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ORGANIZER;CN=ESTAD 2023:mailto:info@metec-estad.com
LOCATION:Room 28
SUMMARY:Reduce cobble risk in hot strip mills with real-time data analytics
DESCRIPTION:This paper presents a method for minimizing the formation of cobbles in hot strip mills using data analytics, which was successfully implemented and proven in real-life production. The paper provides learnings from the implementation of this use case. Cobbles can cause significant damage, safety issues and production delays, resulting in financial losses. By analyzing data from various sources, patterns and trends in the production process that lead to cobbles can be identified. Using this information, real-time recommendations are provided to the process engineers and operators, who can then make adjustments to the process to prevent the formation of cobbles and improve overall efficiency. The results of the data analysis, implementation of preventative measures, and the real-life production are discussed, showing a reduction in the occurrence of cobbles and an improvement in overall efficiency. The paper concludes by providing valuable insights and learnings that can be applied to similar use cases, and how the use of data analytics, coupled with real-time recommendations, is a powerful and effective tool for identifying and mitigating the causes of production issues in hot strip mills.


CLASS:PUBLIC
DTSTART:20230614T141000
DTEND:20230614T143000
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