Metal additive manufacturing (AM) is a transformative set of technologies that are increasingly being used for demanding structural applications. However, persistent challenges regarding reliability and properties of the printed parts seriously impact qualification and certification (Q&C). Computational approaches can mitigate these challenges, but availability of benchmark measurement data for model validation is a key requirement. Q&C will be discussed in the context of the Computational Materials for Qualification and Certification (CM4QC) steering group, a tightly focused collaboration of aviation-focused companies, research and regulatory government agencies, and universities that is working to develop a roadmap for increasing the use of computational approaches in the aviation Q&C process. Benchmark measurement data will be discussed in the context of the Additive Manufacturing Benchmark Test Series (AM Bench), a broad collaboration of 10 NIST divisions and about 20 external organizations, including several that are collaborators on CM4QC, that provide rigorous measurement data for validating AM simulations for a wide range of AM technologies and material systems. Technical standards also play an important role for Q&C and the confluence between CM4QC, AM Bench, and standards organizations will be discussed.
No takes yet. Share an insight, caveat, or question.
Levine et al. (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: