04 Integrated Automation Systems for Steelmaking at COSIPA

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INTEGRATED AUTOMATION SYSTEMS FOR STEELMAKING AT 
COSIPA 1 
 
 
 
Josef Weisz2 
Anton Mayr3 
Peter Juza4 
Barbara Angermayr5 
Günther Straka6 
 
Summary 
From end of 2001 to beginning of 2002 VAI has successfully installed and 
commissioned new facilities for a steel production route including one 160 t LD (BOF) 
converter, one aluminium heating facility and one 2-strand slab caster at COSIPA / 
Brazil. 
An important part of this project was the implementation of a complete automation 
system for process control and process optimization guiding and supervising all steps 
of the production process. 
Production and quality requirements are prepared and provided by the existing 
production planning automation and the new VAI-Q quality assurance system. The 
new process optimization systems feature state-of-the-art metallurgical models and 
technological controls and provide process observation to ensure and report the 
required steel and product quality at the end of each production step. 
The human machine interface presents an up-to-date overview about the actual 
production process and facilitates operator interaction if this is required. 
The commissioning of the new facilities including automation systems was started in 
Nov-2001. The performance guarantee tests commenced in Dec-2001 and Jan-2002. 
 
Keywords: BOF, AHF, continuous casting, process control, automation system 
 
 
1 ABM XXXIII Steelmaking Seminar 2002, from 6th to 8th of May/2002 in Santos - São Paulo State 
2 Project Manager, Ing. Josef Weisz, Voest-Alpine Industrieanlagenbau G.m.b.H.&Co 
3 Project Manager, D.I. Anton Mayr, Voest-Alpine Industrieanlagenbau G.m.b.H.&Co 
4 Automation Manager, Dr. Peter Juza, Voest-Alpine Industrieanlagenbau G.m.b.H.&Co 
5 Automation Manager, D.I. Barbara Angermayr, Voest-Alpine Industrieanlagenbau G.m.b.H.&Co 
6 Product Manager, Dr. Günther Straka, Voest-Alpine Industrieanlagenbau G.m.b.H.&Co 
Introduction 
In December 1999 VOEST-ALPINE Industrieanlagenbau GmbH, a company of VA 
Technology AG, received a contract from COSIPA / Brazil for the delivery of a 
turnkey expansion of the existing No. 2 steelmaking plant. 
The project comprises general modernization of the existing converter steel plant to 
result in a high-capacity LD (BOF) production facility for highest-quality products. 
Steel is produced in three LD (BOF) converters, one of which has been installed as 
part of this project. The converter capacity is 160 t each. An aluminum heating facility 
was installed in addition to the existing ladle furnace while a new two-strand slab 
caster enhances the continuous casting capacity. Slabs of 750-1900 mm width and 
210 mm thickness can be produced on the new caster. 
Due to this plant upgrade the annual steel production capacity has been increased 
from 2.7 Mio tons to 4.5 Mio tons. 
The production on the new facilities was started at following dates: 
Continuous casting machine: November 2001 
Aluminum heating facility: December 2001 
LD (BOF)-converter: January 2002 
The realization and implementation of an integrated automation system for all new 
production units was a major part of the project. 
This paper describes the concepts and implementation of the automation package 
and its contribution to achieve the specified production quality and performance. 
 
Description of the Production Route 
The following figure shows possible production routes at COSIPA. The new 
production units are identified by shaded background. 
 
Figure 1: Plant configuration 
Converters are charged with hot metal and scrap according to their actual availability. 
Heats produced at converter 5 and 6 are mainly treated on the LF whereas heats 
from converter 7 are mainly treated at the AHF station. All steel from the secondary 
metallurgy is cast on the 2-strand slab caster. 
Automation Concept 
Basic Automation and Process Control 
Process control systems on each production unit collect the data and propagate them 
event driven or on a cyclic basis to the process optimization systems. Conventional 
instrumentation, sequential and closed loop controls, as well as dedicated 
technological packages such as sub-lance control on the converter, LEVCON mold 
level control, DYNAFLEX hydraulic oscillator and the width adjustable mold package 
- the latter all on the continuous caster - have been installed. 
Process Optimization and Quality Supervision 
Tracking modules and advanced process models assure optimized production on the 
individual production units. Process set-points are automatically forwarded to the 
process control systems thus assuring that operators can concentrate on product 
quality and production supervision. 
On the CC automation system the quality data from the entire steel plant are 
collected and assigned to slabs and slab segments for quality evaluation and 
documentation purposes in the VAI-Q Slab Quality Assurance system. 
Human Machine Interface (HMI) 
A common HMI philosophy has been implemented providing similar ‘Look and Feel’ 
for the new process control and process optimization systems. 
 
Figure 2: Automation concept 
An example display from the CC HMI system is shown below. 
 
 
Production Planning 
The existing production planning and plant coordination (PPC) system for flexible and 
just-in-time production was adapted by COSIPA software experts to meet the 
requirements of the new process optimization systems. COSIPA chose an approach 
that production and quality information is collected from and re-distributed to the 
process optimization system by the PPC system. 
 
Process Optimization Systems 
The installed automation systems form an exact image of the technological 
requirements of the plant. This refers especially to the process models, which contain 
the underlying metallurgical know-how, while the planning, coordination and control 
functions, i.e. the core functionality of the process optimization systems, assure plan 
and data handling, process tracking and set-point generation. The process models 
rely on the information which is provided by the process optimization core functions. 
 
Figure 3: Main window of the CC process optimization human machine interface 
LD (BOF) Models and Technological Controls 
According to the production steps on the LD (BOF) converter a sequence of tailored 
mathematical models is 
applied to optimize the 
steel bath analysis, 
tapping temperature, 
carbon content and the 
throughput on the 
converter. Figure 4 
shows the sequence of 
models for a single 
blowing process. 
The following chapters 
describe the LD (BOF) 
process models applied 
in the different 
production phases. 
Heat Preparation 
The heat preparation phase is accompanied by the Charge Calculation, which 
provides the information for required raw material amounts and oxygen volume to get 
the aim tap steel weight, the required blowing end temperature and steel analysis. 
 
While the First Charge Calculation calculates the scrap and hot metal weights 
considering the technological presets for scrap and hot metal mixture, the Second 
Charge Calculation calculates the required converter additions and oxygen volume 
based on the actual weights of scrap as well as hot metal and the hot metal 
temperature. 
Based on the charged hot metal weight the Bath Level Model determines the 
current steel bath height and also the absolute position of the bath level, which varies 
according to the wear of the converter lining. 
 
Main Blowing Phase 
The main blowing phase starts with oxygen blowing. It is finished after the prescribed 
and later dynamically adjusted oxygen volume has been applied. 
During this period the results of the second charge calculation are sent to the basic 
automation system for execution. Whilethe required oxygen amount is a result of the 
second charge calculation, the required oxygen flow, lance height and blowing 
duration of several blowing steps are taken from the blowing scheme. This scheme is 
a predefined table of blowing steps which has been prepared by the metallurgist for 
each steel grade. The bottom-stirring scheme is handled in the same way. 
During the main blowing phase a sub-lance measurement yielding carbon content 
and steel bath temperature is performed to allow Dynamic Process Control. The 
timing of the sub-lance measurement is determined by the second charge calculation 
model. 
 
Figure 4: Process model cycle 
Figure 5 shows the improvements of predicted carbon content and steel bath 
temperature in case dynamic process control is applied. If only a static model would 
be used, any smaller deviation in the input data increases the variation of steel 
temperature and carbon concentration results as indicated in the drawing. 
 
The inblow model 
calculates the required 
oxygen and/or cooling or 
heating agent depending 
on the current deviation of 
temperature and carbon 
from target values. 
Applying the Inblow 
Calculation after the sub-
lance measurement allows 
a synchronization of the 
model calculation with the 
steel bath condition at a 
process stage close to the 
estimated blowing end. 
Subsequent deviations will 
be limited to smaller values. 
Correction and Alloying Phase 
If after the main blowing phase the temperature and the analysis of liquid steel are 
within the specified limits, the heat is ready for tapping. Depending on the steel grade 
it is possible to use the inblow sample analysis as basis for a decision whether any 
further treatments are necessary. If this is not sufficient an extra sample is taken. 
The operator can decide to start the Correction Model to calculate correction 
treatment measures. 
 
The Alloying Calculation is started when the steel analysis after blowing end is 
available. The required quantities of alloying agents and the final steel weight are 
determined taking into account the analysis of the alloying agents and the agent 
specific losses. 
The models are based on physical-chemical reactions. In practice though, there will 
be deviations between calculated and actual values. The compensation of short-term 
trends due to unknown influences is the task of the Feedback Calculation. This 
model recalculates each heat and then determines the parameters for the adaptation 
of the process models by comparing the actual and the target values. For 
subsequent heats the calculations are based on the adapted parameters. 
 
Figure 5: BOF dynamic process control 
AHF Models 
In order to control the metallurgical and thermodynamic state of the heat during the 
secondary metallurgical treatment a set of mathematical process models is applied. 
The actual condition of steel bath and slag are continuously determined. Setpoint 
calculations are performed to control the required addition materials, as shown in 
Figure 6. 
The model calcu-
lations are based on 
the thermodynamic 
and kinetic relation-
ships of the secon-
dary metallurgical 
reactions. 
Furthermore the 
balance equations 
between the compo-
nents of the metal- 
and slag-phase are 
considered. 
The particular process 
models and their 
application in the AHF 
process optimization 
are described in the 
following. 
C
D of the steel-bath and the 
t
 
T f the slag and steel bath 
a in the slag, taking into 
a on. 
T e actual process state of 
t any time for the set-point 
m
T f the heat and the actual 
t based on the previously 
c . 
M
A
p
a
T
s
 
Figure 6: AHF process model overview 
yclic Model 
uring the whole AHF treatment the metallurgical condition 
opslag are determined continuously. 
he Cyclic Metallurgical Model calculates the variation o
nalysis due to the reduction process of the oxide phases
ccount the bottom stirring flowrate and the treatment durati
his ensures that the operator is always informed about th
he heat and the current steel bath condition is available at 
odels. 
he Cyclic Thermal Model calculates the energy balance o
emperature of the steel bath during the whole treatment, 
alculated thermal status and by considering process events
etallurgical Set-point Models 
ccording to the different treatment steps in the AHF station the metallurgical set-
oint models are supplied in order to produce a heat with the target steel analysis 
nd temperature. 
he AHF treatment comprises the process steps alloying, de-oxidation, de-
ulfurization, slag formation, inclusion shape control, cooling by addition of scrap as 
well as heating with aluminum. Before materials are charged, the corresponding 
model is started to determine the required material types and weights. This 
calculation is based on the actual steel and slag analysis and considers the analyses 
and availability of raw materials as well as instructions defined by the production 
practice. 
 
Event Triggered Models 
After important process events, the corresponding models are started, in order to 
determine the metallurgical and thermal condition of the steel bath and topslag. 
At treatment start, after addition of materials or when aluminum heating is finished, 
the temperature and energy content as well as the analysis of steel and slag are 
calculated. In case of treatment start this is based on available heat information from 
the previous plant (BOF or LF). 
After receipt of a sample analysis or a temperature measurement the calculated steel 
analysis respectively bath energy and temperature are adapted corresponding to the 
received values. 
 
CC Process Models and Technological Packages 
A large variety of state-of-the-art process models and technological packages has 
been installed on the 2 strand slab casting machine: 
 
VAI's top-of-the-line secondary cooling model DYNACS® is used for optimum 
secondary cooling results. DYNACS® keeps track of the thermal state of the steel 
inside the entire strand by cyclically solving the thermodynamic differential equations 
and utilizing actual process data such as tundish temperature, steel analysis, casting 
speed and actual water flows. DYNACS® applies cooling strategies, that aim and 
achieve constant surface temperature profiles for the steel in the strand containment 
within small tolerances. These results are within certain limits independent of the 
casting speed variations during the production process. 
 
The VAI-Q Slab-Quality Assurance System guides the operators by automatically 
displaying the production practices for each heat and immediately alarming the 
personnel in case of violations to the prescribed limits. The practices are derived 
from the metallurgical knowledge database, maintained by the plant metallurgist. The 
VAI-Q Slab-Quality Production subsystem collects the quality-relevant data for the 
entire steel plant and assigns the collected information to 0,5 meter slab segments. A 
comparison of prescriptions and actual data forms the basis of the slab quality rating. 
In case of deviations the operators are automatically advised to inspect the 
respective slabs. 
 
Cut Length Optimization increases overall yield by allocating the planned slab 
lengths in such a way that the number of prime-length slabs is maximized and overall 
scrap is minimized. COSIPA specific caster and rolling mill parameters are naturally 
taken into account. 
 
The DYNAFLEX hydraulic oscillator is controlled by a dedicated technological 
package allowing a remote adjustment of its oscillation parameters in accordance 
with the requirements of each steel grade. Adjustable parameters include negative 
and positive strip, non-sinusoidal factor as well as stroke and frequency behavior. 
 
Mold width adjustment providesfast and smooth width adjustments guided by an 
automation package that contains an integrated expert system assuring reliable 
operation even in critical situations. 
 
The MoldEXPERT 
system collects tem-
perature data from 
the mold and 
hydraulic pressure 
data from the 
DYNAFLEX oscil-
lator to determine 
the actual mold 
condition concerning 
temperature profile, 
mold friction and 
heat removal. The 
output information of 
the MoldEXPERT is 
used for breakout 
prediction as 
operator guidance. 
The automatically 
saved data also 
serves as feedback 
for the metallurgist on quality-influencing parameters such as mold powder behavior, 
immersion depth of the submerged entry nozzle, mold taper or applied oscillation 
practice. 
Figure 7 shows the main screen of the MoldEXPERT system providing information of 
the mold’s thermal and friction condition and some history thereof. 
 
The most recent development for the CC process optimization system is the 
‘Intermix Model’. 
Each time a new heat is opened during a casting sequence the steel of the old and 
the new heat mix in the tundish and the upper part of the steel in the strands. The 
applied model calculates the intermix analysis and compares the output information 
to the limits of the most recent and new heats. In case either of both analysis 
specifications is met the steel in concern may be used for achieving the production 
orders of the previous or the actual heat. In case of incompatibility with both specified 
steel grades intermix steel segments are identified and treated separately. 
 
 
Figure 7: MoldEXPERT thermal and friction information 
Conclusion 
VAI automation packages for one LD (BOF) converter, an aluminum heating facility 
and a two-strand caster have been embedded into the existing automation 
environment containing COSIPA’s production planning system, which has been 
extended due to project requirements. The integrated automation system matches 
today’s market demands on product quality, productivity and production costs by 
incorporating latest automation technology combined with comprehensive know-how 
of the steelmaking process. Advanced process models and technological packages 
are the core components of the automation system. 
 
The LD (BOF) first and second charge calculation as well as dynamic process control 
using the inblow calculation, yield smaller deviations from the aim temperature and 
the aim carbon content of the steel bath. The correction model and the alloying 
calculation are stabilizing the required steel analysis additionally. 
At the AHF metallurgical and thermal models are used to assist the heat treatment. 
The continuous casting process is under the guidance of tailored functions like cut 
length optimization, DYNACS secondary cooling model, VAI-Q Slab Quality 
Assurance and the MoldEXPERT package to name just a few. 
The VAI-Q Slab Quality Assurance System is the basis for permanent product quality 
improvement and facilitates extensive quality documentation. 
 
The VAI automation solution assists COSIPA’s efforts for 
• standardized operation 
• flexible and just-in-time production 
• higher production rate (e.g. shorter tap-to-tap time) 
• increase of refractory lifetime 
• reduction of energy and material consumption 
• increase of product yield 
• comprehensive quality certification 
 
	Summary
	Introduction
	Description of the Production Route
	Automation Concept
	Basic Automation and Process Control
	Process Optimization and Quality Supervision
	Human Machine Interface (HMI)
	Production Planning
	Process Optimization Systems
	LD (BOF) Models and Technological Controls
	Heat Preparation
	Main Blowing Phase
	Correction and Alloying Phase
	AHF Models
	Cyclic Model
	Metallurgical Set-point Models
	Event Triggered Models
	CC Process Models and Technological Packages
	Conclusion