[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 …

Research and application of artificial intelligence techniques for wire arc additive manufacturing: a state-of-the-art review

F He, L Yuan, H Mu, M Ros, D Ding, Z Pan… - Robotics and Computer …, 2023 - Elsevier
Recent development in the Wire arc additive manufacturing (WAAM) provides a promising
alternative for fabricating high value-added medium to large metal components for many …

Federated learning-based semantic segmentation for pixel-wise defect detection in additive manufacturing

M Mehta, C Shao - Journal of Manufacturing Systems, 2022 - Elsevier
Semantic segmentation is a promising machine learning (ML) method for highly precise fine-
scale defect detection and part qualification in additive manufacturing (AM). Most existing …

Applying machine learning to wire arc additive manufacturing: a systematic data-driven literature review

A Hamrani, A Agarwal, A Allouhi… - Journal of Intelligent …, 2024 - Springer
Due to its unique benefits over standard conventional “subtractive” manufacturing, additive
manufacturing is attracting growing interest in academic and industrial sectors. Here, special …

Deep learning-based welding image recognition: A comprehensive review

T Liu, P Zheng, J Bao - Journal of Manufacturing Systems, 2023 - Elsevier
The reliability and accuracy of welding image recognition (WIR) is critical, which can largely
improve domain experts' insight of the welding system. To ensure its performance, deep …

A Survey of Image-Based Fault Monitoring in Additive Manufacturing: Recent Developments and Future Directions

RG Kim, M Abisado, J Villaverde, GA Sampedro - Sensors, 2023 - mdpi.com
Additive manufacturing (AM) has emerged as a transformative technology for various
industries, enabling the production of complex and customized parts. However, ensuring the …

[HTML][HTML] High geometric fidelity through closed-loop control of the weld pool size in gas metal arc welding based direct energy deposition

M Scheck, A Richter, S Beitler, T Gehling, K Treutler… - Additive …, 2024 - Elsevier
Arc based direct energy deposition combines the flexibility of additive manufacturing with
high build rates and low investment costs. However, high geometric fidelity of manufactured …

Deep learning-based framework for the observation of real-time melt pool and detection of anomaly in wire-arc additive manufacturing

M Chandra, S Rajak, V KEK - Materials and Manufacturing …, 2024 - Taylor & Francis
Object detection has become a popular tool of deep learning in the era of digital
manufacturing. In this study, the most powerful and efficient object detection algorithm, ie …

Deep learning-based image segmentation for defect detection in additive manufacturing: An overview

S Deshpande, V Venugopal, M Kumar… - The International Journal …, 2024 - Springer
Additive manufacturing (AM) applications are rapidly expanding across multiple domains
and are not limited to prototyping purposes. However, achieving flawless parts in medical …

Indirect porosity detection and root-cause identification in WAAM

JYII Alcaraz, W Foqué, A Sharma… - Journal of Intelligent …, 2024 - Springer
Due to the complexity of the Wire-arc Additive Manufacturing (WAAM) process, it is prone to
the occurrence of defects in the product. One of the most common defects is porosity, which …