Simulation of technological process by usage neural networks and factorial design of experiments

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F16%3A00000830" target="_blank" >RIV/75081431:_____/16:00000830 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Simulation of technological process by usage neural networks and factorial design of experiments
Original language description
The possibilities of simulation of technological process ofaluminium anodic oxidation using the methodology of Design of Experiments (DOE) and theory of neural networks in order to monitor the anodizing process under various operating conditions are presented in this paper. The influence of chemical and physical input factors on the resulting AAO (anodic aluminium oxide) layer thickness at applied current density of 1 A x dm-2 and 6 A x dm-2 has been investigated. Based on the evaluation of experimentally obtained data, the computational predictive model describing the effect of individual input factors and their mutual interactions on the AAO layer thickness was developed in the form of cubic function. This model indicates which factors are important and how they combine to influence the response, it will enable us to optimize operating conditions. The most significant benefit of our research work in this field is the fact that all relevant factors were varied simultaneously.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JR - Other machinery industry
OECD FORD branch
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Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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