Prediction of EDMed micro-hole quality characteristics using hybrid bio-inspired machine learning-based predictive approaches
Author:
Publisher
Springer Science and Business Media LLC
Subject
Industrial and Manufacturing Engineering,Modeling and Simulation
Link
https://link.springer.com/content/pdf/10.1007/s12008-022-01117-3.pdf
Reference47 articles.
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3. Hribersek, M., Pusavec, F., Rech, J., Kopac, J.: Modeling of machined surface characteristics in cryogenic orthogonal turning of inconel 718. Mach. Sci. Technol. 22(5), 829–850 (2018). https://doi.org/10.1080/10910344.2017.1415935
4. Khanna, N., Agrawal, C., Gupta, M.K., Song, Q.: Tool wear and hole quality evaluation in cryogenic drilling of Inconel 718 superalloy. Tribol. Int. 143, 106084 (2020). https://doi.org/10.1016/j.triboint.2019.106084
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