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- W2183635964 abstract "Milling is the one of machining processes which is widely used in manufacturing and its cross-section temperature has a great influence on the tool lifetime and the surface quality. Therefore, determination of section temperature before the process has a vital role. In the present study, temperature of milling cross-section is determined by Neural Networks. Neural networks are used because these methods are very fast respect than other methods. Numerical model of the work-piece is provided and governing equations are solved using finite volume approach. Obtained results are used as the database to train the neural network. Position of nodes and milling blade size are set as input and temperature of milling surface is set as the target of the network. Finally, comparison is performed among the soft-computing and experimental measurements. It is show that soft-computing code can be used more efficiently and to determine the temperature in a milling process." @default.
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- W2183635964 date "2012-01-01" @default.
- W2183635964 modified "2023-09-27" @default.
- W2183635964 title "Prediction of Cross-Section Temperature During Milling Process Using Artificial Neural Networks" @default.
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