Hot Rolling Process Research Articles

Roll force prediction by combined FEM and ANN in the hot rolling process under nano-lubrication condition

Roll force prediction by combined FEM and ANN in the hot rolling process under nano-lubrication condition

Temporal online self-learning stochastic configuration networks: A study on strip deviation prediction

Stochastic configuration networks (SCNs), with the rapid learning abilities and universal approximation properties, have garnered growing interest in the industrial domain in recent years. In the hot rolling process, strip deviation affects product quality and production safety. In this paper, a novel model named temporal online self-learning stochastic configuration networks (TOSL-SCNs) designed for early prediction of strip deviation in the hot rolling process is introduced. To address the challenges of time series prediction, conventional SCNs are extended to a two-dimensional format, enabling effective processing of time series data. Given the dynamic nature of industrial environments, the model incorporates an online self-learning capability to adapt to nonstationary data. Additionally, to ensure the stability of the model’s predictive performance, a data buffer strategy is introduced to dynamically refresh the training dataset. This paper demonstrates the capabilities of TOSL-SCNs in time series modeling, online self-learning, and data buffer strategy from multiple perspectives. The case study on strip deviation prediction highlights the necessity of these capabilities in industrial applications.

Study on the continuous cooling transformation behavior of X65 hydrogen transportation pipeline steel

Abstract In this work, the continuous cooling transformation (CCT) behavior of X65 hydrogen transportation pipeline steel was studied by Gleeble-3800 machine. The CCT curve was constructed by temperature-dilation curves and microstructures of samples at different cooling speeds. The Ac1 and Ac3 temperatures of the tested steel are 715 °C and 901 °C. Polygonal ferrite and pearlite can be recognized when the cooling speed is between 0.2 °C/s ~ 5 °C/s, bainite and polygonal ferrite can be recognized when the cooling speed is higher than 10 °C/s. The hot-rolling process was designed according to CCT. After finishing rolling, the air cooling steel plates possesses higher hydrogen diffusion coefficient, and the steel plates coiled at 650 °C possesses lower hydrogen diffusion coefficient.

Formation mechanism of edge crack during hot rolling process of high-grade non-oriented electrical steel

Edge crack formed during the hot rolling process significantly affected the quality of high-grade non-oriented electrical steel (NOES), posing substantial challenges to production. This study investigated the formation mechanism of serrated edge cracks in hot rolled strip, characterized by unusually coarse strip-like grains with typical thicknesses ranging from 0.5 to 0.8 mm and lengths ranging from 10 to 15 mm. These coarse strip-like grains evolved from abnormal columnar grains at the edges of reheating slab. During the continuous casting process, the bulge phenomenon occurred easily in high-grade NOES slabs, due to its lower yield strength at high temperatures. This bulge induced high internal stress at the slab edge, leading to abnormal growth of the columnar grains during the slab reheating process at high temperature. The orientation of coarse grains gradually changed to a rotated cube texture ({100}<011>) throughout the hot rolling process. These grains with rotated cube texture exhibited fewer slip systems and lower deformation storage energy, which is not conducive to the plastic deformation in thickness direction. Consequently, coarse grains at the slab edge deformed along TD direction and overflowed towards the lower surface of hot rolled strip, resulting in the original edge boundary enveloped by the overflowed metal to generate crack source. Finally, the serrated edge crack was formed from crack source under tensile stress during finish hot rolling.

Mechanical properties and stability of hot rolled Zn-0.8Mg alloy

Insufficient mechanical strength and mechanical instability are important factors limiting the application of zinc-based alloys as biodegradable materials. Currently, alloying and plastic deformation are effective methods to improve material properties. Therefore, this paper investigates the effect of hot rolling process on the mechanical properties and stability of Zn-0.8Mg alloys. The results show that after hot rolling, the internal grain of Zn-0.8Mg alloy is refined, the second phase is precipitated, the weaving strength is enhanced, and the overall mechanical properties are significantly improved. The contribution of deformation strengthening can reach about 90 %. The tensile strength, yield strength, and elongation of the alloy were 312.3 MPa, 249.5 MPa, and 15.6 % (141.72 %, 155.96 %, and 189.96 %, respectively) at a rolling volume of 70 %, which meets the clinical criteria for degradable material implants. However, this treatment reduced the stability of the mechanical properties of the Zn-0.8Mg alloy. During natural ageing, a small amount of Mg2Zn11 phase precipitated inside the alloy, reducing the elongation. Compared with cast alloys, hot rolled alloys have higher grain boundary density, which accelerates the precipitation of secondary phases, leading to more pronounced changes in the mechanical properties of the alloys after hot rolling.

Damage Initiation of 15V38 Steel Bar during Square‐to‐Round Hot Rolling Process

Damage Initiation of 15V38 Steel Bar during Square‐to‐Round Hot Rolling Process

On the Relationship between Thermomechanical Processing Parameters and Recrystallization Texture in AA1100 Aluminum Alloy

In this study, 48 hot-rolling processing conditions were designed to investigate the influences of thermomechanical processing parameters on the recrystallization behavior and texture development. The hot-rolling experiments were conducted using the thermomechanical simulator Gleeble 3800 at temperatures of 275, 300, and 350 °C with strain rates of 5 and 90 s−1 up to 60 and 85% reduction. The microstructure and texture analysis were measured by using the EBSD technique on a large area. Experimental results show that the Cube component maintains a volume fraction between 10% and 20%, below the 40% recrystallization fraction, but the volume fraction of Cube significantly increases between 20% and 50% above the 40% recrystallization fraction. However, the fractions of Rotated Cube (RC) and Goss components remain below 10%.

Effect of hot rolling process on the microstructure and mechanical properties of a high-strength strip casting microalloyed steel

A novel Nb–V–Mo microalloyed steel with 1 GPa yield strength and high ductility was developed by strip casting. The effects of hot rolling on the microstructure and mechanical properties of the Nb–V–Mo microalloyed steel were investigated using scanning electron microscopy, electron backscatter diffraction, transmission electron microscopy, atom probe tomography and tensile tests. Both the as-cast and hot-rolled specimens exhibit a microstructure characterized by lath-like bainite and (Nb, V, Mo)C clusters, while the bainite lath was refined after hot rolling. Tensile test results show obvious improvements in the yield strength, tensile strength, and elongation of the hot-rolled specimen (1008 MPa, 1075 MPa, 20.1 %, respectively), compared to that of the as-cast ones (879 MPa, 978 MPa, 19.0 %, respectively). Additionally, the hot-rolled specimen displays a similar dislocation multiplication and storage capacity to the as-cast specimen, resulting in a comparable work-hardening capability during plastic deformation.

Synthesis of Nd-lean (Nd,Ce,La)-Fe-B magnets via hot deformation and rolling

In this work, we have used bulk combinatorial synthesis to rapidly identify a (Nd,Ce,La)-Fe-B composition that is both Nd-lean (<50 % of total rare earth content) and exhibits good thermal stability (TC∼269 °C). Bulk anisotropic magnets of the corresponding composition [i.e. (Nd0.47Ce0.28La0.25)2.2Fe14B1 (at%) + (1.5 wt% TiC)] were synthesized by hot deformation and hot-roll processes. To enhance the energy product of the hot deformed alloys, feedstock powder with 2.5–7.5 wt% Ce-Al-Cu grain boundary modifier was blended together prior to deformation processing. Moreover, hot deformation processing parameters, temperature (T), and processing time (t), were examined over a wide range to enhance the energy product of the resultant magnet alloys. We found that adding just 2.5 wt% Ce-Al-Cu increased the maximum energy product from ∼12 MGOe for the monolithic alloy to ∼20 MGOe for the alloy with added grain bounder modifier. The processing parameters (e.g., temperature and time) identified for hot deformation were applied to the hot-rolling process to synthesize samples with larger dimensions that exhibit an energy product of 17.7 MGOe with 5 wt% Ce-Al-Cu added.

Enhanced mechanical performance and tailored degradation characteristics of rolled Zn-0.8Li-0.4Mn alloy

The application of biodegradable Zn-based vascular alloy stents proves to be an ideal solution for addressing cardiovascular diseases. In this work, a Zn-0.8Li-0.4Mn alloy is designed with no biological toxicity, and optimized microstructure and properties through a hot rolling process. The resulting alloy shows a combined enhancement in both mechanical strength and resistance to corrosion. Noteworthy is the effectiveness of rolling deformation in refining alloy grains, promoting the uniform distribution of precipitates, and enhancing strength and ductility. After 90 % deformation, the Zn-0.8Li-0.4Mn alloy demonstrates excellent mechanical properties, with peak yield strength and ultimate tensile strength of 406.0 MPa and 449.1 MPa, respectively, and elongation exceeding 75 %. Corrosion studies indicate a relationship between the degradation rate increase and grain refinement, with the primary corrosion mechanism being pitting corrosion. The corrosion product Li2CO3 exhibits high stability, providing a passivation effect on the alloy surface. This work establishes a theoretical foundation and practical reference for the development of new biodegradable Zn-based alloys tailored for biomedical applications.

High-dimensional process monitoring under time-varying operating conditions via covariate-regulated principal component analysis

High-dimensional process monitoring, which aims to raise warnings for faulty events, is a fundamental tool in ensuring the safety of large-scale industrial systems. Over the last few decades, there has been significant interest in Principal Component Analysis (PCA)-based Statistical Process Control (SPC) charts. However, most of them rely on PCA’s optimal properties in homogeneous data, which often fails when dealing with heterogeneous data from industrial processes under time-varying operating conditions. To address this issue, this study proposes a Covariate-regulated PCA model (CrPCA) seamlessly integrated into a process monitoring framework. The main idea is to adjust the principal component directions smoothly according to the time-varying operating conditions, resulting in significantly less information loss in the principal component scores compared to existing methods. This approach further yields a low-dimensional feature vector that follows a distribution with fixed parameters, regardless of covariates, for real-time surveillance. We validate the performance of our methodology through a comprehensive numerical study and two real-world applications: wind turbine condition monitoring and hot rolling process monitoring.

Deep learning-based quality prediction for multi-stage sequential hot rolling processes in heavy rail manufacturing

Traditional quality control practices in heavy rail manufacturing primarily rely on experiential knowledge and numerical simulations. However, these methods come with significant drawbacks, including high costs, safety concerns, and limited accuracy due to the inadequate consideration of various influencing factors. Despite the accumulation of extensive data by some heavy rail manufacturers in recent years, achieving data-driven quality modeling remains a formidable challenge, mainly due to the complexity of the multi-stage sequential production process. This study presents the Temporal-Spatial Mapping approach to transform isochronous sampling data into spatially aligned data. Additionally, it introduces a multi-objective prediction model, Temporal-Fusion-LSTM (TFL), designed for evaluating the quality of heavy rails. The proposed model presents the Double-Layer LSTM with Time-Steps Fusion (DLL) architecture. The first layer of the DLL architecture targets the temporal transfer regularity within a single stage, while the second layer addresses the transition dynamics across multiple rolling stages in the heavy rail rolling process. Following this, the Local Process Correlation Matrix (LPCM) based on the Maximal Information Coefficient (MIC) is employed to empower the model to comprehend the intricate interactions among parameters in each stage of the rolling process. Finally, the Multi-Gate based Shared-Bottom architecture is employed to accentuate manufacturing processes highly correlated with the target quality indicators during multi-objective prediction. Real production data from a heavy rail factory is utilized to validate the effectiveness of the method. The experimental results unequivocally demonstrate that the proposed method accurately predicts heavy rail quality and facilitates cross-stage prediction, thus establishing the groundwork for data-driven quality diagnosis and pre-control in heavy rail production.

Effects of Hot Rolling Process Conditions on Microstructure and Mechanical Properties of Hot-rolled Al-Zn-Mg-Cu-Sc-Zr Alloys

Effects of Hot Rolling Process Conditions on Microstructure and Mechanical Properties of Hot-rolled Al-Zn-Mg-Cu-Sc-Zr Alloys

Crystallization Behavior of the CaO–SiO2–Al2O3–MgO System Inclusions

The crystallization process of low melting point CaO–SiO2–Al2O3–MgO system inclusions during the continuous casting and hot rolling process greatly affects the deformability of inclusions. The effect of Al2O3 and MgO contents on the crystallization characteristics of CaO–SiO2–Al2O3–MgO system melts representing the typical oxide inclusions in Si–Mn deoxidized steels is systematically investigated. The continuous cooling transformation and time–temperature transformation experiments are carried out. The results reveal that the increase of Al2O3 contents restrains the crystallization process of the melt, whereas the crystallization tendency of the melt is promoted with the increase of MgO contents. The precipitated phases are predominately 2CaO·MgO·2SiO2 and 3CaO·MgO·2SiO2, and the primary crystalline phase is unaffected by the changes of Al2O3 and MgO contents. To obtain low melting point plasticized inclusions with limited crystallization ability, it is recommended to control the Al2O3 and MgO contents greater than 15 wt% and below 5 wt%, respectively. The isothermal treatment is suggested to be controlled within a proper temperature range (1175–1250 °C) to decrease the crystallization kinetics. The oxide system's viscosity change is the limiting kinetic factor in the crystallization process, and it can be utilized to predict the system's crystallization tendency.

Interpretable prediction model for decoupling hot rough rolling camber-process parameters

The presence of asymmetrical camber defects in reversible hot rough rolling processes significantly impacts the quality of plate shapes. Understanding and quantifying the intricate relationship between process parameters and camber is essential for developing cost-effective strategies to rectify plate shape defects. Previous research predominantly concentrated on specific couplings between process variables and camber, employing simplified mathematical models with physical mechanisms. However, these approaches may overlook critical factors inherent in the entire rough rolling process, which can substantially influence plate shape deformation. Furthermore, heavy reliance on expertise within the rolling domain may limit the capability and accuracy of coupling analysis models. In this paper, we introduce an Interpretable Prediction Model for Decoupling Camber-process Parameters (called IP-DCP), to investigate the process coupling within the entire rough rolling process. IP-DCP employs conditional modeling to integrate the intricate dependencies of process parameters during rough rolling, dynamically shaping composite features that enhance accurate camber predictions. Additionally, we introduce statistical interpretations for camber predictions using SHapley Additive exPlanation (SHAP) models. This enables a comprehensive comparison of critical process factors influencing camber and coupling analysis in various rolling scenarios, including the overall rough-rolled slab and specific steel grades such as Q335B and ST12. Extensive experiments have been conducted on actual rough roughing datasets, demonstrating the superior performance of our camber prediction model compared to baselines. Furthermore, we have conducted a quantitative analysis of their overall effect, main effect, and interaction effect. These coupling analysis results consistently align with established theoretical insights, showing their substantial significance in advancing precise process optimization strategies and cost-efficient measures for controlling camber.

Evolution of microstructure, texture and formability of Al–Mg–Si alloys at different hot rolling finish temperatures

The impact of hot rolling finish temperature (HRFT) on the evolution of microstructure, texture, as well as formability—including deep drawability and bendability—of Al–Mg–Si alloy was studied in present work. The obtained results reveal that HRFT has a notable influence on the dynamic softening and dynamic precipitation behaviors during the hot rolling process of the investigated alloy. This leads to the volume fraction and number density of micro-sized Mg2Si particles increase as the increase of HRFT, those of nano-sized particles decrease, and the dislocation density decrease, in the hot-rolled sheets. These microstructural variations persist in the cold-rolled sheets, subsequently affecting the ultimate microstructure, texture, as well as formability of T4P sheets. The deep drawability improves as the HRFT rises, as indicated by the increase in normal anisotropy (r‾) and decrease in planar anisotropy (Δr). This is attributed to the weakening of texture intensity. The bendability, quantified by the minimum hemming factor (Rmin/t), deteriorates as the HRFT rises from 260 °C to 390 °C, attributed to the strengthening of P component along with the weakening of Cube component. Conversely, with the HRFT rises from 390 °C to 420 °C, the bendability improves dramatically due to the significant reduction in the average grain size. A combination of excellent deep drawability and bendability could be obtained by elevating the HRFT to 420 °C, attributed to the combined effect of weakened texture intensity and fine grains.

Evolution of the Microstructure, Phase Composition and Thermomechanical Properties of the CuZnIn Alloys, Achieved by Thermally Controlled Phase Transitions

Ternary alloys with CuZnIn compositions based on the binary CuZn diagram and the modeled ternary system solidus projection were investigated. The as-cast alloys, hot-rolled sheets, and samples annealed at low temperature were examined. It was found that the α-CuZn solution phase, with minor indium additions (1–2% at.), was the primary phase crystallizing during casting and remained stable at low temperatures. The ternary phase with an approximate composition of Cu8(In,Zn)4.5 and a structure analogous to the high-temperature γ-Cu9In4 phase crystallized from the liquid state and remained stable at low temperatures. This behavior results from the stabilization against peritectoidal decomposition by the Zn atoms when substituting In in the structure. A new phase γ*-Cu9(In,Zn)4 with a modified structure was identified, characterized by a reduced unit cell and an altered electronic structure. The hot-rolling process preserves the phase composition and forms a composite-like structure, with the matrix composition of γ* and large ellipsoidal α-CuZn solution particles. On a microscale, the γ* matrix exhibited a specific structure resulting from segregation processes and was composed of micrometer-sized α-CuZn(In) solution particles and nano-sized β-CuZn phase precipitates. Low-temperature annealing intensifies the γ* matrix decomposition through binary phase precipitation.

Low-cost Ti-6Al-4V containing low content nano-carbon solid solution for achieving high strength and good ductility

With the rapid advancement of the aerospace industry, in addition to higher requirements for material properties, the cost-effective of its production have also attracted more attention. In this work, titanium matrix composite with high performance and low cost was designed using ball milling, spark plasma sintering and hot rolling process, i.e. hydrogenated dehydrogenated Ti and AlV powders as the precursor of Ti-6Al-4 V matrix, and a low content (0.15 wt%) reduced graphene oxide (rGO) with high-activity was selected to reinforce the matrix alloy. The as-rolled composite shows obvious texture orientation along the rolling direction without pores and microcracks. The incorporation of rGO led to the activation of the as-rolled composites along the {0001}[112¯0] type base slip. The as-rolled composite containing only 0.15 wt% rGO exhibits superior yield strength (1308.1 MPa) and ultimate tensile strength (1444.3 MPa), which are 11% and 9.3% higher than those of the matrix alloy, respectively, and the elongation remains at ∼5.6%. The strengthening mechanisms are mainly attributed to the solid solution strengthening effect of interstitial carbon in the matrix after the incorporation of rGO. This work highlights the development potential of low-cost and high-strength titanium matrix composites

Enhancing fusion welding in die-cast Mg alloys: A combined ultrasonic vibration and hot rolling approach for porosity reduction, microstructure refinement, and mechanical property improvement

Severe weld porosity has led the industry to believe that die-cast magnesium alloys cannot be fusion welded. To address this challenge, a new process of ultrasonic vibration coupled with hot rolling was employed to eliminate porosity, and the mechanism associated with weld porosity in die-cast magnesium alloys was analyzed in detail. Unlike conventional welding processes, ultrasonic vibration coupled with hot rolling is effective and efficient. In this study, a roller with ultrasonic vibrations is synchronized with the molten pool to apply pressure to the weld, which is in a semi-solid state on the upper surface. The results showed that hot rolling and ultrasonic vibration coupled with hot rolling could eliminate 78.12 % and 85.5 % of the porosity, respectively. Compared to hot rolling, the ultrasonic vibration coupled with the hot rolling process resulted in smaller and fewer porosities and finer β-Mg17Al12. This is attributed to the cavitation effect of ultrasonic vibration that promotes bubble overflow and breaks the β-Mg17Al12 dendrites in the melt pool, as well as the thermal effect that improves the plasticity of the weld. Furthermore, after closing the porosity under pressure, recrystallized grains will be produced around it. Tensile test results indicated that hot rolling was able to increase the ultimate tensile strength by 84.21 % and elongation by 44.03, whereas ultrasonic vibration coupled with hot rolling was able to increase the ultimate tensile strength by 244.46 % and elongation by 71.70 %. Combining the micron-scale industrial computed tomography results with theoretical calculations, it is found that the porosity of die-cast magnesium alloys is mainly caused by nitrogen, and they originate from gas entrapment during the die-casting process; further, the formation mechanism of die-cast magnesium alloys' fusion-welding porosity is revealed in detail. A physical model of the formation process of welded porosity morphology was established, and the analysis suggested that the pattern of the inner wall of the porosity was related to the Kelvin–Helmholtz instability. This research is expected to improve the weld quality of alloys manufactured by the die-casting process.

Enhancing the fatigue resistance of high and medium entropy alloys by manufacturing-driven microstructural developments

Excellent fatigue performance is essential for broader applications of structural materials. In the present work, we report a microstructural design that improves fatigue resistance for high and medium-entropy alloys fabricated by direct energy deposition and hot-rolling processes. Specifically, we discover that the concurrent evolution of microstructures with fine-structure, including stacking faults, nano-twins and hexagonal-close-packed (HCP) structures, leads to zig-zag fracture that hinders crack propagation under cyclic loadings. These multiple characteristic microstructures improve fatigue resistance, which are attributed to the combination of low effective stacking fault energy and a high capacity for strain energy density. Anisotropic microstructural evolution is driven by the correlation between partial dislocations and the resolved shear stresses depending on the crystallographic orientation relationship. Consequently, stacking faults and nano-twins form prominently in the {111} grains under tension and in the {200} grains under compression. The current work provides an effective method to design advanced alloys for high fatigue resistance through microstructural tuning that controls the stacking fault energy combined by manufacturing processes.