Digital technologies are transforming industry at all levels. Steel has the opportunity to lead all heavy industries as an early adopter of specific digital technologies to improve our sustainability and competitiveness. This column is part of AIST’s strategy to become the epicenter for steel’s digital transformation, by providing a variety of platforms to showcase and disseminate Industry 4.0 knowledge specific for steel manufacturing, from big-picture concepts to specific processes. Fully Automated Rating of Slab Segregation Images for Pipeline Steel on a Continuous Scale
{"title":"Fully Automated Rating of Slab Segregation Images for Pipeline Steel on a Continuous Scale","authors":"K. Dunnett, L. Collins, A. van der Breggen","doi":"10.33313/380/153","DOIUrl":"https://doi.org/10.33313/380/153","url":null,"abstract":"Digital technologies are transforming industry at all levels. Steel has the opportunity to lead all heavy industries as an early adopter of specific digital technologies to improve our sustainability and competitiveness. This column is part of AIST’s strategy to become the epicenter for steel’s digital transformation, by providing a variety of platforms to showcase and disseminate Industry 4.0 knowledge specific for steel manufacturing, from big-picture concepts to specific processes. Fully Automated Rating of Slab Segregation Images for Pipeline Steel on a Continuous Scale","PeriodicalId":226675,"journal":{"name":"AISTech2020 Proceedings of the Iron and Steel Technology Conference","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133128156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stability of the hot strip mill rolling process remains a main topic when it comes to processing thin and hard materials. Strip steering especially at the end of rolling and tail out rips are a main source of unscheduled down times in a hot strip mill. Main focus of this paper is the new X-Roll Guide system to improve mill stability and quality. An overview of SMS group developments in the recent years regarding equipment and control strategies is given. The new side guiding system in the entry area of the finishing mill is introduced and explained with operational examples. The system provides reproducible conditions for the threading process and during rolling. Steering control has a direct benefit on the availability of the mill. New developments of the roll alignment control strategies based on roll force and mill stand entry guide force measurement will be presented. Additionally a camera based measuring system is introduced that generates a direct process feedback of the strip position. It provides together with the roll alignment control the necessary control parameters for adjusting the roll gap and guiding the strip correct centered through the mill. As a summary the SMS group system is explained combining all features.
{"title":"Cutting-Edge Technology for HSM – Strip Steering Control","authors":"C. Mengel, M. Breuer, O. Jepsen","doi":"10.33313/380/117","DOIUrl":"https://doi.org/10.33313/380/117","url":null,"abstract":"Stability of the hot strip mill rolling process remains a main topic when it comes to processing thin and hard materials. Strip steering especially at the end of rolling and tail out rips are a main source of unscheduled down times in a hot strip mill. Main focus of this paper is the new X-Roll Guide system to improve mill stability and quality. An overview of SMS group developments in the recent years regarding equipment and control strategies is given. The new side guiding system in the entry area of the finishing mill is introduced and explained with operational examples. The system provides reproducible conditions for the threading process and during rolling. Steering control has a direct benefit on the availability of the mill. New developments of the roll alignment control strategies based on roll force and mill stand entry guide force measurement will be presented. Additionally a camera based measuring system is introduced that generates a direct process feedback of the strip position. It provides together with the roll alignment control the necessary control parameters for adjusting the roll gap and guiding the strip correct centered through the mill. As a summary the SMS group system is explained combining all features.","PeriodicalId":226675,"journal":{"name":"AISTech2020 Proceedings of the Iron and Steel Technology Conference","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134264226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Danieli Universal Endless — Outstanding First Results of Production Flexibility","authors":"M. Knigge, A. Pigani","doi":"10.33313/380/108","DOIUrl":"https://doi.org/10.33313/380/108","url":null,"abstract":"","PeriodicalId":226675,"journal":{"name":"AISTech2020 Proceedings of the Iron and Steel Technology Conference","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133388098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Thomas, B. Petrus, D. Stephens, J. Bentsman, L. Chen, M. Milligan, Zhelin Chen, Z. Xu
Mold level fluctuations in continuous casting of steel slabs give rise to slag inclusions, strand surface cracks, and, in severe cases, breakouts. One of the main causes of mold level fluctuations is dynamic bulging, which arises due to periodic squeezing of the strand in the spray cooling zones beneath the mold. This paper presents two models to predict the effect of dynamic bulging on liquid level variations. The first model estimates mold level variations due to dynamic bulging based on two submodels: 1) a computational heat flow model of the continuous casting process that outputs strand surface temperature and shell thickness to an empirical equation to estimate the maximum inner-roll bulging amplitude under steady casting conditions, and 2) an analytical geometric model that calculates the dynamic shape of the bulged shell and the resulting mold level fluctuations, based on the output from the first model and an assumed frozen fraction history. The second model is a simple analytical calculation of the dynamic bulging effect based on the difference between two plant measurements: the mold level sensor data and the stopper rod position, together with a model that predicts the effect of inlet flow variations from the tundish through the SEN into the mold under transient conditions, caused by the measured stopper rod movements, including the effects of erosion. The predictions from these two models are compared to gain new insight into the mold level fluctuations caused by dynamic bulging. At present, this comparison shows quantitative similarities, but also noticeable discrepancy. Steps to improve the accuracy of both models are discussed. INTRODUCTION The quality of steel manufactured by continuous casting depends on controlling many different phenomena. Perhaps the most important factor affecting steel quality is ability to control transient fluctuations of the mold level. These fluctuations lead to severe quality problems, such as surface defects and the entrainment of mold slag that forms the inclusions. Level fluctuations also lead to large, detrimental slag rims, which prevent proper liquid mold slag infiltration. Severe mold level fluctuations also cause deep oscillation marks and increase the incidence of surface cracks [1], [2] and the chance of breakouts [3]. Currently,
{"title":"Modeling of the Dynamic-Bulging-Induced Surface Level Fluctuations in Continuous Casting","authors":"B. Thomas, B. Petrus, D. Stephens, J. Bentsman, L. Chen, M. Milligan, Zhelin Chen, Z. Xu","doi":"10.33313/380/090","DOIUrl":"https://doi.org/10.33313/380/090","url":null,"abstract":"Mold level fluctuations in continuous casting of steel slabs give rise to slag inclusions, strand surface cracks, and, in severe cases, breakouts. One of the main causes of mold level fluctuations is dynamic bulging, which arises due to periodic squeezing of the strand in the spray cooling zones beneath the mold. This paper presents two models to predict the effect of dynamic bulging on liquid level variations. The first model estimates mold level variations due to dynamic bulging based on two submodels: 1) a computational heat flow model of the continuous casting process that outputs strand surface temperature and shell thickness to an empirical equation to estimate the maximum inner-roll bulging amplitude under steady casting conditions, and 2) an analytical geometric model that calculates the dynamic shape of the bulged shell and the resulting mold level fluctuations, based on the output from the first model and an assumed frozen fraction history. The second model is a simple analytical calculation of the dynamic bulging effect based on the difference between two plant measurements: the mold level sensor data and the stopper rod position, together with a model that predicts the effect of inlet flow variations from the tundish through the SEN into the mold under transient conditions, caused by the measured stopper rod movements, including the effects of erosion. The predictions from these two models are compared to gain new insight into the mold level fluctuations caused by dynamic bulging. At present, this comparison shows quantitative similarities, but also noticeable discrepancy. Steps to improve the accuracy of both models are discussed. INTRODUCTION The quality of steel manufactured by continuous casting depends on controlling many different phenomena. Perhaps the most important factor affecting steel quality is ability to control transient fluctuations of the mold level. These fluctuations lead to severe quality problems, such as surface defects and the entrainment of mold slag that forms the inclusions. Level fluctuations also lead to large, detrimental slag rims, which prevent proper liquid mold slag infiltration. Severe mold level fluctuations also cause deep oscillation marks and increase the incidence of surface cracks [1], [2] and the chance of breakouts [3]. Currently,","PeriodicalId":226675,"journal":{"name":"AISTech2020 Proceedings of the Iron and Steel Technology Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129618961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Inspection of Rolled Heavy Plate by 3D Inspection","authors":"G. Gutmann, D. Recker","doi":"10.33313/380/145","DOIUrl":"https://doi.org/10.33313/380/145","url":null,"abstract":"","PeriodicalId":226675,"journal":{"name":"AISTech2020 Proceedings of the Iron and Steel Technology Conference","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133452073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scale formed during slab reheating can be difficult to remove by high-pressure descaling, having a negative impact hot roll surface quality. A large-capacity thermogravimetric apparatus that replicates the combustion atmosphere and temperature in a slab reheat furnace was used to investigate scale formation on 430 stainless steel. Effects of reheating parameters (temperature, time and atmosphere) on oxidation kinetics were investigated. Oxidized samples were characterized by scanning electron microscopy, Raman spectroscopy and x-ray diffraction to document the microstructure and morphology of scale. Mechanisms for the formation of multi-layered oxide structures that complicate oxidation kinetics and scale removal are discussed.
{"title":"Scale Formation on 430 Stainless Steel in a Simulated Slab Combustion Reheat Furnace Atmosphere","authors":"R. O’Malley, S. Lekakh, R. Osei","doi":"10.33313/380/120","DOIUrl":"https://doi.org/10.33313/380/120","url":null,"abstract":"Scale formed during slab reheating can be difficult to remove by high-pressure descaling, having a negative impact hot roll surface quality. A large-capacity thermogravimetric apparatus that replicates the combustion atmosphere and temperature in a slab reheat furnace was used to investigate scale formation on 430 stainless steel. Effects of reheating parameters (temperature, time and atmosphere) on oxidation kinetics were investigated. Oxidized samples were characterized by scanning electron microscopy, Raman spectroscopy and x-ray diffraction to document the microstructure and morphology of scale. Mechanisms for the formation of multi-layered oxide structures that complicate oxidation kinetics and scale removal are discussed.","PeriodicalId":226675,"journal":{"name":"AISTech2020 Proceedings of the Iron and Steel Technology Conference","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130418152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimizing Sinter Chemistry to Counter Alumina Effect","authors":"C. Verma","doi":"10.33313/377/053","DOIUrl":"https://doi.org/10.33313/377/053","url":null,"abstract":"","PeriodicalId":226675,"journal":{"name":"AISTech2020 Proceedings of the Iron and Steel Technology Conference","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128276446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Hydrogen-Based Annealing Technologies for High-Alloyed Steel Strips Open Various Market Segments","authors":"S. Eppensteiner","doi":"10.33313/380/172","DOIUrl":"https://doi.org/10.33313/380/172","url":null,"abstract":"","PeriodicalId":226675,"journal":{"name":"AISTech2020 Proceedings of the Iron and Steel Technology Conference","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122024383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Digital technologies are transforming industry at all levels. Steel has the opportunity to lead all heavy industries as an early adopter of specific digital technologies to improve our sustainability and competitiveness. This column is part of AIST’s strategy to become the epicenter for steel’s digital transformation, by providing a variety of platforms to showcase and disseminate Industry 4.0 knowledge specific for steel manufacturing, from big-picture concepts to specific processes. Machine Learning–Based On-Line Model for Slag Conditioning in Ladle Furnaces at Ternium Mexico
{"title":"Machine Learning–Based On-Line Model for Slag Conditioning in Ladle Furnaces at Ternium Mexico","authors":"J. Lara, N. Sánchez, A. Zambrano","doi":"10.33313/380/206","DOIUrl":"https://doi.org/10.33313/380/206","url":null,"abstract":"Digital technologies are transforming industry at all levels. Steel has the opportunity to lead all heavy industries as an early adopter of specific digital technologies to improve our sustainability and competitiveness. This column is part of AIST’s strategy to become the epicenter for steel’s digital transformation, by providing a variety of platforms to showcase and disseminate Industry 4.0 knowledge specific for steel manufacturing, from big-picture concepts to specific processes. Machine Learning–Based On-Line Model for Slag Conditioning in Ladle Furnaces at Ternium Mexico","PeriodicalId":226675,"journal":{"name":"AISTech2020 Proceedings of the Iron and Steel Technology Conference","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130884007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Sawant, B. Masters, B. Feagan, K. Harmon, L. Zhang
Digital technologies are transforming industry at all levels. Steel has the opportunity to lead all heavy industries as an early adopter of specific digital technologies to improve our sustainability and competitiveness. This column is part of AIST’s strategy to become the epicenter for steel’s digital transformation, by providing a variety of platforms to showcase and disseminate Industry 4.0 knowledge specific for steel manufacturing, from big-picture concepts to specific processes. Classifier Tuning of Automated Surface Inspection System
{"title":"Classifier Tuning of Automated Surface Inspection System","authors":"A. Sawant, B. Masters, B. Feagan, K. Harmon, L. Zhang","doi":"10.33313/380/217","DOIUrl":"https://doi.org/10.33313/380/217","url":null,"abstract":"Digital technologies are transforming industry at all levels. Steel has the opportunity to lead all heavy industries as an early adopter of specific digital technologies to improve our sustainability and competitiveness. This column is part of AIST’s strategy to become the epicenter for steel’s digital transformation, by providing a variety of platforms to showcase and disseminate Industry 4.0 knowledge specific for steel manufacturing, from big-picture concepts to specific processes. Classifier Tuning of Automated Surface Inspection System","PeriodicalId":226675,"journal":{"name":"AISTech2020 Proceedings of the Iron and Steel Technology Conference","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126845789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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