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On the Implementation of Neural Network Concept to Optimize Thermal Spray Deposition Process

Published online by Cambridge University Press:  17 March 2011

Sofiane Guessasma,
Ghislain Montavon and
Christian Coddet
Sofiane Guessasma
Affiliation:
LERMPS, Université de Technologie de Belfort-Montbéliard 90 010 Belfort Cedex, France
Ghislain Montavon
Affiliation:
LERMPS, Université de Technologie de Belfort-Montbéliard 90 010 Belfort Cedex, France
Christian Coddet
Affiliation:
LERMPS, Université de Technologie de Belfort-Montbéliard 90 010 Belfort Cedex, France
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Abstract

Numerous processing parameters, up to fifty, characterize the plasma spray deposition process. A better quality control of the resulting deposits induces a better understanding of their effects on coating formation mechanisms. Numerical models can help to provide such an understanding. From a mathematical point of view, d.c. plasma spray deposition process is assimilated to a nonlinear problem in regards to its variables (operating parameters, environment, etc.). This paper develops a global approach based on an implicit describing of the mechanisms implementing Artificial Neural Networks (ANNs). The global concept and the protocols to implement are presented and developed for an example related to d.c. plasma spray process.

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