Development and prospects of molten steel deoxidation in steelmaking process

In the long traditional process of steelmaking,excess oxygen is blown into the converter,and alloying elements are used for deoxidation.This inevitably results in excessive deoxidation of products remaining within the steel liquid,affecting the cleanliness of the steel.With the increasing requirements for steel performance,reducing the oxygen content in the steel liquid and ensuring its high cleanliness is necessary.After more than a hundred years of development,the total oxygen content in steel has been reduced from approximately 100×10^(-6)to approximately 10×10^(-6),and it can be controlled below 5×10^(-6)in some steel grades.A relatively stable and mature deoxidation technology has been formed,but further reducing the oxygen content in steel is no longer significant for improving steel quality.Our research team developed a deoxidation technology for bearing steel by optimizing the entire conventional process.The technology combines silicon–manganese predeoxidation,ladle furnace diffusion deoxidation,and vacuum final deoxidation.We successfully conducted industrial experiments and produced interstitial-free steel with natural decarbonization predeoxidation.Non-aluminum deoxidation was found to control the oxygen content in bearing steel to between 4×10^(-6) and 8×10^(-6),altering the type of inclusions,eliminating large particle Ds-type inclusions,improving the flowability of the steel liquid,and deriving a higher fatigue life.The natural decarbonization predeoxidation of interstitial-free steel reduced aluminum consumption and production costs and significantly improved the quality of cast billets.

Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms

This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.

Interfacial reaction between AZ91D magnesium alloy melt and mild steel under high temperature

The metallurgical quality control of magnesium(Mg)and Mg alloys in melting process is required to ensure a satisfied mechanical and corrosion performance,while the typical used steel crucible introduces impurities and interfacial interaction during melting process.Therefore,a systematic study about impurities diffusion and interfacial interaction between molten Mg and steel is necessary.In the present study,the interfacial reaction between molten AZ91D Mg alloy and mild steel during melting process was investigated with the melting temperatures of 700℃,750℃ and 800℃.The results show that Al(Fe,Mn)intermetallic layer is the intermetallic primarily formed at the interfaces of AZ91D melt and mild steel.Meanwhile,Al_(8)(Mn,Fe)5is indexed between Al(Fe,Mn)and AZ91D.AlFe_(3)C appears between the mild steel and Al(Fe,Mn)at 700℃ and 750℃,but absent at 800℃ due to the increased solubility of carbon in Mg matrix.It is found that the growth of the intermetallic layer is controlled by diffusion mechanism,and Al and Mn are the dominant diffusing species in the whole interfacial reaction process.By measuring the thickness of different layers,the growth constant was calculated.It increases from 1.89(±0.03)×10^(-12)m^(2)·s^(-1)at 700℃ to 3.05(±0.05)×10^(-12)m^(2)·s^(-1)at 750℃,and 5.18(±0.05)×10^(-12)m^(2)·s^(-1)at 800℃.Meanwhile,the content of Fe is linearly increased in AZ91D with the increase of holding time at 700℃ and 750℃,while it shows a significantly increment after holding for 8 h at 800℃,indicating holding temperature is more crucial to determine the Fe content of AZ91D than holding time.

Stress-assisted corrosion mechanism of 3Ni steel by using gradient boosting decision tree machining learning method

Traditional 3Ni weathering steel cannot completely meet the requirements for offshore engineering development,resulting in the design of novel 3Ni steel with the addition of microalloy elements such as Mn or Nb for strength enhancement becoming a trend.The stress-assisted corrosion behavior of a novel designed high-strength 3Ni steel was investigated in the current study using the corrosion big data method.The information on the corrosion process was recorded using the galvanic corrosion current monitoring method.The gradi-ent boosting decision tree(GBDT)machine learning method was used to mine the corrosion mechanism,and the importance of the struc-ture factor was investigated.Field exposure tests were conducted to verify the calculated results using the GBDT method.Results indic-ated that the GBDT method can be effectively used to study the influence of structural factors on the corrosion process of 3Ni steel.Dif-ferent mechanisms for the addition of Mn and Cu to the stress-assisted corrosion of 3Ni steel suggested that Mn and Cu have no obvious effect on the corrosion rate of non-stressed 3Ni steel during the early stage of corrosion.When the corrosion reached a stable state,the in-crease in Mn element content increased the corrosion rate of 3Ni steel,while Cu reduced this rate.In the presence of stress,the increase in Mn element content and Cu addition can inhibit the corrosion process.The corrosion law of outdoor-exposed 3Ni steel is consistent with the law based on corrosion big data technology,verifying the reliability of the big data evaluation method and data prediction model selection.

Flow characteristics and hot workability of a typical low-alloy high-strength steel during multi-pass deformation

Heavy components of low-alloy high-strength(LAHS) steels are generally formed by multi-pass forging. It is necessary to explore the flow characteristics and hot workability of LAHS steels during the multi-pass forging process, which is beneficial to the formulation of actual processing parameters. In the study, the multi-pass hot compression experiments of a typical LAHS steel are carried out at a wide range of deformation temperatures and strain rates. It is found that the work hardening rate of the experimental material depends on deformation parameters and deformation passes, which is ascribed to the impacts of static and dynamic softening behaviors. A new model is established to describe the flow characteristics at various deformation passes. Compared to the classical Arrhenius model and modified Zerilli and Armstrong model, the newly proposed model shows higher prediction accuracy with a confidence level of 0.98565. Furthermore, the connection between power dissipation efficiency(PDE) and deformation parameters is revealed by analyzing the microstructures. The PDE cannot be utilized to reflect the efficiency of energy dissipation for microstructure evolution during the entire deformation process, but only to assess the efficiency of energy dissipation for microstructure evolution in a specific deformation parameter state.As a result, an integrated processing map is proposed to better study the hot workability of the LAHS steel, which considers the effects of instability factor(IF), PDE, and distribution and size of grains. The optimized processing parameters for the multi-pass deformation process are the deformation parameters of 1223–1318 K and 0.01–0.08 s^(-1). Complete dynamic recrystallization occurs within the optimized processing parameters with an average grain size of 18.36–42.3 μm. This study will guide the optimization of the forging process of heavy components.

Improving creep strength of the fine-grained heat-affected zone of novel 9Cr martensitic heat-resistant steel via modified thermo-mechanical treatment

The infamous type Ⅳ failure within the fine-grained heat-affected zone (FGHAZ) in G115 steel weldments seriously threatens the safe operation of ultra-supercritical (USC) power plants.In this work,the traditional thermo-mechanical treatment was modified via the replacement of hot-rolling with cold rolling,i.e.,normalizing,cold rolling,and tempering (NCT),which was developed to improve the creep strength of the FGHAZ in G115 steel weldments.The NCT treatment effectively promoted the dissolution of preformed M_(23)C_(6)particles and relieved the boundary segregation of C and Cr during welding thermal cycling,which accelerated the dispersed reprecipitation of M_(23)C_(6) particles within the fresh reaustenitized grains during post-weld heat treatment.In addition,the precipitation of Cu-rich phases and MX particles was promoted evidently due to the deformation-induced dislocations.As a result,the interacting actions between precipitates,dislocations,and boundaries during creep were reinforced considerably.Following this strategy,the creep rupture life of the FGHAZ in G115 steel weldments can be prolonged by 18.6%,which can further push the application of G115 steel in USC power plants.

An Integrated Analysis on the Synergistic Reduction of Carbon and Pollution Emissions from China’s Iron and Steel Industry

Decarbonization and decontamination of the iron and steel industry(ISI),which contributes up to 15%to anthropogenic CO_(2) emissions(or carbon emissions)and significant proportions of air and water pollutant emissions in China,are challenged by the huge demand for steel.Carbon and pollutants often share common emission sources,indicating that emission reduction could be achieved synergistically.Here,we explored the inherent potential of measures to adjust feedstock composition and technological structure and to control the size of the ISI to achieve carbon emission reduction(CER)and pollution emission reduction(PER).We investigated five typical pollutants in this study,namely,petroleum hydrocarbon pollutants and chemical oxygen demand in wastewater,particulate matter,SO_(2),and NO_(x) in off gases,and examined synergies between CER and PER by employing cross elasticity for the period between 2022 and 2035.The results suggest that a reduction of 8.7%-11.7%in carbon emissions and 20%-31%in pollution emissions(except for particulate matter emissions)could be achieved by 2025 under a high steel scrap ratio(SSR)scenario.Here,the SSR and electric arc furnace(EAF)ratio serve critical roles in enhancing synergies between CER and PER(which vary with the type of pollutant).However,subject to a limited volume of steel scrap,a focused increase in the EAF ratio with neglection of the available supply of steel scrap to EAF facilities would lead to an increase carbon and pollution emissions.Although CER can be achieved through SSR and EAF ratio optimization,only when the crude steel production growth rate remains below 2.2%can these optimization measures maintain the emissions in 2030 at a similar level to that in 2021.Therefore,the synergistic effects between PER and CER should be considered when formulating a development route for the ISI in the future.

Reliability Prediction of Wrought Carbon Steel Castings under Fatigue Loading Using Coupled Mold Optimization and Finite Element Simulation

The fatigue life and reliability of wrought carbon steel castings produced with an optimized mold design are predicted using a finite element method integrated with reliability calculations.The optimization of the mold is carried out using MAGMASoft mainly based on porosity reduction as a response.After validating the initial mold design with experimental data,a spring flap,a common component of an automotive suspension system is designed and optimized followed by fatigue life prediction based on simulation using Fe-safe.By taking into consideration the variation in both stress and strength,the stress-strength model is used to predict the reliability of the component under fatigue loading.Under typical loading conditions of 70 kN,the analysis showed that 95%of the steel spring flaps achieve infinite life.However,under maximum loading conditions of 90 kN,reliability declined significantly,with only 65%of the spring flaps expected to withstand the stress without failure.The study also identified a safe load-induced stress of 95 MPa on the spring flap.The findings suggest that transitioning from forged to cast spring flaps is a promising option,particularly if further improvements in casting design reduce porosity to negligible levels,potentially achieving 100%reliability under typical loading conditions.This integrated approach of mold optimization coupled with reliability estimation under realistic service loading conditions offers significant potential for the casting industry to produce robust,cost-effective products.

Value of Charpy impact test results with sub-and half-size specimens extracted from overage steel bridge members

For the maintenance of steel bridges,the mechanical properties of steel used in the bridges must be elucidated.When enough dimensions of specimens cannot be extracted from the actual members,miniaturized specimens are used for evaluation.In the case of the Charpy impact test,sub-and half-size specimens are specified instead of full-size specimens of which the thickness is 10 mm.The value of absorbed energy and energy transient temperature obtained by Charpy impact tests with sub-size and half-size specimens were investigated from the viewpoint of maintenance of bridges in this study.The absorbed energy was not in proportion to the thickness of specimens of steel used in the actual overage bridges.The tendency of energy transient temperature obtained by thin specimens of the overage steel differed from that of the present steel.A method for evaluating the performance against brittle fracture occurrence based on the WES3003 criterion was examined.The results show the significance of evaluation based on the energy transient temperature for reasonable maintenance of bridges.

Recent progress in visualization and digitization of coherent transformation structures and application in high-strength steel

High-strength steels are mainly composed of medium-or low-temperature microstructures,such as bainite or martensite,with coherent transformation characteristics.This type of microstructure has a high density of dislocations and fine crystallographic structural units,which ease the coordinated matching of high strength,toughness,and plasticity.Meanwhile,given its excellent welding perform-ance,high-strength steel has been widely used in major engineering constructions,such as pipelines,ships,and bridges.However,visual-ization and digitization of the effective units of these coherent transformation structures using traditional methods(optical microscopy and scanning electron microscopy)is difficult due to their complex morphology.Moreover,the establishment of quantitative relationships with macroscopic mechanical properties and key process parameters presents additional difficulty.This article reviews the latest progress in microstructural visualization and digitization of high-strength steel,with a focus on the application of crystallographic methods in the development of high-strength steel plates and welding.We obtained the crystallographic data(Euler angle)of the transformed microstruc-tures through electron back-scattering diffraction and combined them with the calculation of inverse transformation from bainite or martensite to austenite to determine the reconstruction of high-temperature parent austenite and orientation relationship(OR)during con-tinuous cooling transformation.Furthermore,visualization of crystallographic packets,blocks,and variants based on actual OR and digit-ization of various grain boundaries can be effectively completed to establish quantitative relationships with alloy composition and key process parameters,thereby providing reverse design guidance for the development of high-strength steel.

Mechanical Behavior and Microstructure Evolution during Tensile Deformation of Twinning Induced Plasticity Steel Processed by Warm Forgings

The mechanical behavior and microstructural evolution of an Fe-30Mn-3Al-3Si twinninginduced plasticity(TWIP)steel processed using warm forging was investigated.It is found that steel processed via warm forging improves comprehensive mechanical properties compared to the TWIP steel processed via cold rolling,with a high tensile strength(R_(m))of 793 MPa,a yield strength(R_(P))of 682 MPa,an extremely large R_(P)/R_(m)ratio as high as 0.86 as well as an excellent elongation rate of 46.8%.The microstructure observation demonstrates that steel processed by warm forging consists of large and elongated grains together with fine,equiaxed grains.Complicated micro-defect configurations were also observed within the steel,including dense dislocation networks and a few coarse deformation twins.As the plastic deformation proceeds,the densities of dislocations and deformation twins significantly increase.Moreover,a great number of slip lines could be observed in the elongated grains.These findings reveal that a much more dramatic interaction between microstructural defect and dislocations glide takes place in the forging sample,wherein the fine and equiaxed grains propagated dislocations more rapidly,together with initial defect configurations,are responsible for enhanced strength properties.Meanwhile,larger,elongated grains with more prevalently activated deformation twins result in high plasticity.

Effect of temperature and time on the precipitation ofκ-carbides in Fe-28Mn-10Al-0.8C low-density steels:Aging mechanism and its impact on material properties

In low-density steel,κ-carbides primarily precipitate in the form of nanoscale particles within austenite grains.However,their precipitation within ferrite matrix grains has not been comprehensively explored,and the second-phase evolution mechanism during aging remains unclear.In this study,the crystallographic characteristics and morphological evolution ofκ-carbides in Fe-28Mn-10Al-0.8C(wt%)low-density steel at different aging temperatures and times and the impacts of these changes on the steels’microhardness and properties were comprehensively analyzed.Under different heat treatment conditions,intragranularκ-carbides exhibited various morpho-logical and crystallographic characteristics,such as acicular,spherical,and short rod-like shapes.At the initial stage of aging,acicularκ-carbides primarily precipitated,accompanied by a few spherical carbides.κ-Carbides grew and coarsened with aging time,the spherical carbides were considerably reduced,and rod-like carbides coarsened.Vickers hardness testing demonstrated that the material’s hardness was affected by the volume fraction,morphology,and size ofκ-carbides.Extended aging at higher temperatures led to an increase in carbide size and volume fraction,resulting in a gradual rise in hardness.During deformation,the primary mechanisms for strengthening were dislocation strengthening and second-phase strengthening.Based on these findings,potential strategies for improving material strength are proposed.

Effects of heating temperature and atmosphere on element distribution and microstructure in high-Mn/Al austenitic low-density steel

The elemental distribution and microstructure near the surface of high-Mn/Al austenitic low-density steel were investigated after isothermal holding at temperatures of 900-1200℃ in different atmospheres,including air,N2,and N_(2)+CO_(2).No ferrite was formed near the surface of the experimental steel during isothermal holding at 900 and 1000℃ in air,while ferrite was formed near the steel sur-face at holding temperatures of 1100 and 1200℃.The ferrite fraction was larger at 1200℃ because more C and Mn diffused to the sur-face,exuded from the steel,and then reacted with N and O to form oxidation products.The thickness of the compound scale increased owing to the higher diffusion rate at higher temperatures.In addition,after isothermal holding at 1100℃ in N2,the Al content near the surface slightly decreased,while the C and Mn contents did not change.Therefore,no ferrite was formed near the surface.However,the near-surface C and Al contents decreased after holding at 1100℃in the N_(2)+CO_(2)mixed atmosphere,resulting in the formation of a small amount of ferrite.The compound scale was thickest in N2,followed by the N_(2)+CO_(2)mixed atmosphere,and thinnest in air.Overall,the element loss and ferrite fraction were largest after holding in air at the same temperature.The differences in element loss and ferrite frac-tion between in N2 and N_(2)+CO_(2)atmospheres were small,but the compound scale formed in N2 was significantly thicker.According to these results,N_(2)+CO_(2)is the ideal heating atmosphere for the industrial production of high-Mn/Al austenitic low-density steel.

Corrosion Test of the Steel Plate in a WJ-8 Fastener for High Speed Rail

It was found that the steel plate in the composite plate in the WJ-8 fastener used in high speed rail is rusty. The objective of this study is to test the zinc coating of the steel plate. A literature review was conducted to identify the zinc coating techniques, and the companies that can provide different coating service was identified. A salt fog chamber was built that was in compliance with the ANSI B117 code, and the steel plates that were coated by the identified companies were tested using the salt fog chamber. The results indicated that the coating technique that had the best performance in preventing corrosion was the Greenkote plates with passivation. The galvanized option had the roughest coating layer, and it was the most reactive in the salt water solution. This makes it non-ideal for the dynamic rail environment because the increased friction of the plate could damage the supports, especially during extreme temperatures that would cause the rail to expand or contract. Greenkote with Phosphate and ArmorGalv also provided increased corrosion prevention with a smooth, strong finish, but it had more rust on the surface area than the Greenkote with ELU passivation. The ArmorGalv sample had more rust on the surface area than the Greenkote samples. This may not be a weakness in the ArmorGalv process;rather, it likely was the result of this particular sample not having the added protection of a colored coating.

Effect of Mn addition on microstructure and mechanical properties of GX40CrNiSi25-12 austenitic heat resistant steel

Three types of steels were designed on the basis of GX40CrNiSi25-12 austenitic heat resistant steel by adding different Mn contents(2wt.%,6wt.%,and 12wt.%).Thermodynamic calculation,microstructure characterization and mechanical property tests were conducted to investigate the effect of Mn addition on the microstructure and mechanical properties of the austenitic heat resistant steel.Results show that the matrix structure in all the three types of steels at room temperature is completely austenite.Carbides NbC and M_(23)C_(6)precipitate at grain boundaries of austenite matrix.With the increase of Mn content,the number of carbides increases and their distribution becomes more uniform.With the Mn content increases from 1.99%to 12.06%,the ultimate tensile strength,yield strength and elongation increase by 14.6%,8.0%and 46.3%,respectively.The improvement of the mechanical properties of austenitic steels can be explained by utilizing classic theories of alloy strengthening,including solid solution strengthening,precipitation strengthening,and grain refinement.The increase in alloy strength can be attributed to solid solution strengthening and precipitation strengthening caused by the addition of Mn.The improvement of the plasticity of austenitic steels can be explained from two aspects:grain refinement and homogenization of precipitated phases.

Critical precipitation behavior of MnTe inclusions in resulfurized steels during solidification

Te treatment is an effective method for modifying sulfide inclusions,and MnTe precipitation has an important effect on thermal brittleness and steel corrosion resistance.In most actual industrial applications of Te treatment,MnTe precipitation is unexpected.The critical precipitation behavior of MnTe inclusions was investigated through scanning electron microscopy,transmission electron microscopy,machine learning,and first-principles calculation.MnTe preferentially precipitated at the container mouth for sphere-like sulfides and at the interface between MnS grain boundaries and steel matrix for rod-like sulfides.The MnS/MnTe interface was semicoherent.A composition transition zone with a rock-salt structure exhibiting periodic changes existed to maintain the semicoherent interface.The critical precipitation behavior of MnTe inclusions in resulfurized steels involved three stages at varying temperatures.First,Mn(S,Te)precipitated during solidification.Second,MnTe with a rock-salt structure precipitated from Mn(S,Te).Third,MnTe with a hexagonal NiAs structure transformed from the rock-salt structure.The solubility of Te in MnS decreased with decreasing temperature.The critical precipitation behavior of MnTe inclusions in resulfurized steels was related to the MnS precipitation temperature.With the increase in MnS precipitation temperature,the critical Te/S weight ratio decreased.In consideration of the cost-effectiveness of Te addition for industrial production,the Te content in resulfurized steels should be controlled in accordance with MnS precipitation temperature and S content.

Electromagnetic responses on microstructures of duplex stainless steels based on 3D cellular and electromagnetic sensor finite element models

Microstructures determine mechanical properties of steels,but in actual steel product process it is difficult to accurately control the microstructure to meet the requirements.General microstructure characterization methods are time consuming and results are not rep-resentative for overall quality level as only a fraction of steel sample was selected to be examined.In this paper,a macro and micro coupled 3D model was developed for nondestructively characterization of steel microstructures.For electromagnetic signals analysis,the relative permeability value computed by the micro cellular model can be used in the macro electromagnetic sensor model.The effects of different microstructure components on the relative permeability of duplex stainless steel(grain size,phase fraction,and phase distribu-tion)were discussed.The output inductance of an electromagnetic sensor was determined by relative permeability values and can be val-idated experimentally.The findings indicate that the inductance value of an electromagnetic sensor at low frequency can distinguish dif-ferent microstructures.This method can be applied to real-time on-line characterize steel microstructures in process of steel rolling.

Microstructural evolution and strengthening mechanism of aligned steel fiber cement-based tail backfills exposed to electromagnetic induction

Cemented tailings backfill(CTB)not only boosts mining safety and cuts surface environmental pollution but also recovers ores previously retained as pillars,thereby improving resource utilization.The use of alternative reinforcing products,such as steel fiber(SF),has continuously strengthened CTB into SFCTB.This approach prevents strength decreases over time and reinforces its long-term durability,especially when mining ore in adjacent underground stopes.In this study,various microstructure and strength tests were performed on SFCTB,considering steel fiber ratio and electromagnetic induction strength effects.Lab findings show that combining steel fibers and their distribution dominantly influences the improvement of the fill’s strength.Fill’s strength rises by fiber insertion and has an evident correlation with fiber insertion and magnetic induction strength.When magnetic induction strength is 3×10^(-4) T,peak uniaxial compressive stress reaches 5.73 MPa for a fiber ratio of 2.0vol%.The cracks’expansion mainly started from the specimen’s upper part,which steadily expanded downward by increasing the load until damage occurred.The doping of steel fiber and its directional distribution delayed crack development.When the doping of steel fiber was 2.0vol%,SFCTBs showed excellent ductility characteristics.The energy required for fills to reach destruction increases when steel-fiber insertion and magnetic induction strength increase.This study provides notional references for steel fibers as underground filling additives to enhance the fill’s durability in the course of mining operations.

Effects of iron oxide on crystallization behavior and spatial distribution of spinel in stainless steel slag

Chromium plays a vital role in stainless steel due to its ability to improve the corrosion resistance of the latter.However,the re-lease of chromium from stainless steel slag(SSS)during SSS stockpiling causes detrimental environmental issues.To prevent chromium pollution,the effects of iron oxide on crystallization behavior and spatial distribution of spinel were investigated in this work.The results revealed that FeO was more conducive to the growth of spinels compared with Fe2O3 and Fe3O4.Spinels were found to be mainly distrib-uted at the top and bottom of slag.The amount of spinel phase at the bottom decreased with the increasing FeO content,while that at the top increased.The average particle size of spinel in the slag with 18wt%FeO content was 12.8μm.Meanwhile,no notable structural changes were observed with a further increase in FeO content.In other words,the spatial distribution of spinel changed when the content of iron oxide varied in the range of 8wt%to 18wt%.Finally,less spinel was found at the bottom of slag with a FeO content of 23wt%.

A Hybrid Deep Learning and Machine Learning-Based Approach to Classify Defects in Hot Rolled Steel Strips for Smart Manufacturing

Smart manufacturing is a process that optimizes factory performance and production quality by utilizing various technologies including the Internet of Things(IoT)and artificial intelligence(AI).Quality control is an important part of today’s smart manufacturing process,effectively reducing costs and enhancing operational efficiency.As technology in the industry becomes more advanced,identifying and classifying defects has become an essential element in ensuring the quality of products during the manufacturing process.In this study,we introduce a CNN model for classifying defects on hot-rolled steel strip surfaces using hybrid deep learning techniques,incorporating a global average pooling(GAP)layer and a machine learning-based SVM classifier,with the aim of enhancing accuracy.Initially,features are extracted by the VGG19 convolutional block.Then,after processing through the GAP layer,the extracted features are fed to the SVM classifier for classification.For this purpose,we collected images from publicly available datasets,including the Xsteel surface defect dataset(XSDD)and the NEU surface defect(NEU-CLS)datasets,and we employed offline data augmentation techniques to balance and increase the size of the datasets.The outcome of experiments shows that the proposed methodology achieves the highest metrics score,with 99.79%accuracy,99.80%precision,99.79%recall,and a 99.79%F1-score for the NEU-CLS dataset.Similarly,it achieves 99.64%accuracy,99.65%precision,99.63%recall,and a 99.64%F1-score for the XSDD dataset.A comparison of the proposed methodology to the most recent study showed that it achieved superior results as compared to the other studies.