[HTML][HTML] Research and application of machine learning for additive manufacturing

J Qin, F Hu, Y Liu, P Witherell, CCL Wang… - Additive …, 2022 - Elsevier
Additive manufacturing (AM) is poised to bring a revolution due to its unique production
paradigm. It offers the prospect of mass customization, flexible production, on-demand and …

Process monitoring and machine learning for defect detection in laser-based metal additive manufacturing

T Herzog, M Brandt, A Trinchi, A Sola… - Journal of Intelligent …, 2024 - Springer
Over the past several decades, metal Additive Manufacturing (AM) has transitioned from a
rapid prototyping method to a viable manufacturing tool. AM technologies can produce parts …

3D printing in materials manufacturing industry: A realm of Industry 4.0

TS Tamir, G Xiong, Z Shen, J Leng, Q Fang, Y Yang… - Heliyon, 2023 - cell.com
Additive manufacturing (AM), also known as 3D printing, is a new manufacturing trend
showing promising progress over time in the era of Industry 4.0. So far, various research has …

Applications of machine learning in metal powder-bed fusion in-process monitoring and control: status and challenges

Y Zhang, W Yan - Journal of Intelligent Manufacturing, 2023 - Springer
The continuous development of metal additive manufacturing (AM) promises the flexible and
customized production, spurring AM research towards end-use part fabrication rather than …

Physics-informed and hybrid machine learning in additive manufacturing: application to fused filament fabrication

B Kapusuzoglu, S Mahadevan - Jom, 2020 - Springer
This article investigates several physics-informed and hybrid machine learning strategies
that incorporate physics knowledge in experimental data-driven deep-learning models for …

A single-sensor multi-scale quality monitoring methodology for laser-directed energy deposition: Example with height instability and porosity monitoring in additive …

B Li, Y Zhang, Y Lei, H Wei, C Chen, F Liu, P Zhao… - Additive …, 2024 - Elsevier
Abstract Laser Additive Manufacturing (LAM) faces various technical challenges,
encompassing issues with dimensional accuracy, mechanical properties, and processing …

A random forest classifier for anomaly detection in laser-powder bed fusion using optical monitoring

IA Khan, H Birkhofer, D Kunz, D Lukas, V Ploshikhin - Materials, 2023 - mdpi.com
Metal additive manufacturing (AM) is a disruptive production technology, widely adopted in
innovative industries that revolutionizes design and manufacturing. The interest in quality …

Optimizing quality inspection and control in powder bed metal additive manufacturing: Challenges and research directions

S Di Cataldo, S Vinco, G Urgese… - Proceedings of the …, 2021 - ieeexplore.ieee.org
One of the key targets of Industry 4.0 and digital production, in general, is the support of
faster, cleaner, and increasingly customizable manufacturing processes. Additive …

Neural network-based build time estimation for additive manufacturing: a performance comparison

Y Oh, M Sharp, T Sprock, S Kwon - Journal of Computational …, 2021 - academic.oup.com
Additive manufacturing (AM) has brought positive opportunities with phenomenal changes
to traditional manufacturing. Consistent efforts and novel studies into AM use have resolved …

Spatiotemporal analysis of powder bed fusion melt pool monitoring videos using deep learning

RJ Williams, SL Sing - Journal of Intelligent Manufacturing, 2024 - Springer
For several years now, in-situ process monitoring has been proposed as the enabler of fast
and flexible part qualification in powder bed fusion manufacturing. However, the predictive …