Artificial neural network-based prediction technique for wear loss quantities in Mo coatings

Çetinel H.; Öztürk H.; Çelik E.; Karlik B.

Artificial neural network-based prediction technique for wear loss quantities in Mo coatings

Date

2006

Authors

Çetinel H.

Öztürk H.

Çelik E.

Karlik B.

Abstract

Mo coated materials are used in automotive, aerospace, pulp and paper industries in order to protect machine parts against wear and corrosion. In this study, the wear amounts of Mo coatings deposited on ductile iron substrates using an atmospheric plasma-spray system were investigated for different loads and environment conditions. The Mo coatings were subjected to sliding wear against AISI 303 counter bodies under dry and acid environments. In a theoretical study, cross-sectional microhardness from the surface of the coatings, loads, environment and friction test durations were chosen as variable parameters in order to determine the amount of wear loss. The numerical results obtained via a neural network model were compared with the experimental results. Agreement between the experimental and numerical results is reasonably good. © 2006 Elsevier B.V. All rights reserved.

Keywords

Friction, Mathematical models, Molybdenum, Neural networks, Plasma spraying, Sprayed coatings, Wear of materials, Friction, Mathematical models, Molybdenum, Neural networks, Plasma spraying, Wear of materials, Mo coatings, Neural network model, Sprayed coatings