WIT Press


Wear Prediction Of Hot Working Tools

Price

Free (open access)

Paper DOI

10.2495/CON990401

Volume

24

Pages

10

Published

1999

Size

998 kb

Author(s)

M. Tercelj, R. Turk & I. Perus

Abstract

The method of CAE neural network was used to predict the wear of hot forging tool. The data base for prediction consisted of experimental observations of the laboratory simulation of tribomechanical and tribotemperature conditions on the locally most loaded part of the forging tool during the application. Individual influence variables on the wear were computed by FEM. The laboratory simulation of the tool wear was performed on a module which was developed separately as appendix for the GLEEBLE 1500 simulator. The ability of CAE has shown to be vital in the prediction of wear on the basis of experimental phenomena

Keywords