A Statistical-Based Model of Roll Force During Commercial Hot Rolling of Steel

This research introduces a new model to predict the roll force during hot rolling of steel, based on a statistical analysis of approximately 38,980 sets of measurements in a commercial mill with five finishing stands. The study includes ten different steel grades and features models of both single grades and the entire dataset. Three models are developed and compared: a temperature-dependent strain rate model (M1), a strain rate model (M2), and a simplified strain rate model (M3). The decrease in temperature with roll stand has a strong cross-correlation with compensating decreases in strain and contact length by roll stand, such that both the temperature and strain terms are statistically insignificant. The final model (M3)—F[N]=113.1·ϵ˙[s−1]0.3141·w[mm]·ℓ[mm]—relates force (F) to strain rate (ϵ˙), width (w), and contact length (ℓ) and achieves an R2 fit of 0.946 over all 10 steel grades. Although the single-grade models show slightly higher accuracy, the final model retains robust predictive capability with only two fitting parameters. This model enables fast and easy estimation of roll force for commercial hot rolling of low-carbon, medium-carbon, and high-strength–low-alloy steels.

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Publication Details

Journal
Metals
Published
2025-12-08
DOI
https://doi.org/10.3390/met15121346
Primary Topic
Metallurgy and Material Forming
Type
article
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article

A Statistical-Based Model of Roll Force During Commercial Hot Rolling of Steel

Luke Messer, Alexandra M. Newman, Emmanuel Udofia, Brian G. Thomas et al.
Metals
Metallurgy and Material Forming
article

A Statistical-Based Model of Roll Force During Commercial Hot Rolling of Steel

Luke Messer, Alexandra M. Newman, Emmanuel Udofia, Brian G. Thomas, Gus Greivel
article en

Abstract

This research introduces a new model to predict the roll force during hot rolling of steel, based on a statistical analysis of approximately 38,980 sets of measurements in a commercial mill with five finishing stands. The study includes ten different steel grades and features models of both single grades and the entire dataset. Three models are developed and compared: a temperature-dependent strain rate model (M1), a strain rate model (M2), and a simplified strain rate model (M3). The decrease in temperature with roll stand has a strong cross-correlation with compensating decreases in strain and contact length by roll stand, such that both the temperature and strain terms are statistically insignificant. The final model (M3)—F[N]=113.1·ϵ˙[s−1]0.3141·w[mm]·ℓ[mm]—relates force (F) to strain rate (ϵ˙), width (w), and contact length (ℓ) and achieves an R2 fit of 0.946 over all 10 steel grades. Although the single-grade models show slightly higher accuracy, the final model retains robust predictive capability with only two fitting parameters. This model enables fast and easy estimation of roll force for commercial hot rolling of low-carbon, medium-carbon, and high-strength–low-alloy steels.

MetalsVol. 15(12)
Colorado School of Mines (US)
Openalex Percentile: Top 57%
Metallurgy and Material Forming
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A Statistical-Based Model of Roll Force During Commercial Hot Rolling of Steel — Luke Messer, Alexandra M. Newman, et al. · Metals (2025) | TGRS Research Map | TGRS