetal additive manufacturing (AM) has a great impact on recent advancements in the manufacturing of metallic components in many industries such as automobile, aerospace, biomedical, and sports. Moreover, a new era has opened up for designing customized shapes and complex geometries with the controlled microstructure of metal alloys. The path to the design and manufacturing of additively manufactured components was pursued in evolutionary as well as revolutionary ways. Laser-based metal AM is one of the promising AM processes for metal alloy. However, there are several open issues related to the process performances. Process modeling and optimization will play a crucial role to advance the capability to quantify the influence of process variables on process performances. Besides multi-physics-based process modeling, data-driven modeling has emerged as a new paradigm in the modeling of metal AM. This chapter presents an application of data-driven statistical modeling and artificial intelligence (AI)-based modeling of the laser-based direct metal deposition process. The predictive accuracy of each modeling technique has been compared with experimental results. The ability of process modeling of metal AM using the AI approach will help to develop an intelligent AM system.KeywordsMetal additive manufacturingProcess modelingArtificial intelligenceStatistical modelingLaser direct metal deposition