Building microstructures by welding millions of little bits of metal together: measurement approaches, model validation, and post-build processing

Over the past decade, immense, world-wide research and development efforts have attempted to bring additive manufacturing (AM) of metals into broad industrial use. Although major advances in our understanding and control over metal AM have accrued, its practical application has been underwhelming. The slow pace of commercial adoption can be traced to numerous factors, including poor build reproducibility, sensitivity to heterogeneous local processing conditions during the build, complications in developing and validating suitable processing-structure-property-performance (PSPP) simulation capabilities (physics-based models, surrogate models, and machine learning models), the small number of alloys suitable for metal AM, and the need for developing new alloy-specific post-processing protocols. All these factors negatively impact the purely business decision of what manufacturing approach should be used to produce a given component. Computational materials engineering approaches could play a major role in accelerating the adoption of metal AM, but rigorous model validation will be necessary to make this a reality. Here, discussion will focus on development and deployment of measurement approaches for model validation, and methodologies for accelerating development of post-build heat treatment through thermo-kinetic modelling and in situ measurements.