熱間圧延の摩擦係数に及ぼす潤滑油因子の影響と潤滑メカニズムの解明

Using pure water in comparison to water-based lubricant containing 4% TiO2 nanoparticles (NPs), the hot rolling tests of 304 stainless steel were carried out at a rolling temperature of 1050 °C under varying rolling reductions and speeds. The effects of lubrication on rolling force, torque, power and contact friction were systematically investigated. The coefficient of friction (COF) during steady-state hot steel rolling was inversely calculated using a developed flow stress model. The COF models including the effects of rolling reduction and speed were proposed via multiple linear regression. The results indicated that the use of the nanolubricant enabled a reduction of rolling force up to 6.1% and decreases in rolling torque and power up to 21.6%, compared to that of water condition. The results obtained from the linear regression agreed well with those from the inverse calculation, suggesting the developed COF models had high accuracy. The lubrication mechanisms were derived from a boundary lubrication regime, owing to ball bearing and mending effects of TiO2 NPs, and formation of thin lubricant film under high rolling pressure.

Recently, customers are demanding for hot rolled strip products to have tight oxide scales on the surfaces. Therefore, high finishing rolling temperature, low coiling temperature and fast finishing rolling speed have to be used to obtain tight oxide scale, which is different from conventional controlled rolling. In order to ensure the mechanical properties at the same time, a framework consisting of the Bayesian neural network and multi-objective particle swarm optimization has been established to determine the optimal hot strip rolling parameters. Due to excellent generalization ability, the Bayesian neural network was employed to develop the model for the prediction of mechanical properties of hot rolled automotive beam steels. The accuracy between the measured and predicted values was within ±30 MPa and ±4% for strength and elongation, respectively, providing a reliable model for the optimal process design. By applying multi-objective particle swarm optimization, the optimized hot rolling process was obtained for the production of hot rolled automotive beam steel with “Tight Oxide Scale”. Industrial trials have been carried out, which showed good agreement with the optimized hot strip rolling processes. It has been theoretically and practically proven that the optimal process design framework can effectively locate the optimal processing window for hot strip rolling.

The coupling machine learning for microstructural evolution and rolling force during hot strip rolling of steels

Serrated yielding behavior after cold and hot rolling of a high Mg content Al–Mg alloy

Event Abstract Back to Event A multipass "low-strain-per-pass" thermomechanical processing for strengthening biomedical Co−Cr−Mo alloys Manami Mori1, Kenta Yamanaka2, Shigeo Sato3 and Akihiko Chiba2 1 National Institute of Technology, Sendai College, Department of Materials and Environmental Engineering, Japan 2 Tohoku University, Institute for Materials Research, Japan 3 Ibaraki University, Graduate School of Science and Engineering/Institute of Applied Beam Science, Japan Introduction: Owing to their excellent wear and corrosion resistance, Co−Cr−Mo alloys have been used in various biomedical devices, such as bearings in artificial hip joints, rods for spinal-instrumentation surgery, bone plates, and screws. Further strengthening of biomedical Co−Cr−Mo alloys is desired, owing to the demand for improvements to their durability in these applications. For this purpose, we focused on dynamic recrystallization (DRX), which occurs during hot deformation at temperatures above ~1273 K, as a grain refining mechanism[1],[2]. Though the DRX-mediated grain refining process can produce exceptionally high-strength Co–Cr–Mo alloys with ultrafine-grained microstructures[3], it is still not viable in the industrial sense. In this paper, we present a concept—multipass “low-strain-per-pass” thermomechanical processing—as a method for obtaining high-strength Ni-free Co−Cr−Mo alloy. The process is carefully designed to enhance the strain accumulation for strengthening. The concept was verified by performing hot rolling of a Co−Cr−Mo alloy and the strengthening mechanisms involved were also examined. Materials and Methods: A Ni-free Co–28Cr–6Mo (mass%) alloy with 0.13 mass% nitrogen was processed by hot rolling at 1473 K with a height reduction of ~1 mm per pass. This process was repeated to realize accumulative height reduction (r) of 30%, 60% and 90%. Microstructures were investigated by scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and conventional and high-resolution transmission electron microscopy (TEM and HRTEM). Mechanical properties were evaluated by room temperature tensile testing. We analyzed microstructural evolution during the hot rolling process using the convolutional multiple whole profile (CMWP) fitting for X-ray diffraction (XRD) line profiles. Results and Discussion: The EBSD analysis revealed that the grain refinement observed in this work was less significant than that in the DRX-dominated processes and the minimum grain size obtained was 37 μm for r = 90%. This indicates the “less active DRX conditions”. The strength increased monotonically with hot-rolling reduction, eventually reaching 1400 MPa in 0.2% proof stress, which is comparable to that obtained by the DRX-mediated process (Fig. 1). The XRD line-profile analysis for the hot-rolled samples revealed a drastic increase in the dislocation density with an increase in hot-rolling reduction (Fig. 2a) and proposed that the significant strengthening was primarily driven by the increased dislocation density. The CMWP analyses and complementary TEM observations also found that the amounts of stacking faults and resulting deformation twins increased with increasing hot rolling reduction (Fig. 2b). Consequently, extra strengthening, which originates from contributions of these planar defects, became apparent for greater hot-rolling reductions and contributed to the extremely high strength. Figure 1. Tensile properties of hot-rolled Co−Cr−Mo alloy prepared in this study. Figure 2. (a) Dislocation density and (b) stacking fault probability as a function of equivalent strain imposed during hot rolling. Conclusions: The obtained results demonstrated that our strategy is effective to increase the strength of Ni-free Co−Cr−Mo alloys without loss of ductility. The proposed strategy helps in reconsidering the existing strengthening strategy for the alloys, and thus, a novel feasible manufacturing route using conventional hot deformation processing is realized.

Effects of oil-in-water based nanolubricant containing TiO2 nanoparticles in hot rolling of 304 stainless steel

This paper studies a new scheduling problem in a steel plant, referring to continuous casting (CC), reheating furnace, and hot rolling (HR) processes, which is meaningful and important to the production efficiency and energy saving. First, the problem is modeled as a combination of two coupled subproblems: one assigns casts to continuous casting (CC) machines, decides sequence and start time for casts and rolling units; and another assigns furnaces and decides start time for rolling slabs in a reheating furnace. The objectives are to maximize the number of slabs processed in a mode of hot charge rolling or direct hot charge rolling so as to reduce the energy requirement and the temperature drop of slabs and minimize the residence time of slabs in a reheating furnace to save energy. Then, based on a Benders decomposition strategy, a hybrid algorithm that combines mixed-integer programming and constraint programming is designed to solve each subproblem. An effective cut-generation scheme based on a priority relationship is developed for resolving resource conflicts and unsatisfied setup time constraints. Finally, extensive experiments are conducted to verify the effectiveness of the proposed approach. Note to Practitioners —This paper deals with a scheduling problem arising from CC to HR process in steel manufacturing. It decomposes the original problem into a CC–HR scheduling problem and a reheating furnace scheduling problem. Previously, such a problem is handled, respectively, which always cause energy waste and mismatching plan. This paper takes complex technology constraints into full account to minimize energy waste and energy requirement and establishes nonlinear mathematical models for studied problems. Then, it designs a hybrid algorithm combined mixed-integer programming and constraint programming. The results demonstrate that the proposed approach can solve them effectively. The obtained solution gives decision makers some desired reference to determine a right schedule when actual production tasks are executed.

Recently, hot rolling with a severely high redution was developed to make the ultra fine grained steels. The high reduction in the hot rolling caused some troubles such as increase of the rolling load, occurrence of friction pick up and so on. To solve these problems, new lubricants with high coefficient of friction at biting and low coefficient of friction during hot rolling must be developed. The lubricants cannot be estimated using the two-disks testing machine or the pin-on-disk testing machine. So, a testing machine to simulate hot rolling in the laboratory has been developed by the author et al. The performance of the simulator is evaluated at a hot rolling temperature of 800°C using SPHC strip with a width of 22 mm and a thickness of 9 mm, SKD61 roll with a diameter of 100 mm and a width of 60 mm and new lubricants. Results from experiment to measure the coefficient of friction decided the lubricity of the lubriconts in hot rolling with a severely high reduction can be evaluated.

Hot rolling processes have been extensively used to produce round bars by reducing the cross‐sectional area of continuously cast steel. The current trend toward increasing productivity often requires a more aggressive reduction per pass. Establishing safe and optimized hot rolling parameters must be determined to avoid damage while deforming the specific steel composition. Understanding the damage mechanism during the metal forming process is vital for product quality. Herein, a combined experimental and simulation approach is developed to track the evolution potential damage during hot bar rolling. Hot tension tests are conducted on as‐cast vanadium microalloyed 15V38 steel at different hot rolling temperatures and strain rate conditions to develop Johnson–Cook‐type material model. A thermomechanical finite element model is developed to simulate potential damage trends in a 12‐pass square‐to‐round and 8‐pass round‐to‐round standard industrial hot rolling process, employing damage criteria. Results are illustrated by creating a damage map at each rolling pass to determine the critical hot rolling conditions for damage initiation. Several parametric studies are also performed to illustrate the application of the suggested methodology for hot rolling process optimization. Results show that the probability of the damage initiation is higher at higher pass reductions and lower temperatures.

The influence of lubrication on profile and flatness control during asymmetry self-compensating work roll (ASR) hot strip rolling process is studied in order to meet the requirement of schedule-free rolling (SFR) campaigns for non-oriented electrical steel production with identical strip width. The effects of lubrication on rolling force, surface topography, and work roll wear are analyzed through experimental data. A work roll wear model for a wide non-oriented electrical steel production considered lubrication during the hot rolling process is built, which can accurately reflect the work roll wear during the hot rolling process with lubrication. A 3D finite element model for roll stack considering lubrication is built. The effects of shifting strategy on ASR work roll wear contour, loaded roll gap crown, and edge drop are analyzed based on the models. The optimal shifting rhythm is 1, and the optimal shifting step is 2 ~ 3 mm. By combining the ASR technology with lubrication, the life of work rolls expands from 70 to 100 ~ 150 by different shifting step, the loaded roll gap crown can be efficiently controlled by bending force and the edge drop control ability can be improved efficiently within an entire rolling campaign.

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.

A hybrid artificial intelligence algorithm for fault diagnosis of hot rolled strip crown imbalance

High-speed steel (HSS) materials are universally used as work rolls for the hot rolling of stainless steels. Their use has increased the output of the rolling mill and decreased roll material consumption and grinding. Sticking defects often occur, however, during the hot rolling process. In this article, extreme pressure (EP) additives were dropped on the HSS samples at high temperature. Zinc dialkyl dithiophosphate (ZDDP) was chosen as the most effective EP additive by scratch tests on the HSS samples. In order to determine the optimum proportion of ZDDP in the lubricant, two reduction rates were tested on a Hille 100 experimental rolling mill by hot rolling ferritic stainless steel 445J1M at five different concentrations of ZDDP. The mechanism of EP additive action during the hot rolling process was also investigated. By analyzing the deformation behavior of the oxide scale of samples after hot rolling using different proportions of ZDDP, it was found that 20% ZDDP in the lubricant is the preferred concentration for industrial application.

Hot rolling can improve the mechanical properties after heat treatment by improving the microstructure. The effect of hot rolling (HR) deformation on the microstructural transformation of G20CrNi2MoA bearing steel in the subsequent CQT (carburizing-quenching and tempering) and RQT (reheating-quenching and tempering) processes was studied. The results indicate that the austenite grain size decreased by 20% after 45% hot rolling reduction, and the number of large-angle grain boundaries increased due to the recovery and recrystallization induced by hot deformation. The refinement effect of hot deformation on austenite grains was retained after dual austenitizing, and the large-angle grain boundaries and massive dislocation in the grains caused by hot deformation promoted the diffusion of carbon atoms during carburization, resulting in a higher surface carbon concentration. The refined grains and higher carbon concentration affected the volume fraction and size of undissolved carbides in RQT specimens. When the initial hot rolling reduction reached 45%, the average particle size of carbides decreased by 40%, and the area volume fraction increased by 37%. The Vickers hardness increased, but the friction coefficient and wear rate were significantly reduced with the increase in the initial hot rolling reduction. The main reasons for the improved wear resistance were fine grains, superior carbide distribution and high hardness.

Fuzzy control algorithm for the prediction of tension variations in hot rolling