Optimization of Laser-Based Additive Manufacturing

Abstract

This chapter defines the problem of laser-based additive manufacturing (LBAM) process optimization. Two types of methods/models have been used to address the challenge of LBAM process optimization: physics-based models that seek to characterize the underlying thermophysics deposition process of LBAM and data-driven methods that target identifying the patterns in the existing experiment data through design of experiments and empirical modeling. The chapter summarizes the effects of a number of key process parameters on the thermal history and mechanical properties of LBAM parts to delineate the complex relationship between process parameters and microstructural/mechanical properties. In order to achieve enhanced or optimal quality for LBAM parts, it is essential to understand and characterize how LBAM process parameters affect thermal history, solidification, and eventually microstructural/mechanical properties. Further research is needed to leverage the information from existing studies and systematically characterize the relation between process parameters and part features so that the LBAM process can be optimized in a more efficient manner.