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  • Production of ingots of bigger sizes which are designed above all for forges represents an inconsiderable part of production in the metallurgical industry. At some types of ingots technological deviations exhibit by defects which occur as late as in the forging process. Timely prediction of such defects would enable a fast intervention to the instant process and thus reduce costs for the reparation. Statistically was proved 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. Even 100% accordance of predicted and actual values occurred in some cases.
  • Production of ingots of bigger sizes which are designed above all for forges represents an inconsiderable part of production in the metallurgical industry. At some types of ingots technological deviations exhibit by defects which occur as late as in the forging process. Timely prediction of such defects would enable a fast intervention to the instant process and thus reduce costs for the reparation. Statistically was proved 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. Even 100% accordance of predicted and actual values occurred in some cases. (en)
  • Výroba ingotů větších rozměrů, které jsou určeny především pro kovárny, představuje v metalurgickém průmyslu nezanedbatelnou část výroby. U některých typů ingotů se projevují technologické odchylky vadami, které se projeví až v procesu kování. Statisticky bylo zjištěno, že vady nejsou způsobeny překročením žádného měřeného parametru ve výrobě. Jsou však způsobeny nevhodnou kombinací více parametrů. Pro predikci vadných ingotů byly úspěšně aplikovány umělé neuronové sítě. V některých případech docházelo až ke 100% shodě predikovaných a skutečných hodnot. (cs)
Title
  • Investigation of Causes of the Forge Ingots Impaired Formability with Artificial Intelligence Elements Exploitation
  • Výzkum příčin zhoršené tvařitelnosti kovárenských ingotů s využitím prvků umělé inteligence (cs)
  • Investigation of Causes of the Forge Ingots Impaired Formability with Artificial Intelligence Elements Exploitation (en)
skos:prefLabel
  • Investigation of Causes of the Forge Ingots Impaired Formability with Artificial Intelligence Elements Exploitation
  • Výzkum příčin zhoršené tvařitelnosti kovárenských ingotů s využitím prvků umělé inteligence (cs)
  • Investigation of Causes of the Forge Ingots Impaired Formability with Artificial Intelligence Elements Exploitation (en)
skos:notation
  • RIV/61989100:27360/07:00016103!RIV09-GA0-27360___
http://linked.open...avai/riv/aktivita
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  • P(GA106/05/2596)
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  • 427457
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  • RIV/61989100:27360/07:00016103
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  • networks; prediction; modeling; formability; ingots (en)
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  • [712EABDD8494]
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  • Štrbské Pleso, Slovenská republika
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  • Košice
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  • Proceedings of 8th International Carpathian Control Conference ICCC?2007
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  • Jančíková, Zora
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  • Technická univerzita v Košiciach
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  • 978-80-8073-805-1
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  • 27360
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