| Autor: |
Rudy, Vladimír, Malega, Peter, Daneshjo, Naqib, Kováč, Juraj |
| Předmět: |
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| Zdroj: |
Advances in Science & Technology Research Journal; 2022, Vol. 16 Issue 5, p271-276, 6p |
| Abstrakt: |
This article discusses a predictive quality management system that aims to eliminate repair technologies by exploiting the cognitive capability of manufacturing facilities in the manufacturing process. During production, deviations from the required quality parameters such as strip flatness, strip profile, and non-achievement of the required mechanical properties of dimensional variations occur, and their correction or correction requires repair technologies beyond the standard processes. The metallurgical process itself is energy and financially demanding. Repairing technologies represent added production costs and environmental burdens not only in the form of high-energy consumption but also in the production of harmful substances that have a negative impact on the environment. The production of solid dust impurities, the production of gaseous exhalations, high water consumption, environmental warming and water pollution, and the formation of slag ash are just a few negative aspects of metallurgical production. Steel producers make great efforts to achieve the required quality parameters and reduce the cost of repair technologies. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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