Applying machine learning to wire arc additive manufacturing: a systematic data-driven literature review
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DOI: 10.1007/s10845-023-02171-8
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References listed on IDEAS
- Manuel Dias & João P. M. Pragana & Bruna Ferreira & Inês Ribeiro & Carlos M. A. Silva, 2022. "Economic and Environmental Potential of Wire-Arc Additive Manufacturing," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
- Chunyang Xia & Zengxi Pan & Joseph Polden & Huijun Li & Yanling Xu & Shanben Chen, 2022. "Modelling and prediction of surface roughness in wire arc additive manufacturing using machine learning," Journal of Intelligent Manufacturing, Springer, vol. 33(5), pages 1467-1482, June.
- Ohyung Kwon & Hyung Giun Kim & Min Ji Ham & Wonrae Kim & Gun-Hee Kim & Jae-Hyung Cho & Nam Il Kim & Kangil Kim, 2020. "A deep neural network for classification of melt-pool images in metal additive manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 31(2), pages 375-386, February.
- Jian Qin & Yipeng Wang & Jialuo Ding & Stewart Williams, 2022. "Optimal droplet transfer mode maintenance for wire + arc additive manufacturing (WAAM) based on deep learning," Journal of Intelligent Manufacturing, Springer, vol. 33(7), pages 2179-2191, October.
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Keywords
Additive manufacturing; Wire arc additive manufacturing; Artificial intelligence; Machine learning;All these keywords.
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