| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1604836 | International Journal of Refractory Metals and Hard Materials | 2006 | 7 Pages |
Abstract
Pin-on-disc tests were performed on alumina-13Â wt.% titania coatings obtained under several APS conditions. Friction coefficient data were analysed using artificial neural network. This permitted to predict parameter ranges for which good wear resistance is possible when varying each of the process parameters individually with respect to a reference condition. In this case, results suggest that large parameter ranges did not permit to obtain a significant friction coefficient variation which was mainly between 0.51 and 0.61. In addition, injection parameters and total plasma gas flow rate were the control factors.
Related Topics
Physical Sciences and Engineering
Materials Science
Metals and Alloys
Authors
Sofiane Guessasma, Mokhtar Bounazef, Philippe Nardin,