[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 …

Machine learning algorithms for defect detection in metal laser-based additive manufacturing: A review

Y Fu, ARJ Downey, L Yuan, T Zhang, A Pratt… - Journal of Manufacturing …, 2022 - Elsevier
Laser-based additive manufacturing (LBAM), a series of additive manufacturing
technologies, has unrivaled advantages due to its design freedom to manufacture complex …

Machine learning for metal additive manufacturing: Towards a physics-informed data-driven paradigm

S Guo, M Agarwal, C Cooper, Q Tian, RX Gao… - Journal of Manufacturing …, 2022 - Elsevier
Abstract Machine learning (ML) has shown to be an effective alternative to physical models
for quality prediction and process optimization of metal additive manufacturing (AM) …

When AI meets additive manufacturing: Challenges and emerging opportunities for human-centered products development

C Liu, W Tian, C Kan - Journal of Manufacturing Systems, 2022 - Elsevier
Nowadays, additive manufacturing (AM) has been increasingly leveraged to produce human-
centered products, such as orthoses and prostheses as well as therapeutic helmets, finger …

Data-driven modeling of process, structure and property in additive manufacturing: A review and future directions

Z Wang, W Yang, Q Liu, Y Zhao, P Liu, D Wu… - Journal of Manufacturing …, 2022 - Elsevier
A thorough understanding of complex process-structure-property (PSP) relationships in
additive manufacturing (AM) has long been pursued due to its paramount importance in …

A deep learning solution for real-time quality assessment and control in additive manufacturing using point cloud data

J Akhavan, J Lyu, S Manoochehri - Journal of Intelligent Manufacturing, 2024 - Springer
This work presents an in-situ quality assessment and improvement technique using point
cloud and AI for data processing and smart decision making in Additive Manufacturing (AM) …

[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 …

Securing cyber-physical additive manufacturing systems by in-situ process authentication using streamline video analysis

A Al Mamun, C Liu, C Kan, W Tian - Journal of Manufacturing Systems, 2022 - Elsevier
In cyber-physical systems (CPS) of additive manufacturing (AM), cyber-attacks may
significantly alter the design of the AM part, compromising its mechanical properties and …

A review on machine learning, big data analytics, and design for additive manufacturing for aerospace applications

S Chinchanikar, AA Shaikh - Journal of Materials Engineering and …, 2022 - Springer
Additive manufacturing (AM) has emerged as a promising technology to cater to the
increasing demand for the fabrication of multi-functional, multi-material, and complex parts …

Correlating in-situ sensor data to defect locations and part quality for additively manufactured parts using machine learning

Z Snow, EW Reutzel, J Petrich - Journal of Materials Processing …, 2022 - Elsevier
In this work, process monitoring data, including layerwise imagery, multi-spectral emissions,
and laser scan vector data, were collected during laser-based powder bed fusion additive …