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| Description
| - Though in the metallurgical industry power saving continuous steel casting is more preferred compared to die casting, production of ingots of bigger sizes represents still an inconsiderable part of production. Especially the large weight of ingots leads to an effort to increase a part of high - quality production. At some types of ingots technological deviations exhibit by defects, which occur as late as in the process of forging. Prediction of such defects would enable a fast intervention and thus reducing costs for the reparation. Statistically was proven, that the defects are not caused by exceeding of any measured parameter in the production. However, they are caused by an unsuitable combination of more parameters. In such case artificial intelligence elements can be successfully applied. A multilayer artificial neural network was used for the prediction of defective ingots. Results, which were reached at prediction with neural network, are very interesting. In some cases even 100% accordance occu
- Though in the metallurgical industry power saving continuous steel casting is more preferred compared to die casting, production of ingots of bigger sizes represents still an inconsiderable part of production. Especially the large weight of ingots leads to an effort to increase a part of high - quality production. At some types of ingots technological deviations exhibit by defects, which occur as late as in the process of forging. Prediction of such defects would enable a fast intervention and thus reducing costs for the reparation. Statistically was proven, that the defects are not caused by exceeding of any measured parameter in the production. However, they are caused by an unsuitable combination of more parameters. In such case artificial intelligence elements can be successfully applied. A multilayer artificial neural network was used for the prediction of defective ingots. Results, which were reached at prediction with neural network, are very interesting. In some cases even 100% accordance occu (en)
- I když se v metalurgickém průmyslu více upřednostňuje energeticky úspornější plynulé odlévání oceli oproti lití do kokil, výroba ingotů větších rozměru určena především pro kovárny představuje stále nezanedbatelnou část výroby. Právě značná hmotnost ingotů vede ke snaze zvýšit podíl kvalitní produkce. U některých typů ingotů se projevují technologické odchylky vadami, které se projeví až v procesu kování. Predikce takovýchto vad by umožnila s předstihem zasáhnout a tím snížit náklady na nápravu. Statisticky bylo zjištěno, že vady nejsou způsobeny překročením žádného měřeného parametru ve výrobě. Jsou však způsobeny nevhodnou kombinací více parametrů. V takovém případě mohou být úspěšně aplikovány prvky umělé inteligence. Pro predikci vadných ingotů byla použita vícevrstvá umělá neuronová síť. Výsledky, které byly dosaženy při predikci s neuronovou sítí, jsou velmi zajímavé. V některých případech docházelo až ke 100% shodě. Daná problematika byla řešena v rámci grantového projektu GAČR 106/05/2596 (cs)
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| Title
| - Exploitation of Artificial Intelligence Elements for Prediction of Defects of Forging Ingots
- Exploitation of Artificial Intelligence Elements for Prediction of Defects of Forging Ingots (en)
- Využití prvků umělé inteligence pro predikci vad kovárenských ingotů (cs)
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| skos:prefLabel
| - Exploitation of Artificial Intelligence Elements for Prediction of Defects of Forging Ingots
- Exploitation of Artificial Intelligence Elements for Prediction of Defects of Forging Ingots (en)
- Využití prvků umělé inteligence pro predikci vad kovárenských ingotů (cs)
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| skos:notation
| - RIV/61989100:27360/06:00014225!RIV07-GA0-27360___
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| http://linked.open.../vavai/riv/strany
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| http://linked.open...avai/riv/aktivita
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| http://linked.open...avai/riv/aktivity
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| http://linked.open...vai/riv/dodaniDat
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| http://linked.open...aciTvurceVysledku
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| http://linked.open.../riv/druhVysledku
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| http://linked.open...iv/duvernostUdaju
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| http://linked.open...titaPredkladatele
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| http://linked.open...dnocenehoVysledku
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| http://linked.open...ai/riv/idVysledku
| - RIV/61989100:27360/06:00014225
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| http://linked.open...riv/jazykVysledku
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| http://linked.open.../riv/klicovaSlova
| - neural networks; prediction; modeling; formability; ingots (en)
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| http://linked.open.../riv/klicoveSlovo
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| http://linked.open...ontrolniKodProRIV
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| http://linked.open...i/riv/mistoVydani
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| http://linked.open...i/riv/nazevZdroje
| - Sborník Simulation, Designing and Control of Foundry processes
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| http://linked.open...in/vavai/riv/obor
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| http://linked.open...ichTvurcuVysledku
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| http://linked.open...cetTvurcuVysledku
| |
| http://linked.open...vavai/riv/projekt
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| http://linked.open...UplatneniVysledku
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| http://linked.open...iv/tvurceVysledku
| - Jančíková, Zora
- Heger, Milan
|
| number of pages
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| http://purl.org/ne...btex#hasPublisher
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| https://schema.org/isbn
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| http://localhost/t...ganizacniJednotka
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| is http://linked.open...avai/riv/vysledek
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