抄録
In this paper, we will discuss the technology of prediction in AM processes, which is considered to be increasingly important for
controlling microstructures, maximizing component performance, and ensuring reliability. An attempt to correlate part-scale and
microscale temperature field analysis with actual microstructures is presented as well as an example of predicting solidification
segregation by combining part-scale temperature field analysis with the phase field method. In addition, an example from the
literature is presented, where machine learning was used to predict tensile strength distributions from temperature field data obtained
by monitoring during the AM process.
