Evolution of cold-rolling work roll materials based on the elucidation of the cracking mechanism of thermal shock

Warpage caused by uneven stress distribution is a critical issue limiting shape quality in rolling high‐strength thin strips with an S6‐high cold rolling mill. Owing to high yield strength and small thickness, such strips are sensitive to strain heterogeneity, while conventional methods cannot reveal the complex warpage mechanism. To address this, an elastoplastic finite element (FE) model of the mill‐strip system is developed and validated. Mechanistic analysis clarifies the effects of material and process parameters. A simulation database is established, and a synthetic warpage factor is proposed to quantify global and local trends. An intelligent prediction model is built using the White Shark Optimizer (WSO) optimized Light Gradient Boosting Machine (LightGBM). Results demonstrate that strip thickness and yield strength are intrinsic sources of warpage sensitivity, while work roll misalignment and side support roll position are key inducing factors. Compared with conventional methods, WSO‐LightGBM achieves superior accuracy ( R 2 = 0.963, RMSE = 0.00109 mm, MAE = 0.00191 mm). This study confirms the applicability of mechanism‐data fusion for accurate prediction and process optimization.

ABSTRACT In hot strip rolling, even moderate variations in transfer bar (TB) thickness can critically affect the final strip profile and surface quality. This study investigates the influence of roll wear in the last roughing stand (R5) on these inconsistencies by integrating plant measurements with finite element method (FEM) simulation. Work roll profiles were captured at different stages of a rolling campaign using a Pessometer. These profiles were precisely reconstructed using CAD software and incorporated into the FEM based DEFORM-3D simulation environment to reflect worn roll geometries within a thermo-mechanical framework. A comprehensive FEM model was developed to emulate real mill conditions; from slab discharge at the reheating furnace to deformation through the roughing stands and up to the third finishing stand, where the strip's geometric integrity, especially profile is predominantly established. Simulations conducted with varying degrees of R5 roll wear revealed that roll surface degradation induces non-uniform thickness distribution in the TB. These inconsistencies persist into the finishing mill and lead to shape-related defects such as ridge formation. This integrated approach not only helps to visualise the genesis of shape defect but also provides actionable insights into optimal roll maintenance schedules and control interventions to ensure more uniform strip production.

This paper investigates the nonlinear horizontal vibration of a cold rolling system induced by the gyroscope precession effect-a critical yet underexplored issue affecting strip quality and rolling stability. A nonlinear dynamic model is developed by incorporating the axial excitation force and the elastic deformation of the work roll based on d’Alembert principles. The primary parametric resonance response, corresponding to the first Arnold tongue, is analyzed using the multi-scale method and validated experimentally. To further understand the systematic dynamic behavior, the homotopy analysis method is employed to trace the evolution of energy orbits, revealing bifurcation and jump phenomena as the frequency ratio varies. A devil’s staircase pattern emerges, indicating multiple frequency-locked regions. These nonlinear features are further validated through cell mapping techniques, which depict the transformation of modal energy manifolds. Moreover, by introducing active control inputs, a constraint space for control parameters is designed to induce amplitude death within the maximum Arnold tongue region. The findings contribute to a deeper understanding of the resonance mechanism and offer a theoretical basis for stabilizing precision cold rolling systems via nonlinear control strategies.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-27552-2.

The study focuses on analyzing the effect of hot-rolled strip geometry and hot rolling parameters on the flatness of cold-rolled automotive sheet steel. Based on industrial data from a continuous hot rolling mill, a conditional quality indicator for the strip is developed. This indicator integrates the following parameters: minimum left and right wedge, crown shift, strip width, and the temperature difference between the end of rolling and coiling. It is established that profile asymmetry correlates with flatness defects, with median values of asymmetry for defective strips being 25...50 % higher than for defect-free strips. The importance of additional monitoring of key geometric parameters, particularly edge wedge and crown position, is substantiated. Limitations of active control systems — CVC (Continuously Variable Crown) roll shifting and WRB (Work Roll Bending) on the cold rolling mill — in correcting complex asymmetries of the incoming strip are demonstrated. The results confirm the need to adapt strip shape control algorithms and enhance monitoring of individual geometric parameters of the hot-rolled strip to minimize defects during galvanizing.

The flatness quality of cold-rolled strips is regarded as a crucial quality indicator within the production of steel strips. The accuracy of the bending forces applied to the work and intermediate rolls directly affects the control quality of the strip flatness. Traditional models are based on assumptions and parameter simplifications, which result in lower computational accuracy. To explore the relationship between various process parameters of the rolling process and their impact on the strip flatness, this article proposes a data-driven online setting model for bending force. The model integrates the isolation forest algorithm, sparrow search algorithm, and backpropagation neural network. To eliminate the disturbance caused by non-effective data on prediction results, the isolation forest algorithm is employed for outlier detection. Through these algorithms, the analysis, processing, and feature extraction of extensive measured rolling data are achieved, constructing a data model for the optimal setting. Finally, the validation process was conducted by employing acquired rolling datasets from a 1450-millimetre cold continuous rolling mill. The results demonstrate that the sparrow search algorithm and backpropagation model outperforms traditional roll deformation analysis methods and the standard backpropagation neural network model with respect to convergence speed, precision, and robustness.

This study employs the UCMW (Universal crown mill with work roll shifting) cold rolling mill as the research object, focusing on the critical process parameter of single-taper profiles for both the work roll and intermediate roll. By establishing an integrated finite element model of the roll-strip system, this analysis examines the influence patterns of single-taper profiles applied to the work roll, the intermediate roll, and their combined configuration on strip shape. The research demonstrates that when the work roll utilizes a single-taper profile, the strip shape approximates a rectangular profile at a shift amount of −75 mm and exhibits a concave profile at −95 mm. For the intermediate roll employing a single-taper profile, the strip shape manifests a convex profile within the shift range of −150 mm and transitions to an M-shape at −180 mm. Utilizing the combined roll profiles induces a gradual transition in strip shape from convex to concave within the shift range of −50 mm to −95 mm. Comparative analysis indicates that at a shift of −50 mm, the combined roll profiles yield a shape closer to rectangular; at −75 mm, the work roll profile produces superior results; at −95 mm, both the work roll profile and the combined profiles result in concave shapes, with the combined configuration exerting the most pronounced effect. This investigation furnishes a theoretical foundation for roll profile optimization in rolling mills and the enhancement of strip dimensional precision.

To produce flat cold rolled products with regulated surface roughness, work rolls with a certain initial roughness are used. However, natural variations in the initial roughness of the rolls between their replacements cause instability in the strips surface roughness.The variability of the black plate surface roughness between work rolls replacements in a two-stand skin-pass mill was studied. Variations in the black plate surface roughness were investigated due to different initial roughness of the work rolls from the first and second stands. At rational initial roughness of work rolls during the period between replacement of rolls, metal surface roughness corresponds to the range of efficient values, and root-mean-square error relative to some reasonable value is minimal.In order to display the variability of the mean sampled and extreme black plate surface roughness values between roll replacement, statistically reliable regression equations in the form of degree relationships were obtained.These equations were used to determine the initial roughness of the work rolls in the first and the second stands, which provide an efficient black plate surface roughness with minimal variation between roll replacement.To ensure efficient microgeometry of black plate during its tempering at two-stand skin-pass mill 500/1350×1200 in the first stand it is expedient to use work rolls after notching with initial roughness Ra = 1.5–2.5 µm, and in the second stand – polished work rolls with initial roughness Ra = 0.5–0.8 µm.

During the acceleration phase of continuous cold rolling mill production, transient transitions in rolling speed can lead to dynamic imbalance in the rolling force field. This imbalance induces fluctuations in strip thickness and shape distortions (such as edge waves, center waves, and other defects), which have become critical bottlenecks restricting the quality of high-end cold-rolled products and production line efficiency. Based on the ABAQUS platform, this study constructs a three-dimensional elastoplastic finite element model of a six-roll continuous cold rolling mill, systematically revealing how Work Roll Bending (WRB) and Intermediate Roll Bending (IRB) couple to affect the dynamic response of strip thickness distribution, flatness evolution, cross-sectional crown, and rolling force field. The results demonstrate that increasing WRB shifts the strip thickness distribution from “thick center, thin edges” to “thin center, thick edges,” significantly improving secondary wave defects. Increasing IRB promotes more uniform thickness distribution, but its control capability over quaternary wave defects is relatively weaker. Bending force effectively suppresses shape fluctuations by adjusting rolling force distribution and inter-roll pressure. For the acceleration process, a composite control strategy integrating dynamic bending force compensation and tension cooperative control is proposed, and a segmented speed interval optimization model is established. Simulations show that through segmented speed interval optimization and dynamic compensation, edge wave defects during the acceleration phase are reduced, and thickness uniformity is improved. Optimizing the strip production process during acceleration can effectively enhance production efficiency and reduce production losses. The research outcomes, by establishing a multi-objective coordinated dynamic shape control system, provide theoretical support and engineering implementation pathways for the intelligent process optimization of continuous cold rolling mills during acceleration.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-21834-5.

ABSTRACT Considering the effects of harmonic torque, rolling force, and disturbances, a dynamic model of the horizontal vibration of the work roll was established. To address the issues of excessive control input and severe vibration in traditional super-twisting algorithms, a novel adaptive super-twisting algorithm (NASTA) was proposed. A work roller displacement controller based on NASTA was designed. To improve the robustness of the control system, a sliding mode disturbance observer (SMDO) was designed to estimate system disturbances in real-time. At the same time, the observation results are dynamically compensated in the control system, forming a composite control strategy of NASTA + SMDO. The simulation and experimental results show that, compared with the Double Power Reaching Law (DPRL) and the Fast Power Reaching Law (FRPL), the response speed of the proposed NASTA + SMDO compound control strategy has increased by approximately 53% and 46%, respectively, reduces initial control input to 10% and 2% of DPRL and FPRL, and cuts steady-state error by 95% and 97%, respectively. The proposed strategy significantly enhances dynamic response, energy efficiency, and control accuracy, offering effective methods for vibration suppression in rolling mills.

The CVC (Continuously Variable Crown) work rolls of hot strip mills suffer from severe uneven wear, and traditional models for predicting work roll wear are difficult to adapt to this uneven wear, resulting in low prediction accuracy. Therefore, a CNN-BiLSTM-Attention + NSGA-II model based on the combination of theory and data is proposed, which can be used for high-precision prediction of CVC work roll wear. The CNN-BiLSTM-Attention intelligent algorithm model combines the advantages of each network layer to achieve higher wear prediction accuracy. The CNN layer comprehensively extracts features from rolling process data, the BiLSTM layer handles the bidirectional time-series characteristics of work roll wear over their service life, and the Attention focuses on key parameters influencing work roll wear. The NSGA-II optimisation model effectively characterises the uneven wear state of CVC work rolls by incorporating wear mechanisms. The wear prediction of CVC work rolls was completed by combining the wear law and the parameters of the rolling mill. The results indicate that the CNN-BiLSTM-Attention + NSGA-II combined model achieves the highest prediction accuracy, with an R 2 of 0.9736, mean absolute error of 0.0046, and root mean square error of 0.0061. This model provides significant reference value for work roll wear prediction.

The surface topography of the rolls used in skin-pass cold rolling determines the surface finish of rolled sheets. In this sense, work rolls can be intentionally textured to produce certain topographical features on the final sheet surface. The maskless electrochemical texturing method (MECT) is a potential candidate for industrial-scale application due to its reduced texturing cost and time when compared to traditional texturing methods. However, there are few studies in the literature that address the MECT method applied to the topography control of cold rolling work rolls. The present work aims to analyze the viability of surface texturing via MECT of work rolls used in skin-pass cold rolling. In this study, we first investigated how texturing occurs for tool steel using flat textured samples to facilitate the understanding of the dissolution mechanisms involved. In this case, a specially designed texturing chamber was built to texture flat samples extracted from an actual work roll. The results indicated that the anodic dissolution involved in tool steel texturing occurs preferentially in the metallic matrix around the primary carbides. Then, we textured a work roll used in pilot-scale rolling tests, which required the development of a special prototype to texture cylindrical surfaces. After texturing, the texture transfer from the work roll to the sheets was investigated. Rolling tests showed that the work roll surface textured with a dimple pattern generated a pillar-shaped texture pattern on the sheet surface, possibly due to a reverse extrusion mechanism.

The work roll thermal deformation has a direct impact on the final shape of hot-rolled strips, and the dynamic change of roll temperature distribution makes it difficult to predict the roll deformation accurately. To describe the temperature distribution change caused by the high temperature rolling pieces and complex external environment, a two-dimensional finite-difference model based on energy conservation is established, in which the effects of strip transverse temperature and individual strip temperatures on the contact heat transfer coefficient during the rolling cycle are considered. Additionally, the equivalent water-cooling coefficient is optimised based on actual production data. The result shown that the average temperature-predicted error was enhanced from ±4.0 to ±2.2°C. Further, the optimised model was used to analyse the temperature distribution of the work roll in both rolling process and the subsequent air-cooling process, the influence of various rolling parameters is obtained.

Abstract Focusing on DP590 steel, this study employs numerical simulation to investigate the formation mechanism of temperature field inhomogeneity during continuous casting and its impact on multi-pass rough rolling. A 2D continuous casting temperature field model developed in Abaqus, defined with modeling parameters including a slab size of 1600 × 230 mm, a casting speed of 1.1 m min−1, and specific water volume 1.99 l kg−1, reveals the thermal evolution during the cooling process. A 3D heating-rolling model incorporating defined parameters of work roll radius 500 mm, speed 6 rad s−1 further analyzes how temperature inhomogeneity affects rolling force and stress–strain distribution. The results demonstrate that the non-uniform temperature field significantly exacerbates rolling force fluctuations, with the rolling force under 600 s of heating increasing by approximately 15%–20% compared to a uniform 1200 °C temperature field, while simultaneously inducing a stress gradient along the thickness direction (stress difference exceeding 20 MPa between surface and core) and non-uniform strain distribution (strain difference reaching 0.68); however, extending the heating duration to 1200s reduces the core-surface temperature difference to below 300 °C, achieving stress–strain distribution uniformity comparable to isothermal conditions. Optimized heating processes enhance deformation uniformity, resolving the conflict between low-energy production and product quality in low-speed casting scenarios.

Skin-pass cold rolling is a crucial step in sheet metal production, modifying the sheet surface topography, ensuring thickness uniformity, and enhancing tribological performance. A key factor in this process is the surface texturing of work rolls, which, when transferred to the rolled sheet, directly affects lubrication distribution and formability in subsequent stamping operations. Properly textured sheets promote lubricant retention, reducing friction and wear, while roll wear can compromise texture transfer, leading to defects in the final product. This review presents a holistic view of surface texturing from the roll topography to the final product. First, it explores different texturing methods for work rolls, analyzing their efficiency, durability, and impact on texture transfer. Then, alternative texturing techniques and coatings are discussed as strategies to mitigate roll wear. By assessing the relationship between roll texturing and sheet drawability, this study provides insights to improve industrial processes, enhance product quality, and promote more sustainable manufacturing solutions.

Fracture resistance in hardfaced metal for continuous casting rollers and hot rolling mill work rolls

The paper presents the results of a study of the suitability of copper-graphite electrodes for achieving the required level of work roll microgeometry in the process of electric discharge texturing. Two pairs of work rolls were prepared on pilot lots of electrodes. It was found that the use of copper-graphite electrodes with a graphite content of 1 and 2% allows for an increase in the RPc value on the work roll by 10 and 20 cm–1, respectively, compared to the results obtained using bronze electrodes. 500 tons of DX54D galvanized rolled products for an automobile company were produced on work rolls textured using 1% copper-graphite electrodes. Work rolls textured using 2% copper-graphite electrodes were used throughout the campaign, the production rate was 2,500 t. The use of copper-graphite electrodes with a graphite content of 1 and 2% allows to increase the RPc and NP values on galvanized rolled products by 5–10 and 10–13 cm–1, respectively. The use of copper-graphite electrodes with a graphite content of 2% allows to obtain the NP value on galvanized rolled products in accordance with the requirements of Renault throughout the entire campaign of the automotive sheet

Roll wear significantly affects production efficiency and product quality in hot-rolled strip steel manufacturing by reducing roll lifespan and impeding the control of strip shape. This study addresses these challenges through a comprehensive analysis of the roll wear mechanism and the integration of an elastic deformation model. We propose an optimized wear prediction model for work and backup rolls in a hot continuous rolling finishing mill, dynamically accounting for variations in strip specifications and cumulative wear effects. A three-dimensional elastic–plastic thermo-mechanical coupled finite element model was established using MARC 2020 software, with experimental calibration of wear coefficients under specific production conditions. The developed dynamic simulation software achieved high-precision wear prediction, validated by field measurements. The optimized model reduced prediction deviations for work and backup rolls to 0.012 and 0.004, respectively, improving accuracy by 5.3% and 3.25% for uniform and mixed strip specifications. This research provides a robust theoretical framework and practical tool for precision roll wear management in industrial hot rolling processes.

The study presents the results of developing a production technology for galvanized sheet steel that ensures guaranteed compliance with automotive manufacturers' requirements for peak count standardization. The research revealed a correlation: reducing the number of passes leads to an increase in peak count (NP) by approximately 15 cm⁻¹. However, it should be noted that decreasing the number of texturing passes results in a reduction of roughness parame-ters (Ra and NP) by the end of the campaign, likely due to decreased surface wear resistance. To determine the optimal parameters for the final reverse-polarity pass, work rolls with a nominal roughness of 2.2 μm were prepared in 3 passes. The settings of the EDT (Electro-Discharge Texturing) machine during experimental roll preparation corresponded to standard parameters: pulse-on time – 13 μs, pulse-off time – 14 μs, current – 11 A, and “+” polarity. The influence of the chromium plating process on Ra and RPc values was established: chromium plating reduces Ra by approximately 0.1–0.2 μm and RPc by 10–20 peaks/cm. The best experimental result in terms of achieving Rsk = 0 while maintaining Ra was determined. Based on the optimal experimental parameters, two pairs of work rolls were prepared to assess galvanized strip roughness variation and to test samples in an automotive manufacturer's laboratory. The results obtained at PJSC “Severstal” and the manufacturer's laboratory were comparable.

In order to solve the long‐standing issue of uneven wear on backup rolls and promote the roll gap stiffness in the 2250 mm continuously variable crown hot strip mills, this study presents an optimization method for the design of the varying contact backup roll promotion (VCRpro) backup rolls to eliminate effectively the undesired contact zones between the work and backup rolls. First, the VCRpro contour represented by a cosine function is established based on the particle swarm optimization algorithm. Then, the 3D finite element model is established to investigate the contact pressures between the rolls under different shifting positions, bending forces, strip widths, and rolling forces. The results demonstrate that the regulation efficiency of the bending force has been enhanced. In comparison with the conventional backup rolls, the crown regulation ability of the bending force has an increase of 19.38%. And the roll gap stiffness has a rise of 15.52%. Moreover, the unevenness coefficient has experienced a maximum reduction of 35% and an average reduction of 25.77%. Industrial production results demonstrated that the VCRpro backup rolls significantly reduce the wear of the rolls compared to the conventional backup rolls, with an improvement of 10.54% in roll self‐maintaining.