Publication Type
Book Chapter
Publication Date
Page Numbers
53 to 59
Publisher Name
ASM International
Publisher Location
Almere, Netherlands
Abstract
Process optimization is the discipline of adjusting a process to optimize a specified set of parameters without violating engineering constraints. This article reviews data-driven optimization methods based on genetic algorithms and stochastic models and demonstrates their use in powder-bed fusion and directed energy deposition processes. In the latter case, closed-loop feedback is used to control melt pool temperature and cooling rate in order to achieve desired microstructure.