Metal Forming Process Efficiency Improvement Based on AI Services
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-57496-2_17
Reference16 articles.
1. Liu, C., Zheng, P., Xu, X.: Digitalisation and servitisation of machine tools in the era of Industry 4.0: a review. Int. J. Prod. Res. 61(12), 4069–4101 (2021). https://doi.org/10.1080/00207543.2021.1969462
2. Stavropoulos, P., Sabatakakis, K., Papacharalampopoulos, A., Mourtzis, D.: Infrared (IR) quality assessment of robotized resistance spot welding based on machine learning. Int. J. Adv. Manuf. Technol. 119, 1785–1806 (2022)
3. Stavropoulos, P., Papacharalampopoulos, A., Sabatakakis, K.: Online quality inspection approach for submerged arc welding (SAW) by utilizing IR-RGB multimodal monitoring and deep learning. In: Kim, KY., Monplaisir, L., Rickli, J. (eds.) International Conference on Flexible Automation and Intelligent Manufacturing. LNME, pp. 160–169. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-18326-3_16
4. Li, Y., et al.: A review on the recent development of incremental sheet-forming process. Int. J. Adv. Manuf. Technol. 92(5–8), 2439–2462 (2017). https://doi.org/10.1007/S00170-017-0251-Z
5. Ajay, C.V., Boopathi, C., Kavin, P.: Incremental sheet metal forming (ISMF): a literature review. In: AIP Conference Proceedings, vol. 2128, p. 030012. AIP Publishing LLC (2019)
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