The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Bead geometry prediction for robotic GMAW-based rapid manufacturing through a neural network and a second-order regression analysis
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Citations
Cites
Design and Analysis of Experiments.
Kupper, L. L., & Montgomery, D. C. (1978) · Journal of the American Statistical Association · doi:10.2307/2286559 · Cited by 1,728
Design and Analysis of Industrial Experiments.
Freeman, H. A., Davies, O. L., Box, G. E. P., Connor, L. R., Cousins, W. R., Davies, O. L., Himsworth, F. R., & Sillitto, G. P. (1955) · Journal of the American Statistical Association · doi:10.2307/2280981 · Cited by 933
Low cost integration of additive and subtractive processes for hybrid layered manufacturing
Karunakaran, K. P., Suryakumar, S., Pushpa, V., & Akula, S. (2010) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2010.03.008 · Cited by 377
Process efficiency measurements in the laser engineered net shaping process
Unocic, R. R., & DuPont, J. N. (2004) · Metallurgical and Materials Transactions B · doi:10.1007/s11663-004-0104-7 · Cited by 144
Experimental investigations into rapid prototyping of composites by novel hybrid deposition process
Song, Y., & Park, S. (2005) · Journal of Materials Processing Technology · doi:10.1016/j.jmatprotec.2005.06.062 · Cited by 121
Doumanidis, C. C., & Kwak, Y.-M. (2002) · International Journal of Pressure Vessels and Piping · doi:10.1016/s0308-0161(02)00024-8 · Cited by 96
Lin, H.-L. (2010) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-010-0468-2 · Cited by 70
Cited by
Ding, D., Pan, Z., Cuiuri, D., & Li, H. (2015) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-015-7077-3 · Cited by 1,648
Building blocks for a digital twin of additive manufacturing
Knapp, G. L., Mukherjee, T., Zuback, J. S., Wei, H. L., Palmer, T. A., De, A., & DebRoy, T. (2017) · Acta Materialia · doi:10.1016/j.actamat.2017.06.039 · Cited by 414
Elahi, M., Afolaranmi, S. O., Martinez Lastra, J. L., & Perez Garcia, J. A. (2023) · Discover Artificial Intelligence · doi:10.1007/s44163-023-00089-x · Cited by 303
Machine learning in predicting mechanical behavior of additively manufactured parts
Nasiri, S., & Khosravani, M. R. (2021) · Journal of Materials Research and Technology · doi:10.1016/j.jmrt.2021.07.004 · Cited by 202
Ukwaththa, J., Herath, S., & Meddage, D. P. P. (2024) · Materials Today Communications · doi:10.1016/j.mtcomm.2024.110294 · Cited by 118
Metadata
- Authors
- Xiong, J., Zhang, G., Hu, J., & Wu, L.
- Venue
- Journal of Intelligent Manufacturing
- Published
- 2012-07-19
- Volume
- 25
- Issue
- 1
- Pages
- 157-163
- ISSN
- 0956-5515 (ISSN-L)
- 1572-8145
- OpenAlex
- W1982514318
- Cited by
- 324
- References
- 7
- FWCI
- 10.29
- Type
- journal article
- Language
- en
- Open access
- closed
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Bead geometry prediction for robotic GMAW-based rapid manufacturing through a neural network and a second-order regression analysis. https://app.cochat.ai/papers/10.1007/s10845-012-0682-1
- The paper
- Xiong, J., Zhang, G., Hu, J., & Wu, L. (2014). Bead geometry prediction for robotic GMAW-based rapid manufacturing through a neural network and a second-order regression analysis. Journal of Intelligent Manufacturing. https://doi.org/10.1007/s10845-012-0682-1
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
