Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
795287 | Journal of Materials Processing Technology | 2008 | 12 Pages |
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 author's present workâprediction of surface profile using RBF neural network and future trend are also introduced.