English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

The possibilities of simulation of technological processofaluminium anodic oxidation using the methodology of Design ofExperiments (DOE) and theory of neural networks in order tomonitor the anodizing process under various operatingconditions are presented in this paper. The influence ofchemical and physical input factors on the resulting AAO(anodic aluminium oxide) layer thickness at applied currentdensity of 1 A x dm-2 and 6 A x dm-2 has been investigated.Based on the evaluation of experimentally obtained data, thecomputational predictive model describing the effect ofindividual input factors and their mutual interactions on theAAO layer thickness was developed in the form of cubicfunction. This model indicates which factors are important andhow they combine to influence the response, it will enable usto optimize operating conditions. The most significant benefitof our research work in this field is the fact that allrelevant factors were varied simultaneously.

SIMULATION OF TECHNOLOGICAL PROCESS BY USAGE NEURAL NETWORKS AND FACTORIAL DESIGN OF EXPERIMENTS