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

Kód výsledku v 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>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JR - Ostatní strojírenství

OECD FORD obor

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Projekt

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Návaznosti

R - Projekt Ramcoveho programu EK

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

MM Science Journal

ISSN

1803-1269

e-ISSN

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Svazek periodika

Neuveden

Číslo periodika v rámci svazku

September 2016

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

5

Strana od-do

999-1003

Kód UT WoS článku

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EID výsledku v databázi Scopus

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