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Meeting MS&T26: Materials Science & Technology
Symposium Additive Manufacturing: Equipment, Instrumentation and In-Situ Process Monitoring
Presentation Title K2: An Open Architecture Wire-Laser Directed Energy Deposition Testbed for Advanced Control Strategy Development
Author(s) Jakob D. Hamilton, Walter W Glockner, Elaina Kwarteng, Dedley Gorayeb Filho, Brady Curran, Willem Potter, Alfred Kofi Apianing Achenie
On-Site Speaker (Planned) Jakob D. Hamilton
Abstract Scope Directed energy deposition (DED) additive manufacturing possesses the unique ability to create complex, large-scale, and multi-material structures. Complex thermofluidic behavior and process anomalies have limited the DED application scope to coatings and low aspect ratio geometries. Recent advances in machine learning and embedded sensing have enabled new understandings of DED process physics, yet there remains a significant gap between anomaly detection and automated correction. This work presents an open-architecture wire-laser DED testbed built to address this gap. The testbed enables real-time feedback of critical systems including the incident laser power, the wire feed velocity, and robot trajectory. This work will highlight recent efforts at fusing heterogeneous in-situ data stemming from acoustic, vision, and wire feed sensors. A dynamic robotic path planning strategy via a digital twin will also be presented. By bridging the detection-correction gap, this work addresses critical DED limitations and strengthens applications and capabilities for DED technologies.

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

AMDiffusion: Domain-Adaptive Diffusion Modeling for Causal Data Fusion in Additive Manufacturing
Beyond Deep Learning: A Bayesian-Optimized Computer Vision Framework for Rapid Spatter Detection and Tracking in Laser Powder Bed Fusion
Designing Sensor Systems for Anomaly and Flaw Detection in Laser Powder Bed Fusion Additive Manufacturing
Hybrid Feedforward-Feedback Process Control of Laser Powder Bed Fusion
K2: An Open Architecture Wire-Laser Directed Energy Deposition Testbed for Advanced Control Strategy Development
Large Language Models for In-Situ Interpretation of Defect Signatures in Powder Bed Fusion
Rapid Modeling and Prediction of Thermal Strain in Laser Powder Bed Fusion
Self-Sensing of 3D-Printed Materials by Measuring the Inductance, Resistance and Capacitance
Smoke, Mirrors, and Melt Pools: An Assessment of Commercial PBF-LB In-Situ Process Monitoring Solutions

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