Title of article :
Study on prediction of surface quality in machining process
Author/Authors :
Chen Lu، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2008
Abstract :
The surface profile and roughness of a machined workpiece are two of the most important product quality characteristics and in most cases a technical requirement for mechanical products. Achieving the desired surface quality is of great importance for the functional behavior of a part. The process-dependent nature of the surface quality mechanism along with the numerous uncontrollable factors that influence pertinent phenomena, make it important to find a straightforward solution and an absolutely accurate prediction model. Firstly, this paper reviews the methodologies and practice that are being employed for the prediction of surface profile and roughness, each approach with its advantages and disadvantages is summarized. Finally, the authorʹs present work—prediction of surface profile using RBF neural network and future trend are also introduced.
Keywords :
Surface profile prediction , Machining , Surface roughness prediction
Journal title :
Journal of Materials Processing Technology
Journal title :
Journal of Materials Processing Technology