Fundamental requirements of a machine learning operations platform for industrial metal additive manufacturing

M Safdar, PP Paul, G Lamouche, G Wood… - Computers in …, 2024 - Elsevier
Abstract Metal-based Additive Manufacturing (AM) can realize fully dense metallic
components and thus offers an opportunity to compete with conventional manufacturing …

Transferability analysis of data-driven additive manufacturing knowledge: a case study between powder bed fusion and directed energy deposition

M Safdar, J Xie, H Ko, Y Lu… - … and Information in …, 2023 - asmedigitalcollection.asme.org
Data-driven research in Additive Manufacturing (AM) has gained significant success in
recent years. This has led to a plethora of scientific literature to emerge. The knowledge in …

Digital thread-driven cloud-fog-edge collaborative disturbance mitigation mechanism for adaptive production in digital twin discrete manufacturing workshop

Z Lin, Z Liu, J Yan, Y Zhang, C Chen… - International Journal of …, 2024 - Taylor & Francis
The collaborative capacity among various computing layers within a digital twin workshop
directly impacts the handling of disturbances in discrete manufacturing processes. However …

Multiphysics Missing Data Synthesis: A Machine Learning Approach for Mitigating Data Gaps and Artifacts

JC Steuben, AB Geltmacher… - Journal of …, 2024 - asmedigitalcollection.asme.org
The presence of gaps and spurious nonphysical artifacts in datasets is a nearly ubiquitous
problem in many scientific and engineering domains. In the context of multiphysics …

Toward Fatigue-Tolerant Design of Additively Manufactured Strut-Based Lattice Metamaterials

NA Apetre, JG Michopoulos… - Journal of …, 2024 - asmedigitalcollection.asme.org
The advent of additive manufacturing (AM) has enabled the prototyping of periodic and non-
periodic metamaterials (aka lattice or cellular structures) that could be deployed in a variety …