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The study described in the paper was carried out through measurements taken at a feed station in a hot rolling line. The aforementioned measures are appropriate for the purpose of analyzing power quality. The measurements were taken using a three-phase power quality analyzer. Measurements were taken for voltage and current values, as well as for active, reactive, and apparent powers. The analysis of the measurements taken indicates that the power quality is affected by the nonlinearity of the load. As a consequence, the level of reactive power becomes higher, leading to a reduced power factor.

DP600 steel is widely used in the automotive industry due to its exceptionally favourable combination of high tensile strength and good ductility. In the hot-rolling process, DP600 steel is produced by use of controlled cooling of the rolled strip from temperature above Ar3 to temperature below Ms. In this process, it is quite difficult to control key process parameters such as the time or temperature, and the final microstructure of the material is also affected by the degree of deformation of the material at various stages of the process. This paper presents a statistical analysis of the effect of chemical composition and selected hot rolling process parameters on the microstructure of DP600 sheet with respect to its mechanical properties. Based on industrial data from hot rolling mill combined with extended microstructure analysis, it was possible to find correlations between some of the analysed parameters and material properties. Among many correlations discussed in this work, most notable are those between martensite morphology and mechanical properties, between Mn and Si concentration and martensite morphology and between rolling speed, strain, cooling rate and mechanical properties.

Abstract The prediction accuracy of the rolling force is crucial for the strip hot rolling process, which will significantly affect the dimensional control accuracy of the strip product. The rolling force prediction models used in actual strip hot rolling production before are mainly analytical models and simple neural network models, but with the improvement of product quality, these models can no longer meet the requirements of high-end product production. A new online model based on the gradient boosting decision tree (GBDT) method is proposed to improve the accuracy of the online prediction of rolling force, in which the random forest method based on feature importance is adopted to select feature parameters. A model self-training function was developed in the control system to ensure the accuracy of the model used online. By comparing various machine learning methods, the results show that the rolling force prediction model proposed by the GBDT is better than that based on other regression methods. The established model has been successfully applied to predict the rolling force for the finishing rolling in a 2250 mm strip hot rolling production line. Compared with the traditional model, the rolling force prediction accuracy and thickness control accuracy are significantly improved.

The issues of improving the control systems of the continuous wide-strip hot rolling mill 2000 of NLMK PJSC are considered. Modification of four control subsystems ensures the mill 2000 operation stability in the finishing group of stands, which allows switching to a higher-speed mode of rolling thin strips for cold rolling and actually increasing productivity.

This study establishes a vertical–horizontal coupling vibration model of hot rolling mill rolls under multi-piecewise nonlinear constraints considering the piecewise nonlinear spring force and piecewise nonlinear friction force constraints of the hydraulic cylinder in the vertical direction of the rolls, the piecewise stiffness constraints in the horizontal direction, and the influence of the nonlinear dynamic rolling force in the rolling process. Using the average method to solve the amplitude–frequency response equation of the coupled vibration system and taking the actual parameters of a 1780 mm hot rolling mill (Chengde Steel Co., Ltd., Chengde, China) as an example, we study the amplitude–frequency characteristics of the mill rolls under different parameter settings. The results show that the amplitude and resonance region can be reduced by appropriately reducing the external disturbance force and the nonlinear spring force of the hydraulic cylinder, appropriately increasing the nonlinear friction force, and eliminating the gap between the bearing seat and the mill housing, to avoid the amplitude jump phenomenon due to piecewise variation. Furthermore, using the singularity theory to study the static bifurcation characteristics of the coupled vibration system, we establish a relationship between the vibration parameters and the topological bifurcation solution of the coupled system. The transition sets and their corresponding bifurcation topological structure in three cases are given, and the steady and unsteady process parameter regions of the rolls are obtained. The dynamic behavior of the coupled vibration system can be controlled by varying the bifurcation parameter. This study provides a theoretical basis for restraining the vibration of hot rolling mill rolls and optimizing the process parameters.

A several processes are required for production of steel, and one of these processes is called as hot rolling. The rolling mill efficiency is most important factors that determines the steel quality that is produced. The present article provides a thorough analysis of experiments data, numerical analysis, and artificial neural network simulations for enhancement of hot rolling mill performance. For achieving this rolling mill's experimental data is collected and examined. The speed of the rollers (N), Young modulus (E), distance between a rollers (d) and fillet thickness (t) are the parameters considered in this work. The rolling process is simulated, and its effectiveness is evaluated, using finite element analysis techniques. To describe the behavior of the rolling mill while accounting for many parameters and their interactions, finite element analysis techniques are used. The performance of the rolling mill is also forecasted and optimized using simulations of artificial neural networks. The findings of this study can contribute to the development of advanced control systems and optimization methodologies for hot rolling mills, which can ultimately result in increased efficiency, cost savings, and improved product quality in the steel industry.

ZK61 magnesium-alloy plate with high tensile strength and elongation is obtained by combined multipass symmetric hot rolling and asymmetric warm rolling. Deformation history considering varying strain rate obtained from the macro-finite element analysis of the selected passes are introduced into the viscoplastic self-consistent model (VPSC) as initial boundary conditions for macro- multiscale and micro-multiscale coupling analysis. VPSC simulation results show that in the initial stage of rolling deformation, the basal slip is the dominated deformation mode, supplemented by prismatic slip and pyramidal slip. With increased rolling strain, the pyramidal slip presents competitive relationship with basal slip, and the activation amount of 101—1 compression twins is limited. During asymmetric rolling, the basal slip is dominant, followed by the pyramidal slip. Experimental results show that the basal texture is gradually strengthened after symmetric rolling, and grain size is refined due to the activation and recrystallization of twins. Asymmetric rolling makes the basal texture deflect 10° to the rolling direction and further refine the grain size. With the ongoing of symmetric rolling, the mechanical anisotropy of the plate weakens, and the yield strength, tensile strength, and plasticity of the material improves. In particular, after asymmetric rolling, the tensile strength in the RD and TD directions of the plate reaches 391.2 MPa and 398.9 MPa, whereas the elongation reaches 19.8% and 25.5%.

To determine the power of a process of hot rolling of strips in the mill’ finishing group, the methodology for calculating specific work in the elastic areas of deformation zone is supplemented by accounting the influence of speed on the contact friction coefficient of a strip and work rolls. For the first time, a reliable regression equation has been obtained to determine the rolling friction arm coefficient in the contact of support and working rolls of the hot rolling mill 2000 finishing group of Severstal PJSC, which makes it possible to determine the power consumption spent on overcoming the rolling friction itself and rotating the idle support rolls. Maximum error in calculating power using the augmented method, taking into account the specified technology factors, was 11.9%, the average was 5.5%.

It is difficult to effectively evaluate the technology used to test fatigue in face gears due to their complexity, the lack of experimental data, and weak life evaluation methods. In this paper, we study fatigue experiment technology and carry out a life evaluation for hot rolling straight face gears. A hot rolling forming test was completed by analyzing and simulating the rolling formation of face gears, and the bending stress and fatigue life of face gears was simulated. We designed an experimental scheme and test bench for testing fatigue in straight face gears; this is the first bending fatigue life experiment carried out on hot rolling straight face gears in China. The BP neural network–Bootstrap sample expansion method and GM(1,1) model were carried out to evaluate the fatigue life of hot rolling straight face gears under information-poor conditions. A comparative analysis was carried out with skiving-formed straight face gears, which verifies the feasibility and superiority of hot rolling forming for straight face gears. This study provides a theoretical basis and technological support for the study of fatigue resistance in face gears, and applications for machine installations are provided.

Depending on various properties such as hardness, roughness, friction coefficient, wear resistance, and oxidation behavior, different grades of steel can be used in hot strip mills. In this paper, two grades were investigated: one grade of semi-high-speed steel and one grade of high-speed steel. They differ in their chemical composition, principally the carbon and the chromium content, and the presence or not of other alloying elements such as vanadium, niobium, and tungsten. Their oxidation behavior was studied at 576 °C and 600 °C, temperatures reached in the F1 finishing stand and the roughing stand, respectively, by high-temperature oxidation tests in a wet atmosphere. The sliding wear resistance was followed by pin-on-disc experiments. The evolution of the microstructure was observed by optical and scanning electron microscopies. The oxides formed on the surface of the samples were analyzed by XRD and EDS. The thickness of the oxide layers and the mass gain were measured from oxidation tests. The results showed that for both grades, the surface roughness R a after oxidation tests is high enough to prevent slipping. The low friction coefficient will increase the wear resistance of the roll. The hardness of the steel grades decreases but remains high enough to ensure wear resistance. Consequently, those grades can be used in the roughing stand or the F1 finishing stand of hot rolling mills.