Modeling of the cooling process on the runout table of a hot strip mill - A parallel approach

This paper deals with the development of a new model for the cooling process on the runout table of hot strip mills, The suitability of different numerical methods for the solution of the proposed model equation from the point of view of accuracy and computation time are studied, Parallel solutions for the model equation are proposed.

An investigation of worn work roll materials used in the finishing stands of the hot strip mill for steel rolling

The surface failure characteristics of different work roll materials, i.e. High Speed Steel, High Chromium Iron and Indefinite Chill Iron, used in the finishing stands of a hot strip mill have been investigated using stereo microscopy, 3D optical profilometry, scanning electron microscopy and energy dispersive X-ray spectroscopy. The results show that the surface failure mechanisms of work rolls for hot rolling are very complex, involving plastic deformation, abrasive wear, adhesive wear, mechanical and thermal induced cracking, material transfer and oxidation. Despite the differences in chemical composition and microstructure, the tribological response of the different work roll materials was found to be strongly dependent on the material microstructure and especially the presence and distribution of microstructural constituents, such as the different carbide phases and graphite (in the case of Indefinite Chill Iron). Cracking and chipping of the work roll surfaces, both having a negative impact on work roll wear, are strongly influenced by the presence of carbides, carbide networks and graphite in the work roll surface. Consequently, the amount of carbide forming elements as well as the manufacturing process must be controlled in order to obtain an optimised microstructure and a predictable wear rate.

Modeling precipitation and its effect on recrystallization during hot strip rolling of niobium steels

Using a physically based model, the microstructural evolution of Nb microalloyed steels during rolling in SSAB Tunnplåt’s hot strip mill was modeled. The model describes the evolution of dislocation density, the creation and diffusion of vacancies, dynamic and static recovery through climb and glide, subgrain formation and growth, dynamic and static recrystallization and grain growth. Also, the model describes the dissolution and precipitation of particles. The impeding effect on grain growth and recrystallization due to solute drag and particles is accounted for. During hot strip rolling of Nb steels, Nb in solid solution retards recrystallization due to solute drag and at lower temperatures strain-induced precipitation of Nb(C,N) may occur which effectively retard recrystallization. The flow stress behavior during hot rolling was calculated where the mean flow stress values were calculated using both the model and measured mill data. The model showed that solute drag has an essential effect on recrystallization during hot rolling of Nb steels.

Fusing data-mining and knowledge elicitation for the supervisory control of an aluminium plate mill

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process.

Design, implementation and testing of an intelligent knowledge-based system for the supervisory control of a hot rolling mill

This paper describes the design, implementation and testing of an intelligent knowledge-based supervisory control (IKBSC) system for a hot rolling mill process. A novel architecture is used to integrate an expert system with an existing supervisory control system and a new optimization methodology for scheduling the soaking pits in which the material is heated prior to rolling. The resulting IKBSC system was applied to an aluminium hot rolling mill process to improve the shape quality of low-gauge plate and to optimise the use of the soaking pits to reduce energy consumption. The results from the trials demonstrate the advantages to be gained from the IKBSC system that integrates knowledge contained within data, plant and human resources with existing model-based systems. (c) 2005 Elsevier Ltd. All rights reserved.

A Cost Model for the Effect of Setup Time Reduction in Stainless Steel Strip Production

Setup time reduction facilitate the flexibility needed for just-in-time production. An integrated steel mill with meltshop, continuous caster and hot rolling mill is often operated as decoupled processes. Setup time reduction provides the flexibility needed to reduce buffering, shorten lead times and create an integrated process flow. The interdependency of setup times, process flexibility and integration were analysed through system dynamics simulation. The results showed significant reductions of energy consumption and tied capital. It was concluded that setup time reduction in the hot strip mill can aid process integration and hence improve production economy while reducing environmental impact.

Knowledge-elicitation and data-mining: fusing human and industrial plant information

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process. (C) 2005 Elsevier Ltd. All rights reserved.

Tribology in Metal Working

This thesis focuses on the tribological performance of tool surfaces in two steel working operations, namely wire drawing and hot rolling. In all forming operations dimensions and surface finish of the products are of utmost importance. Forming basically includes three parts – forming conditions excluded – that may be changed; work material, tool and (possibly) lubricant. In the interface between work material and tool, the conditions are very aggressive with – generally or locally – high temperatures and pressures. The surfaces will be worn in various ways and this will change the conditions in the process. Consequently, the surface finish as well as the dimensions of the formed product may change and in the end, the product will not fulfil the requirements of the customer. Therefore, research and development in regard to wear, and consequently tribology, of the forming tools is of great interest. The investigations of wire drawing dies focus on coating adhesion/cohesion, surface characteristics and material transfer onto the coated steel both in laboratory scale as well as in the wire drawing process. Results show that it in wire drawing is possible to enhance the tribological performance of drawing dies by using a lubricant together with a steel substrate coated by a polished, dual-layer coating containing both hard and friction-lowering layers. The investigations of hot rolling work rolls focus on microstructure and hardness as well as cracking- and surface characteristics in both laboratory scale and in the hot strip mill. Results show that an ideal hot work roll material should be made up of a matrix with high hardness and a large amount of complex, hard carbides evenly distributed in the microstructure. The surface failure mechanisms of work rolls are very complex involving plastic deformation, abrasive wear, adhesive wear, mechanical and thermal induced cracking, material transfer and oxidation. This knowledge may be used to develop new tools with higher wear resistance giving better performance, lower costs and lower environmental impact.

Caracterização de materiais utilizados na fabricação de cilindros de laminação submetidos ao desgaste abrasivo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Advanced predictive quality control strategy involving different facilities

There are many industries that use highly technological solutions to improve quality in all of their products. The steel industry is one example. Several automatic surface-inspection systems are used in the steel industry to identify various types of defects and to help operators decide whether to accept, reroute, or downgrade the material, subject to the assessment process. This paper focuses on promoting a strategy that considers all defects in an integrated fashion. It does this by managing the uncertainty about the exact position of a defect due to different process conditions by means of Gaussian additive influence functions. The relevance of the approach is in making possible consistency and reliability between surface inspection systems. The results obtained are an increase in confidence in the automatic inspection system and an ability to introduce improved prediction and advanced routing models. The prediction is provided to technical operators to help them in their decision-making process. It shows the increase in improvement gained by reducing the 40 % of coils that are downgraded at the hot strip mill because of specific defects. In addition, this technology facilitates an increase of 50 % in the accuracy of the estimate of defect survival after the cleaning facility in comparison to the former approach. The proposed technology is implemented by means of software-based, multi-agent solutions. It makes possible the independent treatment of information, presentation, quality analysis, and other relevant functions.

Improving the prediction of the roll separating force in a hot steel finishing mill

This paper focuses on the development of a hybrid phenomenological/inductive model to improve the current physical setup force model on a five stand industrial hot strip finishing mill. We approached the problem from two directions. In the first approach, the starting point was the output of the current setup force model. A feedforward multilayer perceptron (MLP) model was then used to estimate the true roll separating force using some other available variables as additional inputs to the model.

It was found that it is possible to significantly improve the estimation of a roll separating force from 5.3% error on average with the current setup model to 2.5% error on average with the hybrid model. The corresponding improvements for the first coils are from 7.5% with the current model to 3.8% with the hybrid model. This was achieved by inclusion, in addition to each stand's force from the current model, the contributions from setup forces from the other stands, as well as the contributions from a limited set of additional variables such as: a) aim width; b) setup thickness; c) setup temperature; and d) measured force from the previous coil.

In the second approach, we investigated the correlation between the large errors in the current model and input parameters of the model. The data set was split into two subsets, one representing the "normal" level of error between the current model and the measured force value, while the other set contained the coils with a "large" level of error. Additional set of data with changes in each coil's inputs from the previous coil's inputs was created to investigate the dependency on the previous coil.

The data sets were then analyzed using a C4.5 decision tree. The main findings were that the level of the speed vernier variable is highly correlated with the large errors in the current setup model. Specifically, a high positive speed vernier value often correlated to a large error. Secondly, it has been found that large changes to the model flow stress values between coils are correlated frequently with larger errors in the current setup force model.

Calucaltion of waste heat from hot rolled steel coils at SSAB and its recovery

Hot rolling process is heat input process. The heat energy in hot rolled steel coils can be utilized. At SSAB Strip Product Borlänge when the hot rolled steel coils came out of the hot rolling mill they are at the temperature range of 500°C to 800°C. Heat energy contained by the one hot rolled steel coil is about 1981Kwh whereas the total heat energy for the year 2008 is 230 GWh/year.The potential of heat is too much but the heat dissipation rate is too slow. Different factors on which heat dissipation rate depends are discussed.Three suggestions are proposed to collect the waste heat from hot rolled steel coils.The 2nd proposal in which water basin is suggested would help not only to collect the waste heat but to decrease in the cooling time.

Formation of ultra-fine ferrite in hot rolled strip: potential mechanisms for grain refinement

A novel single-pass hot strip rolling process has been developed in which ultra-fine (<2 μm) ferrite grains form at the surface of hot rolled strip in two low carbon steels with average austenite grain sizes above 200 μm. Two experiments were performed on strip that had been re-heated to 1250°C for 300 s and air-cooled to the rolling temperatures. The first involved hot rolling a sample of 0.09 wt.%C–1.68Mn–0.22Si–0.27Mo steel (steel A) at 800°C, which was just above the Ar3 of this sample, while the second involved hot rolling a sample of 0.11C–1.68Mn–0.22Si steel (steel B) at 675°C, which is just below the Ar3 temperature of the sample. After air cooling, the surface regions of strip of both steel A and B consisted of ultra-fine ferrite grains which had formed within the large austenite grains, while the central regions consisted of a bainitic microstructure. In the case of steel B, a network of allotriomorphic ferrite delineated the prior-austenite grain boundaries throughout the strip cross-section. Based on results from optical microscopy and scanning/transmission electron microscopy, as well as bulk X-ray texture analysis and microtextural analysis using Electron Back-Scattered Diffraction (EBSD), it is shown that the ultra-fine ferrite most likely forms by a process of rapid intragranular nucleation during, or immediately after, deformation. This process of inducing intragranular nucleation of ferrite by deformation is referred to as strain-induced transformation.

Static and metadynamic recrystallization of interstitial free steels during hot deformation

A rapid method was used to identify kinetics of the recrystallization for two IF (Interstitial Free) steels which have different phosphorous and boron contents. The static and metadynamic softening behaviour of the materials for a range of strain rates and temperatures were quantified. The critical strain for initiation of strain independent softening was estimated for the IF steels in respect to the time for 50 percent softening after deformation. The results showed that the strain for the initiation of strain independent softening (often referred to as metadynamic recrystallization) varies with the Zener Hollomon parameter. Classic static recrystallization was observed at strains below the strain independent softening for all processing conditions and the strain rate had a strong effect on the time for strain independent softening. Results also revealed that static and metadynamic recrystallization was delayed owing to the phosphorous and boron alloying elements. Hence, the large strain at above no-recrystallization temperature may be required for the early stage of Finishing Stands Unit (FSU) in hot strip rolling mills to initiate austenite grain refinement of phosphorous and boron added IF steels.