Search Results (135)

Rising energy prices, especially in Europe, make it necessary to look for cost reductions wherever possible. It also concerns the industry and hot rolling processes. One of the ideas of reducing costs is to use a roll gap lubrication (RGL) system. Lubrication makes it possible to reduce the forces needed for the materials processing, which directly translates into lower power consumption, but also makes it possible to extend the service life of the working rolls. The authors associated with Krakow Hot Rolling Mill, as a part of their work related to improving the production process of HSLA-type steel, also took into account the possibility of analyzing the subject of roll gap lubrication. This paper is a review of interesting papers concerning research on this topic over the past years. The authors also included in this paper a section on what the RGL system looks like on the AMP HSM in Krakow itself. This paper is a prelude to considering possible modifications to the RGL system. Full article

This study investigates the technological and chemical causes of early zinc-coating degradation on cold-formed steel sections produced from DX51D+Z140 galvanized coils. Commercially manufactured products exhibiting early corrosion symptoms were used in this study. The entire processing route, which included strip preparation, cold rolling, hot-dip galvanizing, passivation, multi-roll forming, storage, and transportation to customers, was analyzed with respect to the residual surface chemistry and process-related deviations that affect the coating integrity. Thirty-three specimens were examined using electromagnetic measurements of coating thickness. Statistical analysis based on the Cochran’s and Fisher’s criteria confirmed that the increased variability in zinc coating thickness is associated with a higher susceptibility to localized corrosion. Surface and chemical analysis revealed chloride contamination on the outer surface, absence of detectable Cr(VI) residues indicative of insufficient passivation, iron oxide inclusions beneath the zinc coating originating from the strip preparation, traces of organic emulsion residues impairing wetting and adhesion, and micro-defects related to deformation during roll forming. Early zinc coating degradation was shown to result from the cumulative action of multiple technological (surface damage during rolling, variation in the coating thickness) and environmental (moisture during storage and transportation) parameters. On the basis of the obtained results, a methodology was proposed to prevent steel product corrosion in industrial conditions. Full article

Edge cracks in hot-rolled sheets of industrial grain-oriented electrical steel significantly affect the yield rate and pose substantial challenges to cold rolling fabrication. Eliminating such structural defects through hot rolling requires a thorough understanding of their formation mechanism. This study investigates the formation mechanism of edge cracks in hot-rolled sheets, which are characterized by coarse strip-like grains with typical thicknesses ranging from 20 μm to 100 μm. Coarse, strip-shaped grains have low fracture stress, which is the cause of edge cracks. They originate from abnormally developed columnar grains in continuous casting slabs after reheating, which is unavoidable in industrial large-scale production. Inadequate fragmentation and insufficient recrystallization during rough rolling result in residual coarse grains of intermediate slabs, and their preferential deformation and outward protrusion lead to the formation of grooves. In the subsequent finishing rolling process, deformed coarse grains near the grooves undergo further elongation, developing into distinct strip-like structures. Based on the above mechanistic understanding, the edge microstructure under various rolling parameters was investigated, and targeted improvement measures for edge cracks were proposed. It is concluded that the edge quality can be significantly enhanced through increasing the total width reduction, additional rough rolling passes, and the implementation of edge heating during rough rolling. Quantitative analysis demonstrates that increasing the rolling passes from D to E significantly reduces the fraction of band structure from 64% to 48% and the average width of elongated grains from 43.5 μm to 38.4 μm. Full article

A novel dual-face hot-roll inlaying technique was developed to fabricate a Ag/Cu through-layered composite for use in melt elements for fuse production, including two stages of grooving in a Cu strip followed by separate inlaying of Ag strips at the same positions on the opposite surfaces. The microstructure was characterized using field emission scanning electron microscopy (FE-SEM), electron probe microanalysis (EPMA), X-ray diffraction (XRD), and selective area electron diffraction (SAED). The Ag/Cu interfaces are flat and well bonded, with an elemental interdiffusion layer of less than 2 μm. The same textural components—copper, brass, and S-type components—were identified in both the Ag and Cu layers. However, no well-matched crystal orientation relationship between Ag and Cu was detected at the interface. Moreover, tensile properties and electrical resistance were measured to evaluate the bonding strength and conductivity of the interface. It was found that Ag/Cu bonding strength surpassed the tensile strength of Ag, i.e., 260 MPa. While the total elongation is less than 1%, the Ag layer exhibits excellent plasticity, with a section shrinkage over 90%. Compared with the calculated resistivity with a series circuit model, the tested value of the composite sample, including six Ag/Cu interfaces, increased by only 6.6%, indicating good conductivity of the Ag/Cu interface. Therefore, the obtained composite is a promising candidate for the fabrication of melt elements. Full article

This article proposes a dynamic causal inference framework that integrates theoretical analysis, numerical simulation, and industrial data mining to address the root-cause tracing problem of time-delay effects in strip thickness and shape quality during hot rolling. First, we analyze the key process parameters, equipment states, and material characteristics influencing geometric quality and clarify their dynamic interaction mechanisms. Second, a delay-correlation matrix calculation method based on Dynamic Time Warping (DTW) and Mutual Information (MI) is developed to handle temporal misalignment in multi-source industrial signals and quantify the strength of delayed correlations. Furthermore, a transformer-based information gain approximation mechanism is designed to replace traditional explicit probability modeling and learn dynamic information-flow relationships among variables in a data-driven manner. Experimental verification on real production data demonstrates that the proposed framework can accurately identify time-delay causal pathways, providing an interpretable and engineering-feasible solution for quality control under complex operating conditions. Full article

High-strength cooling collectors are the key equipment for post-roll cooling technology of hot-rolled plates, and the internal flow characteristics of the collector are crucial to the quality and efficiency of cooling. In this work, numerical simulation is used to study the collector w₂ (collector width), β (manifold inclination), and h₂ (slot height) in different process parameters at the outlet of the velocity size and uniformity of the influence of the law. By comparing the two methods of steady state and transient state, the average velocity and flux errors are less than 0.1, and the effects of structural modifications on the outlet flow velocity and flow field uniformity were obtained for two sizes of trough nozzles. The results show that the increase in pressure increases the fluctuation in velocity, but the increase in velocity in the center of the slot outlet keeps decreasing; when the height of the tank h₁ = 90 mm, the increase in β causes the velocity of the slot outlet to decrease, but the fluctuation in velocity increases; when h₂ increases, the fluctuation in the velocity in the center of the slit outlet is obviously reduced, and the fluctuation is reduced most significantly when it is increased to 9 mm, but it will result in the decrease in the average value of the outlet velocity. Therefore, within the scope of this study, the optimal process parameters are inlet pressure 0.5–0.6 MPa, β = 10°, h₂ = 9–15 mm, and w₂ = 100–110 mm. Full article

In the hot strip rolling process, inter-stand speed coordination directly affects product quality and production stability. Traditional linear speed compensation strategies perform poorly under extreme conditions such as strip tension and strip piling, making it difficult to maintain stable loop control. This study proposes a speed compensation strategy that integrates Particle Swarm Optimization (PSO) with Model Predictive Control (MPC). Based on the mechanism of hot rolling, a nonlinear state-space model is constructed, in which the compensation parameter is treated as an optimization variable to formulate a rolling optimization problem. PSO is employed to globally solve the nonlinear MPC problem, yielding an optimal compensation sequence that adapts to disturbance variations. The proposed algorithm can adaptively adjust the speed compensation parameter under typical strip piling and strip tension conditions, thereby achieving stable loop regulation and maintaining the looper angle within the desired range. This effectively addresses the speed coordination problem under abnormal conditions in hot strip rolling, improving the control performance. The experimental results verify the effectiveness of the proposed method. Full article

The increase in electrification and desire for greater electrical motor efficiency under a range of operating conditions for different products (e.g., household appliances, automotive and aerospace) is driving innovative motor designs and demands for higher performing electrical steels. Improvements in the magnetic, electrical and/or mechanical properties of electrical steels are required for high-volume electric motors and recent advances include steels with increased silicon (Si) content (from <3.5 wt% Si up to 6.5 wt%). Whilst the 6.5 wt% Si steels provide increased motor performance at high frequencies, the formation of a brittle BCC B2/D03 phase means that they cannot be cold-rolled, and therefore the production route involves siliconization after the required thickness strip is produced. The advances in computationally driven alloy design, coupled with physical metallurgical understanding, allow for more adventurous alloy design for electrical steels, outside the traditional predominantly Fe-Si compositional space. Two alloys representing a new alloy family called HiPPES (High-Performing and Processable Electrical Steel), based on low cost commonly used steel alloying elements, have been developed, cast, rolled, heat-treated, and both magnetically and mechanically tested. These alloys (with nominal compositions of Fe-3.2Mn-3.61Si-0.63Ni-0.75Cr-0.15Al-0.4Mo and Fe-2Mn-4.5Si-0.4Ni-0.75Cr-0.09Al) offer improvements compared to current ≈3 wt% Si grades: in magnetic performance (>25% magnetic loss reduction at >1 kHz), and in tensile strength (>33% increase in tensile strength with similar elongation value). Most importantly, they are maintaining processability to allow for full-scale commercial production using traditional continuous casting, hot and cold rolling, and annealing. The new alloys also showed improved resilience to grain size, with the HiPPES materials showing a <5% variance in loss at frequencies greater than 400 Hz for grain sizes between 55 and 180 µm. Comparatively, a commercial M250-35A material showed a 40% increase in loss for the same range. The paper reports on the alloy design approach used, the microstructures, and the mechanical, electrical and magnetic properties of the developed novel electrical steels compared to conventional ≈3 wt% Si and 6.5 wt% Si material. Full article

Surface defects in hot-rolled steel strip alter the material’s properties and degrade its overall quality. Especially in real production environments, due to time sensitivity, lightweight Convolutional Neural Network models are suitable for inspecting these defects. However, in real-time applications, the acquired images are subjected to various degradations, including noise, motion blur, and non-uniform illumination. The performance of lightweight CNN models on degraded images is crucial, as improved performance on such images reduces the reliance on preprocessing techniques for image enhancement. Thus, this study focuses on analyzing pre-trained lightweight CNN models for surface defect classification in hot-rolled steel strips under degradation conditions. Six state-of-the-art lightweight CNN architectures—MobileNet-V1, MobileNet-V2, MobileNet-V3, NasNetMobile, ShuffleNet V2 and EfficientNet-B0—are evaluated. Performance is assessed using standard classification metrics. The results indicate that MobileNet-V1 is the most effective model among those used in this study. Additionally, a new performance metric is proposed in this study. Using this metric, the misclassification distribution is evaluated for concentration versus homogeneity, thereby facilitating the identification of areas for model improvement. The proposed metric demonstrates that the MobileNet-V1 exhibits good performance under both low and high degradation conditions in terms of misclassification robustness. Full article

The effect of the temperature and strain rate during the hot rolling process on the microstructural evolution in fine-grained Ni₃Al intermetallic alloy doped with Zr and B was examined in this work. The hot rolling process was carried out at an initial temperature range of 1000, 1100, and 1280 °C and at a strain rate between 3.9 × 10⁻¹ s⁻¹ and 2.5 s⁻¹. The results of the EBSD microstructural analyses revealed that dynamic recrystallization phenomena are initiated at the rolling temperature of 1100 °C, while a fraction of the dynamically recrystallized grains further increases with both the rising temperature and strain rate of the deformation process. Furthermore, to estimate the heat losses during the hot rolling processing, a non-stationary heat transfer model was formulated and then used to evaluate the experimentally received data. Full article

This study investigated the application of neural network techniques to predict the mechanical properties of low-carbon hot-rolled steel strips using industrial data. A feedforward neural network (FFNN) model was developed to predict the yield strength (YS), ultimate tensile strength (UTS), and elongation (%EL) based on the chemical composition and processing parameters. For the low-carbon hot-rolled steel strip (C: 0.02–0.06%, Mn: 0.17–0.38%), 435 datasets were utilized with 17 input parameters, including 15 composition elements, finish rolling temperature (FRT), and coil target temperature (CTT). The model was trained using 335 datasets and tested using 100 randomly selected datasets. The optimum network architecture consisted of two hidden layers with 34 neurons each, achieving a mean squared error of 0.014 after 200,000 iterations. The model predictions showed excellent agreement with the actual values, with mean percentage errors of 4.44%, 3.54%, and 4.84% for the YS, UTS, and %EL, respectively. The study further examined the influence of FRT and CTT on mechanical properties, demonstrating that FRT has more complex effects on mechanical properties than CTT. The model successfully predicted property variations with different processing parameters, thereby providing a valuable tool for alloy design and process optimization in steel manufacturing. Full article

Semi-continuous casting is an important method for the large-scale production of high-strength conductive copper-iron (Cu-Fe) alloys in the future. However, serious peeling defects were found on the surface of cold-rolled strips during industrial trials. Due to the multi-step complexity of the manufacturing process (from casting to final product), identifying the root cause of defect formation remains challenging. X-ray computed tomography (X-CT) was used to quantitatively characterize the pores and defects in the horizontal continuous casting Cu-Ni-Sn slab, the semi-continuous casting Cu-Fe alloy slab, and the hot-rolled slab of Cu-Fe, and the relationship between the defect characteristics and processes was analyzed. The results showed that the internal defect sphericity distribution of the Cu-Fe alloy slab after hot rolling was similar to that of the reference Cu-Ni-Sn slab. The main difference lies in the low sphericity range (<0.4). The volume of pore defects inside the Cu-Fe alloy after hot rolling was significantly larger than in the reference sample, with a 52-fold volume difference. This phenomenon may be the source of surface-peeling defects in the subsequent cold-rolling process. The occurrence of internal defects in the Cu-Fe alloy is related to both the composition characteristics and casting processes of the Cu-Fe alloy; on the other hand, it is also related to the hot-rolling process. Full article

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. Full article

Currently, in the domain of surface defect detection on hot-rolled strip steel, detecting small-target defects under complex background conditions and effectively balancing computational efficiency with detection accuracy presents a significant challenge. This study proposes CTL-YOLO based on YOLO11, aimed at efficiently and accurately detecting blemishes on the surface of hot-rolled strip steel in industrial applications. Firstly, the CGRCCFPN feature integration network is proposed to achieve multi-scale global feature fusion while preserving detailed information. Secondly, the TVADH Detection Head is proposed to identify defects under complex textured backgrounds. Finally, the LAMP algorithm is used to further compress the network. The proposed algorithm demonstrates excellent performance on the public dataset NEU-DET, achieving a mAP50 of 77.6%, representing a 3.2 percentage point enhancement compared to the baseline algorithm. The GFLOPs is reduced to 2.0, a 68.3% decrease compared to the baseline, and the Params are reduced to 0.40, showing an 84.5% reduction. Additionally, it exhibits strong generalization capabilities on the public dataset GC10-DET. The algorithm can effectively improve detection accuracy while maintaining a lightweight design. Full article

The twin-roll casting (TRC) process is widely used in the aluminum industry due to its cost efficiency and continuous production capability. However, maintaining consistently high surface quality remains challenging due to complex heat transfer behavior at the roll/strip interface. This study examines the critical influence of roll surface conditions, especially the formation of an Al coating layer, on solidification behavior and resulting strip quality in the TRC of an Al-5Mg alloy. Experimental results demonstrated that casting without an Al coating layer led to surface defects such as hot tears and porosity due to insufficient cooling. In contrast, strips produced with a stable Al coating layer exhibited excellent surface quality with no surface defects. Numerical simulations further indicated that a stable Al coating enhanced the interfacial heat transfer coefficient (up to 30,000 W/m²K), ensuring effective cooling and complete solidification before the strip exited the roll nip. Moreover, simulations validated the feasibility of using steel rolls in industrial applications, provided the coating layer was consistently maintained. This research highlights the significance of roll surface control in improving TRC product quality. Full article