| Abstract Scope |
Manufacturing of materials is marching into an era where the gap between conceptualization and commercialization can be significantly reduced by utilizing an integrated materials design approach, materials informatics, and machine learning. Additive manufacturing (AM), which enables fabrication of parts with complex geometries directly from 3D models, is a major driving force in this new design and manufacturing era. In order to fully develop Industry 4.0 capabilities, the field of AM is seeing significant research efforts focused on developing comprehensive and well integrated processing-microstructure-properties knowledge and databases, as well as multi-scale modeling tools to be used in a data-driven materials design and manufacturing approach. There are many metal AM processes that have been developed and are being evaluated for adoption in high-integrity applications. In this context, opportunities for qualification of structural AM materials will be discussed, with emphasis on effective methodologies for rapid material characterization and process optimization for fatigue performance. |