Prediction of Cutting Force and Surface Roughness in Turning Using Machine Learning
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-42659-9_24
Reference17 articles.
1. Abdellaoui, L., Khlifi, H., Bouzid Sai, W.: Prediction of turning performances using an equivalent oblique cutting model. Int. J. Adv. Manuf. Technol. 120, 7735–7753 (2022). https://doi.org/10.1007/s00170-022-09243-8
2. Abdellaoui, L., Khlifi, H., Bouzid Sai, W., Hamdi, H.: Tool nose radius effects in turning process. Mach. Sci. Technol. 25, 1–30 (2020). https://doi.org/10.1080/10910344.2020.1815038
3. Alajmi, M.S., Almeshal, A.M.: Modeling of cutting force in the turning of AISI 4340 using gaussian process regression algorithm. Appl. Sci. 11, 4055 (2021). https://doi.org/10.3390/app11094055
4. Beauchamp, Y., Thomas, M.: Investigation of cutting parameter effects on surface roughness in lathe boring operation by use of a full factorial design. Comput. Ind. 31, 645–651 (1996). https://doi.org/10.1016/S0360-8352(96)00234-3
5. Belguith, R., Khlifi, H., Sai, L., et al.: Effects of the tool bending on the cutting force in ball end milling. In: Lecture Notes in Mechanical Engineering, pp. 143–151 (2019)
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