<p>Roll forming is a material processing technology widely used in industry, especially within the automotive production. Resorting to some new materials promotes the innovation in processing techniques to increase product quality. Therefore, a precise prediction of process outcomes is required. Despite the progress in rolling mill design, a practical modeling approach to investigate shape and geometry of rolled product has been not yet assessed. The highly nonlinear behavior of material motivates setting up either time-consuming numerical analyses or some simplified approaches, still looking poorly reliable. In this paper, a numerical modeling technique aimed at predicting the properties of rolled product more than mill behavior has been conceived and tested to allow manufacturer performing a preliminary calibration of product line. Particularly, a real industrial case has been analyzed by focusing on three roll forming lines, with “U,” “W,” and “HAT” cross-section, respectively. The first two shapes have been exploited to experimentally validate the numerical model. The “U” line validation performed on the folded edges distance showed a relative systematic deviation of 1.44% and a dispersion of the relative error of <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="170_2025_16140_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="58" /> </InlineMediaObject> <EquationSource Format="TEX">$\pm 0.56\%$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo>±</mo> <mn>0.56</mn> <mo>%</mo> </mrow> </math></EquationSource> </InlineEquation>. For the “W” line, the validation performed on crucial lengths and angles of the cross-section exhibited an average relative error of 0.13% and <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="170_2025_16140_Article_IEq2.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="19" /> </InlineMediaObject> <EquationSource Format="TEX">$-$</EquationSource> <EquationSource Format="MATHML"><math> <mo>-</mo> </math></EquationSource> </InlineEquation>0.02%, respectively. The validated numerical approach has been exploited to predict the mill performance in manufacturing the “HAT” profile, still under development. This activity aimed at providing the designer a tool to predict the process performance and assessing the system layout.</p>

Set-up and validation of numerical modeling techniques to simulate the cold roll forming of martensitic and high strength steel

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发表日期：

2025年7月23日

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Edoardo Masoero,
Cristiana Delprete,
Lorenzo Giorio,
Giacomo Maculotti,
Eugenio Brusa,
Luca Caneparo

摘要

Roll forming is a material processing technology widely used in industry, especially within the automotive production. Resorting to some new materials promotes the innovation in processing techniques to increase product quality. Therefore, a precise prediction of process outcomes is required. Despite the progress in rolling mill design, a practical modeling approach to investigate shape and geometry of rolled product has been not yet assessed. The highly nonlinear behavior of material motivates setting up either time-consuming numerical analyses or some simplified approaches, still looking poorly reliable. In this paper, a numerical modeling technique aimed at predicting the properties of rolled product more than mill behavior has been conceived and tested to allow manufacturer performing a preliminary calibration of product line. Particularly, a real industrial case has been analyzed by focusing on three roll forming lines, with “U,” “W,” and “HAT” cross-section, respectively. The first two shapes have been exploited to experimentally validate the numerical model. The “U” line validation performed on the folded edges distance showed a relative systematic deviation of 1.44% and a dispersion of the relative error of $\pm 0.56\%$ $\pm 0.56 %$ . For the “W” line, the validation performed on crucial lengths and angles of the cross-section exhibited an average relative error of 0.13% and $-$ $-$ 0.02%, respectively. The validated numerical approach has been exploited to predict the mill performance in manufacturing the “HAT” profile, still under development. This activity aimed at providing the designer a tool to predict the process performance and assessing the system layout.