Optimization and Modelling of Machining Parameters in End Milling Operation Using Box-Behnken Technique
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-2716-2_43
Reference15 articles.
1. Dikshit, M.K., Puri, A.B., Maity, A., Banerjee, A.J.: Analysis of cutting forces and optimization of cutting parameters in high speed ball-end milling using response surface methodology and genetic algorithm. Procedia Mater. Sci. 5, 1623–1632 (2014)
2. Daniyan, I.A., Tlhabadira, I., Daramola, O.O., Phokobye, S.N., Siviwe, M., Mpofu, K.: Measurement and optimization of cutting forces during M200 TS milling process using the response surface methodology and dynamometer. Procedia CIRP 88, 288–293 (2020)
3. Kilickap, E., Yardimeden, A., Çelik, Y.H.: Mathematical modelling and optimization of cutting force, tool wear and surface roughness by using artificial neural network and response surface methodology in milling of Ti-6242S. Appl. Sci. 7(10) (2017)
4. Subramanian, M., Sakthivel, M., Sooryaprakash, K., Sudhakaran, R.: Optimization of cutting parameters for cutting force in shoulder milling of Al7075-T6 using response surface methodology and genetic algorithm. Procedia Eng. 64, 690–700 (2013)
5. Jeyakumar, S., Marimuthu, K., Ramachandran, T.: Prediction of cutting force, tool wear and surface roughness of Al6061/SiC composite for end milling operations using RSM. J. Mech. Sci. Technol. 27(9), 2813–2822 (2013)
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