Abstract
This paper presents a residual stress prediction model for high-speed machining using the finite element method in conjunction with neural network. The finite element method is utilized to simulate a chip formation process, which is constituted step by step from the workpiece removal process under the conditions of high-speed machining. The residual stress distributions underneath the machined surface of the workpiece are determined subsequently. The artificial neural network is in turn applied to synthesize the data calculated from the finite element method and a prediction model for residual stress distributions within the machined subsurface of the workpiece is thus constructed. The model can predict the residual stress distributions at different locations beneath the machined surface of the workpiece for various workpiece materials under different combinations of cutting conditions such as cutting speed, feed rate, rake angle and edge radius of the tool more effectively.
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