[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 …

[HTML][HTML] Big data, machine learning, and digital twin assisted additive manufacturing: A review

L Jin, X Zhai, K Wang, K Zhang, D Wu, A Nazir, J Jiang… - Materials & Design, 2024 - Elsevier
Additive manufacturing (AM) has undergone significant development over the past decades,
resulting in vast amounts of data that carry valuable information. Numerous research studies …

On the application of in-situ monitoring systems and machine learning algorithms for developing 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 …

Machine learning in manufacturing towards industry 4.0: From 'for now'to 'four-know'

T Chen, V Sampath, MC May, S Shan, OJ Jorg… - Applied Sciences, 2023 - mdpi.com
While attracting increasing research attention in science and technology, Machine Learning
(ML) is playing a critical role in the digitalization of manufacturing operations towards …

[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 …

[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 …

Machine learning models for efficient characterization of Schottky barrier photodiode internal parameters

RO Ocaya, AA Akinyelu, AG Al-Sehemi, A Dere… - Scientific Reports, 2023 - nature.com
We propose ANN-based models to analyze and extract the internal parameters of a Schottky
photodiode (SPD) without presenting them with any knowledge of the highly nonlinear …

Imbalanced data generation and fusion for in-situ monitoring of laser powder bed fusion

J Li, L Cao, H Liu, Q Zhou, X Zhang, M Li - Mechanical Systems and Signal …, 2023 - Elsevier
Laser powder bed fusion (LPBF) can produce near net shape products with complex
geometries. Unfortunately, the LPBF technology still largely suffer from poor part consistency …

[HTML][HTML] A novel machine learning-based approach for in-situ surface roughness prediction in laser powder-bed fusion

S Toorandaz, K Taherkhani, F Liravi, E Toyserkani - Additive Manufacturing, 2024 - Elsevier
Controlling and optimizing surface roughness remain a significant challenge in laser powder
bed fusion (LPBF). Surface roughness affects printed part quality, particularly fatigue life …

Photodiode-based porosity prediction in laser powder bed fusion considering inter-hatch and inter-layer effects

Z Tao, A Thanki, L Goossens, A Witvrouw… - Journal of Materials …, 2024 - Elsevier
Laser powder bed fusion, while promising, faces hurdles in certifying fabricated parts due to
cost and complexity, with in-process monitoring emerging as a potential solution. Existing …