Towards the next generation of machine learning models in additive manufacturing: A review of process dependent material evolution

M Parsazadeh, S Sharma, N Dahotre - Progress in Materials Science, 2023 - Elsevier
Additive manufacturing facilitates producing of complex parts due to its design freedom in a
wide range of applications. Despite considerable advancements in additive manufacturing …

[HTML][HTML] Holistic computational design within additive manufacturing through topology optimization combined with multiphysics multi-scale materials and process …

M Bayat, O Zinovieva, F Ferrari, C Ayas… - Progress in Materials …, 2023 - Elsevier
Additive manufacturing (AM) processes have proven to be a perfect match for topology
optimization (TO), as they are able to realize sophisticated geometries in a unique layer-by …

Machine learning–aided real-time detection of keyhole pore generation in laser powder bed fusion

Z Ren, L Gao, SJ Clark, K Fezzaa, P Shevchenko… - Science, 2023 - science.org
Porosity defects are currently a major factor that hinders the widespread adoption of laser-
based metal additive manufacturing technologies. One common porosity occurs when an …

[HTML][HTML] Machine learning-assisted in-situ adaptive strategies for the control of defects and anomalies in metal additive manufacturing

DR Gunasegaram, AS Barnard, MJ Matthews… - Additive …, 2024 - Elsevier
In metal additive manufacturing (AM), the material microstructure and part geometry are
formed incrementally. Consequently, the resulting part could be defect-and anomaly-free if …

Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis

B Bevans, A Ramalho, Z Smoqi, A Gaikwad… - Materials & Design, 2023 - Elsevier
The goal of this work is to detect flaw formation in the wire-based directed energy deposition
(W-DED) process using in-situ sensor data. The W-DED studied in this work is analogous to …

On the application of in-situ monitoring systems and machine learning algorithms for develo** quality assurance platforms in laser powder bed fusion: A review

K Taherkhani, O Ero, F Liravi, S Toorandaz… - Journal of Manufacturing …, 2023 - Elsevier
Laser powder bed fusion (LPBF) is one class of metal additive manufacturing (AM) used to
fabricate high-quality complex-shape components. This technology has significantly …

[HTML][HTML] In-process and post-process strategies for part quality assessment in metal powder bed fusion: A review

C Chua, Y Liu, RJ Williams, CK Chua… - Journal of Manufacturing …, 2024 - Elsevier
An increasing number of metal components processed by additive manufacturing (AM) are
now being used in industrial applications. However, in the most demanding applications …

Multi phenomena melt pool sensor data fusion for enhanced process monitoring of laser powder bed fusion additive manufacturing

A Gaikwad, RJ Williams, H de Winton, BD Bevans… - Materials & Design, 2022 - Elsevier
Finding actionable trends in laser-based metal additive manufacturing process monitoring
data is challenging owing to the diversity and complexity of the underlying physical …

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 …

[HTML][HTML] Laser beam sha** facilitates tailoring the mechanical properties of IN718 during powder bed fusion

JD Pérez-Ruiz, F Galbusera, L Caprio… - Journal of Materials …, 2024 - Elsevier
One of the recent technological developments in the Laser Powder Bed Fusion (LPBF)
process is the use of non-Gaussian beam profiles of power density distributions. Irrespective …