Advancing additive manufacturing through deep learning: A comprehensive review of current progress and future challenges

AI Saimon, E Yangue, X Yue, C Liu - arXiv preprint arXiv:2403.00669, 2024 - arxiv.org
Additive manufacturing (AM) has already proved itself to be the potential alternative to
widely-used subtractive manufacturing due to its extraordinary capacity of manufacturing …

In-situ process monitoring and adaptive quality enhancement in laser additive manufacturing: a critical review

L Chen, G Bi, X Yao, J Su, C Tan, W Feng… - Journal of Manufacturing …, 2024 - Elsevier
Abstract Laser Additive Manufacturing (LAM) presents unparalleled opportunities for
fabricating complex, high-performance structures and components with unique material …

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 …

Multimodal sensor fusion for real-time location-dependent defect detection in laser-directed energy deposition

L Chen, X Yao, W Feng… - … and Information in …, 2023 - asmedigitalcollection.asme.org
Real-time defect detection is crucial in laser-directed energy deposition (L-DED) additive
manufacturing (AM). Traditional in-situ monitoring approach utilizes a single sensor (ie …

Metal Laser-Based Powder Bed Fusion Process Development Using Optical Tomography

R Björkstrand, J Akmal, M Salmi - Materials, 2024 - mdpi.com
In this study, a set of 316 L stainless steel test specimens was additively manufactured by
laser-based Powder Bed Fusion. The process parameters were varied for each specimen in …

Enhancing Part Quality Management Using a Holistic Data Fusion Framework in Metal Powder Bed Fusion Additive Manufacturing

Z Yang, J Kim, Y Lu, A Jones… - Journal of …, 2024 - asmedigitalcollection.asme.org
Metal powder bed fusion additive manufacturing (AM) processes have gained widespread
adoption for the ability to produce complex geometries with high performance. However, a …

Engineering-Guided Deep Learning of Melt-Pool Dynamics for Additive Manufacturing Quality Monitoring

S Zhang, H Yang, Z Yang, Y Lu - … of Computing and …, 2024 - asmedigitalcollection.asme.org
Additive manufacturing (AM) fabricates three-dimensional parts via layer-by-layer deposition
and solidification of materials. Due to the complexity of this process, advanced sensing is …

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 …

[PDF][PDF] A Hybrid Manufacturing Process Monitoring Method Using Stacked Gated Recurrent Unit and Random Forest.

CL Yang, AA Yilma, BH Woldegiorgis… - … Automation & Soft …, 2024 - cdn.techscience.cn
This study proposed a new real-time manufacturing process monitoring method to monitor
and detect process shifts in manufacturing operations. Since real-time production process …