Uncertainty quantification for additive manufacturing process improvement: recent advances

S Mahadevan, P Nath, Z Hu - … -ASME Journal of …, 2022 - asmedigitalcollection.asme.org
This paper reviews the state of the art in applying uncertainty quantification (UQ) methods to
additive manufacturing (AM). Physics-based as well as data-driven models are increasingly …

A deep learning framework for layer-wise porosity prediction in metal powder bed fusion using thermal signatures

Y Mao, H Lin, CX Yu, R Frye, D Beckett… - Journal of Intelligent …, 2023 - Springer
Part quality manufactured by the laser powder bed fusion process is significantly affected by
porosity. Existing works of process–property relationships for porosity prediction require …

Knowledge-transfer-enabled porosity prediction for new part geometry in laser metal deposition

S Guo, C Zamiela, L Bian - Journal of Manufacturing Processes, 2023 - Elsevier
Data-driven porosity prediction in Laser Metal Deposition (LMD) is mainly done with
supervised machine learning methods. These methods require labeled thermal signatures …

Smart process map** of powder bed fusion additively manufactured metallic wicks using surrogate modeling

M Borumand, S Nannapaneni, G Madiraddy… - Journal of Intelligent …, 2024 - Springer
Powder bed fusion is an innovative additive manufacturing (AM) technique to achieve
metallic wick structures for efficient two-phase thermal management systems. However, a …

Probabilistic digital twin for additive manufacturing process design and control

P Nath, S Mahadevan - Journal of Mechanical …, 2022 - asmedigitalcollection.asme.org
This paper proposes a detailed methodology for constructing an additive manufacturing
(AM) digital twin for the laser powder bed fusion (LPBF) process. An important aspect of the …

[PDF][PDF] 激光粉末床熔融增材制造过程智能监控研究进展与挑战

赵志斌王晨希, 张兴武, 陈雪峰, **应红 - 机械工程学报, 2023 - qikan.cmes.org
激光粉末床熔融(Laser powder bed fusion, LPBF) 增材制造逐渐成为难加工金属构件快速,
低成本, 高性能, 短周期制造的“潜力股”, 被认为是使用最为广泛的金属增材制造技术之一 …

Probabilistic Data-Driven Modeling of a Melt Pool in Laser Powder Bed Fusion Additive Manufacturing

Q Fang, G **ong, M Zhao, TS Tamir… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The widespread adoption of laser powder bed fusion (LPBF) additive manufacturing is
hampered by process unreliability problems. Modeling the melt pool behavior in LPBF is …

Multi-fidelity Modeling for Uncertainty Quantification in Laser Powder Bed Fusion Additive Manufacturing

P Nath, M Sato, P Karve, S Mahadevan - Integrating Materials and …, 2022 - Springer
Computer simulation of the additive manufacturing (AM) process involves multi-physics,
multi-scale models. These sophisticated higher fidelity (HF) AM models, though more …

Review of digital twin methods for additive manufacturing

M Dezhuang, Y Weidong, CAI Zixing… - Computer Integrated …, 2024 - cims-journal.cn
Additive manufacturing (AM) can provide reliable data support for digital twin model with its
all-digital processing mode. Digital twins help AM give full play to its advantages different …