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Erschienen in: Journal of Materials Engineering and Performance 2/2021

05.01.2021

Reducing Crop Length of Rolling Material Using Predictive Model Analysis

verfasst von: Hyungjin Kim, Donghwan Kim

Erschienen in: Journal of Materials Engineering and Performance | Ausgabe 2/2021

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Abstract

In steel bar rolling, molten metal in the casting process is solidified into a bloom with a large square cross section, which is then made into a billet. Management of the process yield during rolling is very important. In particular, the length and weight of the crop generated at the front/rear end of the material during rolling vary; however, various studies are being conducted to reduce this to 1% of the actual material yield. In this study, we investigated the factors influencing the crop fish tail and identified new operating parameters to derive optimal operating conditions. In particular, to predict the crop length, we conducted several predictive model analyses to identify the factors affecting the crop length. We investigated the factors related to the length of the crop fish tail, established a length prediction model based on correlation, and optimized the operating conditions based on the prediction model. The upper and lower layers of the furnace soaking zone for the hard steel bloom were operated at 1473, 30 K lower than the existing 1503 K. As a result, the length of the crop fish tail was 147.3 mm, shortened by approximately 13.1 mm, compared to the existing 160.4 mm.

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Metadaten
Titel
Reducing Crop Length of Rolling Material Using Predictive Model Analysis
verfasst von
Hyungjin Kim
Donghwan Kim
Publikationsdatum
05.01.2021
Verlag
Springer US
Erschienen in
Journal of Materials Engineering and Performance / Ausgabe 2/2021
Print ISSN: 1059-9495
Elektronische ISSN: 1544-1024
DOI
https://doi.org/10.1007/s11665-020-05405-5

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