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Computer Simulation in CAD-CAM-CAPP Systems for Steelmaking
Copyright © IFAC Automation in Mining. Mineral and Metal Processing. Sun City. South Africa. 1995
COMPUTER SIMULATION IN CAD-CAM-CAPP SYSTEMS FOR STEELMAKING
S.A.VIasov, A.D.Belov Institute of Control Sciences. Russian Academy of Sciences
Abstract: Each shop, department or industrial asembly presents a roundup system so that operation routine changed at single element requries thorough analysis and synthesis of the effects bound to influence the pilot unit, product quality and efficiency of control. The above interrelation can be traced with the help computer simulation. This paper is discussed information and software support of simulation systems for problems of CAD-CAM-CAPP for steelmaking. Keywords: Computer simulation, steel industry, flexible automation, expert systems.
Analysis of the current state of metallurgy in Russia and other countries reveals that the following tasks have to be fulfilled for its further evolution.
The above CTCs are studied by solving the related problems of choosing equipment (type, number, allocation), processes (type and parameters of the processes and material flows) and rules to organize the production.
-broader range of products of improved quality; -more flexible organization of production at all levels; -saving all types of resources used (power, heat, raw materials, etc.); -maintaining the ecological equilibrium around the production zone.
These problems are solved using the CAD-CAM-CAPP systems. The multi-purpose simulation models developed at the Institute of Control Sciences serve as a basis for the algorithmic and software support of such systems.
Comprehensive solution of the above problems starts at an early stage of design and depends largely on the level of computerization of the process and technological complex control. The state-of-the-art metallurgical production is mo~ly based on computerised technological complexes (CTC) which involve adjacent workshops and their control subsystems.
The need for computer simulation in these systems is determined by the effect that the range of products has on the efficiency of a group of interrelated units of varying capacity, also by the effer.t that various control algorithms and operation modes as well as random noise or downtime may have. Moreover, a number of metallurgical plants are unique in terms of the equipment involved and the respective (allocation and planning) solutions, consequently, to make an optimal decision one has not to rely only on standard materials and the analysis of deterministic
Examples of such CTCs can be provided by complexes like: "Steel Melting-Casting" , "heating furnaces-hot rolling mill", or "SteelRolling" complexes with various equipment set-ups and technological flows .
165
systems are refevred to as Expert Systems of Computer Simulation (ESCS). Development of such systems aims at incorporating into the computer simulation software as much of the required knowledge and expertise as possible. These systems (ESCS) enable engineers, researchers, designers and businessmen to perform simulation experiments adequately without being specially trained in many fields of knowledge (programming languages, experiment planning,statistical analysis,etc.).
indicators, but much rather, allude to computer simulation instead. A base version of the CTC for which the multi-purpose simulation model was developed is shown in Fig.l . As you can see from the Diagram in Fig. I , the base version has all the main has all the main components of the state-of-the-art "Steel-Rollng" complexes. Accordingly, the software components have been developed to support the required "usersimulation system" interaction procedures (see Fig.2).
The Institute of Control Sciences of the Russian Academy of Sciences has developed the Concepts for computer simulation with the components which can be refevred to the ESCS. Further evolution of the traditional programming languages for simulation (GPSS , SIMULA) allows using an object-oriented approach to the development of the software for multi-purpose simulation systems including those which are combined with expert systems.
They are listed below: -procedures for introducing a database, these procedures are common for all versions; -procedures for generating versions of CTC using general and specific data; -procedures for simulation experiments with the generated CTC version; -procedures for presenting and analyzing the results of the results of the simulation experiments; -procedures for maintaining the base of the results of the CTC version computer simulation; -procedures for synthesis of the results simulation experiments in accordance with the goal of the analysis.
Modern versions of the algorithmic and software support of ESCS for CTC in metallurgy are developed using the Windows programming environment and object-oriented software versions of the universal languages C++, Pascal. The above software tools facilitate the application of the block modelling concepts and of the so-called "model designer" [Vlasov and colleaques (1981) and Su-Shi-Quan and Zhao Lin-Liang (1992)].
The problems to be solved and their interaction are shown in Fig.3. The experience of using a software package of the simulation system has shown that it can be used both, in design of "Steel-Rolling" CTC with various equipment set-ups and technological flows , and in current schedule planning, developing contact schedules to support the interaction of the CTC components so that the production capacities can be used more efficiently.
In the context of the CTC analysis and synthesis the "model designer" should have as part of its structure the advanced tools for describing technological equipment, material flows and control algorithms (CA) which are built around the procedures of design and changing information in the respective databases (DB). The "model designer" in its structure should also have the knowledge base (KB) containing the modelling rules, and a mechanism for modelling in accordance with the specifications supplied by the user.
The main results obtained with the sumulation software package using specialized programming languages, GPSS-PC and FORTRAN, are described in e.g.[Vlasov and coleaques (1992)].
With the equipment DB the designer of the CTC versions can implement the technique of the "nested" models [Vlasov and colleaques (1981)].
In the recent decade significant results in computer simulation are associated with artificial intelligence methodology and, specifically, its applied field , knowledge-based systems.
This permits the study of the model of one CTC with different degree of detail. By choosing simpler models one can study more versions (due to the shorter modelling time). At a higher degree of detail one can give a deeper insight into more promising alternatives.
Simulation systems based on knowledge are a result of combining two technologies: expert systems (ES) and computer simulation (CS) [Merkuryeva and Merkuryev (1991 )]. These
166
Moreover, the class descriptions can be specified, by making them simpler, ignoring the attributes, states, or subsystems which influence, but weakly, the results, or vica versa, by making them more comprehensive. The effect of the object class properties on the simulation results should be subjected to expert assessment.
CA which would prevent getting into a situation preceding the conflict. In this case the rules are eloborated in a dialoque. The expert is given a description of the assense of the conflict. The expert has to either chose a decision from already existing ones, or find a new one. This approach denotesa change in the control paradigm from "rigid" approach when all CA are described to a "soft" approach assuming incomplete set of CA, inspecified algorithms and tools for generating CA by the user-not a professional programmer. To implement this capability it is required to compliment the traditional programming languages with the systems built around the "soft" control concept which support CA DB and use the CA in developing the control components for the simulation system.
The equipment DB can be implemented through the objects the network presentation of studied by the methods of object-oriented programming. In design of the CA DB one of the key issues is the generation of a mechanism formalization of model situations. To this end, Le. for discribing the CA, use can be made of the procedure presentation mechanism, for example, production systems.
When developing CA with the prehistory accounted for the expert's work is much helped by the capability of returning the model to a state preceding the conflict.
CA KB assumed to be evolving, originally may contain simple rules like (these is at least one non engaged system available in the next of systems in the process class sequence)~(perform processing of the material flow unit in a system with the lower index). As practice shows, such simple and readily formalizable rules or their sets are used rather often. For instance, in modelling the interaction of various systems in the CTC of steel melting shops, these rules implemented by logic algorithms were used for simulation of control inputs [Vlasov and colleaques (1981 »).
To generate CA related with the model, it is possible to use a method based on human operator observations. We know from practice , also for CTC in metallurgy [Vlasov and colleaques (1981), (1992»),that this method is much labourconsuming. The efficiency (or production capacity [Vlasov and colleaques (1992»)) is not the only indicator of the system performance, there are a number of other critical problems which have to be solved at different stages of the CTC life cycle (e.g. in design, strategic planing and current planning). The artificial intelligence concepts and software tools have demonstrated their potential to resolve the above issues. The approach is illustrated in e.g. [Su-Shi-Quan and Zhao Lin-Liang (1992)] .
Special interest in terms of obtaining efficient control systems present those cases when none of the regular CA in the KB associated with the given simulation model resolves the situation, when the control inputs are inefficient. We will refer to such situations as conflict ones. They can be resolved by an expert designer upon the respective request by the model. If this is the case, the rule for resolving a conflict situation as offered by the expert will be stored in the CA KB thus supplementing it.
When embarking on this approach, one has to find ways to use such creative potentials of man, like eurlstlcs, imaginative thinking and sensations. It is proposed, specifically to use in design special command processors which automatically generate procedures for developing complex systems of the CTC type based on the knowledge of the object models and methods of developing them .
Ideally, the model of CTC controlling subsystems which interacts with CA DB and CK KB should not have conflict situations. There are two possible approaches to the using the resolution of conflict situations: conflict history or not using it.
•
In the latter case a decision is made by analyzing only the current state and situations already planned by that time. Technically, this is the simplest approach.
In this case, however, it is preferential to resolve the above problems not by developing specialized equipment, but rather, by developing algorithmic and software tools which expand the capabilities adding intelligence to the standard computing tools. Here, we have to re-emphasize again that it is
If, however, in the computer simulation of CTC we want to consider the reasons for getting into a conflict situation, then we have to develop
167
reasonable and advisablle machine systems.
to
develop
man-
developing systems with the above properties. Software for these investigations may be demonstrated on the technical exibition MMM95 Symposyum.
It has been stated earlier that knowledge used by man in design or planning is difficult to automate completely.
REFERENCES
The best solution is seen in the following concept of creating intelectual decision making support systems (IDMSS).
Vlasov S.A , Belov AD. , Computer Simulation Applied to CAD of Computerized Technological Complexes in Metallurgy. Preprints of 7-th IFAC Sympo~um on Automation in Mining , Mineral and Metal Processing.Beijing, China, 1992. Merkuryeva G.V., Merkushev Yu.L. Expert Systems of computer simulation. Tekhnicheskaya Kibernetika. 1991. N3. Vlasov S.A., Maly S.A , Tomashevskaya V.S. , Tropkina A.1. Integrated design of metallurgical complexes. M: Metallurgiya Publishers, 1981. Su Shi-Quan, Zhao Lin-Liang. Artificial Intelligence Techniques In CIPS (CIMS) for Mining Mineral and Metal Processing: A Review and Future Direction. Preprints of 7th IFAC Symposium on Automation in Mining, Mineral and Metal Processing.Beijing.China, 1992.
In this case the experience of creating simulation systems can be utilized with the utmost efficiency, - since they in essence are also systems for support of decision making during the simulation experiment. The IDMSS for production planning should have the following capabilities: support of knowledge base (KB); support and check-up of the planned decisiones library; hight-quality logical analysis of the decisions made; review of the plan. The structure of information and software support of simulation systems developed at the Institute of Control Sciences for CTC of continious-discrete types of productions r - - - - - - - - - - - - - - - - .. - - - - - - .. - - - - - - ...
ere for Steel-Making Plant -------~----------------------
: - - - - - - - - - - - - - - - - -1- - - - - - - - - - - - - ~
Fig.l
168
Initial DATABASE for used to simulate CTC versions
Procedure for developing a
~--------------------------~ CTC Tecnological diagrams
~ CTC version and generating a data file for it
1
Equipment set-ups CTC versions Parametrs of input and output material flows CTC equipment parametrs Parametrs of material processing operations Parametrs of auxilary operations (maintenance of equipment, transportation, etc.) Control algorithm parametr values Description of initial states of CTC components
~
SIMULATION MODEL
r+~------------~ Modeling of: CTC equipment functioning Material flows Datajlows Control algorithms
,
Procedures for maintaining the original DATABASEfor ....---I~ software used to simulate CTC versions
SOFTWARE', for 'system monitor
Procedures for ANALYSIS and SYNTHFSIS ofCTC modeling versions
USER
,
1 DATABASE OF RESULTS OF CTC VERSIONS MODELING AND SYNTHESIS Calculated annual efficiency: of individual systems, gruops of equipment , CTC as whole; Parametrs of the main technological operations; Parametrs of auxilary operations; Characteristics of reaching the planned targets of production; Data for analyzing the efficiency of control algorithms; Schedules for functioning equipment units in the simulated versions; Schedules for processing material flow units in the simulated versions; Fig.2
169
Long termed target for CTC "Sheet-Rolling Mill"
Capacity of the CTC "Sheet Rolling Mill"
I
t 1
1
+
-.L
I
t
+
I· 1
I
Versions of the work schedules Section Mill 1 1
1
1
1 1
1 1 1
A
-----------1 +
+
1
Versions of short term functioning the CTC systems Rolling Plant 1 1
1
1 I
I
I
'"
t
Versions of the schedules for functioning CTC Casting
1 1
1 1 1 1
I
. 1
. ~~ysis &'SynteSi$
of Planes ' 'os.' '"manifactory'i' 'of SteelMaldng Plant
Versions of short term functioning the CTC systems Steel Making Plant
+, Anal~~ .~$~tesis 'fUriCtiQrun~:, of'~JTCSteelMaking Plant
ere
t
I
+
Versions of schedules for functioning the CTC systems Steel Making Plant
Fig.3
'"
I
COMPUTER SIMULATION IN CAD-CAM-CAPP SYSTEMS FOR STEELMAKING
S.A.VIasov, A.D.Belov Institute of Control Sciences. Russian Academy of Sciences
Abstract: Each shop, department or industrial asembly presents a roundup system so that operation routine changed at single element requries thorough analysis and synthesis of the effects bound to influence the pilot unit, product quality and efficiency of control. The above interrelation can be traced with the help computer simulation. This paper is discussed information and software support of simulation systems for problems of CAD-CAM-CAPP for steelmaking. Keywords: Computer simulation, steel industry, flexible automation, expert systems.
Analysis of the current state of metallurgy in Russia and other countries reveals that the following tasks have to be fulfilled for its further evolution.
The above CTCs are studied by solving the related problems of choosing equipment (type, number, allocation), processes (type and parameters of the processes and material flows) and rules to organize the production.
-broader range of products of improved quality; -more flexible organization of production at all levels; -saving all types of resources used (power, heat, raw materials, etc.); -maintaining the ecological equilibrium around the production zone.
These problems are solved using the CAD-CAM-CAPP systems. The multi-purpose simulation models developed at the Institute of Control Sciences serve as a basis for the algorithmic and software support of such systems.
Comprehensive solution of the above problems starts at an early stage of design and depends largely on the level of computerization of the process and technological complex control. The state-of-the-art metallurgical production is mo~ly based on computerised technological complexes (CTC) which involve adjacent workshops and their control subsystems.
The need for computer simulation in these systems is determined by the effect that the range of products has on the efficiency of a group of interrelated units of varying capacity, also by the effer.t that various control algorithms and operation modes as well as random noise or downtime may have. Moreover, a number of metallurgical plants are unique in terms of the equipment involved and the respective (allocation and planning) solutions, consequently, to make an optimal decision one has not to rely only on standard materials and the analysis of deterministic
Examples of such CTCs can be provided by complexes like: "Steel Melting-Casting" , "heating furnaces-hot rolling mill", or "SteelRolling" complexes with various equipment set-ups and technological flows .
165
systems are refevred to as Expert Systems of Computer Simulation (ESCS). Development of such systems aims at incorporating into the computer simulation software as much of the required knowledge and expertise as possible. These systems (ESCS) enable engineers, researchers, designers and businessmen to perform simulation experiments adequately without being specially trained in many fields of knowledge (programming languages, experiment planning,statistical analysis,etc.).
indicators, but much rather, allude to computer simulation instead. A base version of the CTC for which the multi-purpose simulation model was developed is shown in Fig.l . As you can see from the Diagram in Fig. I , the base version has all the main has all the main components of the state-of-the-art "Steel-Rollng" complexes. Accordingly, the software components have been developed to support the required "usersimulation system" interaction procedures (see Fig.2).
The Institute of Control Sciences of the Russian Academy of Sciences has developed the Concepts for computer simulation with the components which can be refevred to the ESCS. Further evolution of the traditional programming languages for simulation (GPSS , SIMULA) allows using an object-oriented approach to the development of the software for multi-purpose simulation systems including those which are combined with expert systems.
They are listed below: -procedures for introducing a database, these procedures are common for all versions; -procedures for generating versions of CTC using general and specific data; -procedures for simulation experiments with the generated CTC version; -procedures for presenting and analyzing the results of the results of the simulation experiments; -procedures for maintaining the base of the results of the CTC version computer simulation; -procedures for synthesis of the results simulation experiments in accordance with the goal of the analysis.
Modern versions of the algorithmic and software support of ESCS for CTC in metallurgy are developed using the Windows programming environment and object-oriented software versions of the universal languages C++, Pascal. The above software tools facilitate the application of the block modelling concepts and of the so-called "model designer" [Vlasov and colleaques (1981) and Su-Shi-Quan and Zhao Lin-Liang (1992)].
The problems to be solved and their interaction are shown in Fig.3. The experience of using a software package of the simulation system has shown that it can be used both, in design of "Steel-Rolling" CTC with various equipment set-ups and technological flows , and in current schedule planning, developing contact schedules to support the interaction of the CTC components so that the production capacities can be used more efficiently.
In the context of the CTC analysis and synthesis the "model designer" should have as part of its structure the advanced tools for describing technological equipment, material flows and control algorithms (CA) which are built around the procedures of design and changing information in the respective databases (DB). The "model designer" in its structure should also have the knowledge base (KB) containing the modelling rules, and a mechanism for modelling in accordance with the specifications supplied by the user.
The main results obtained with the sumulation software package using specialized programming languages, GPSS-PC and FORTRAN, are described in e.g.[Vlasov and coleaques (1992)].
With the equipment DB the designer of the CTC versions can implement the technique of the "nested" models [Vlasov and colleaques (1981)].
In the recent decade significant results in computer simulation are associated with artificial intelligence methodology and, specifically, its applied field , knowledge-based systems.
This permits the study of the model of one CTC with different degree of detail. By choosing simpler models one can study more versions (due to the shorter modelling time). At a higher degree of detail one can give a deeper insight into more promising alternatives.
Simulation systems based on knowledge are a result of combining two technologies: expert systems (ES) and computer simulation (CS) [Merkuryeva and Merkuryev (1991 )]. These
166
Moreover, the class descriptions can be specified, by making them simpler, ignoring the attributes, states, or subsystems which influence, but weakly, the results, or vica versa, by making them more comprehensive. The effect of the object class properties on the simulation results should be subjected to expert assessment.
CA which would prevent getting into a situation preceding the conflict. In this case the rules are eloborated in a dialoque. The expert is given a description of the assense of the conflict. The expert has to either chose a decision from already existing ones, or find a new one. This approach denotesa change in the control paradigm from "rigid" approach when all CA are described to a "soft" approach assuming incomplete set of CA, inspecified algorithms and tools for generating CA by the user-not a professional programmer. To implement this capability it is required to compliment the traditional programming languages with the systems built around the "soft" control concept which support CA DB and use the CA in developing the control components for the simulation system.
The equipment DB can be implemented through the objects the network presentation of studied by the methods of object-oriented programming. In design of the CA DB one of the key issues is the generation of a mechanism formalization of model situations. To this end, Le. for discribing the CA, use can be made of the procedure presentation mechanism, for example, production systems.
When developing CA with the prehistory accounted for the expert's work is much helped by the capability of returning the model to a state preceding the conflict.
CA KB assumed to be evolving, originally may contain simple rules like (these is at least one non engaged system available in the next of systems in the process class sequence)~(perform processing of the material flow unit in a system with the lower index). As practice shows, such simple and readily formalizable rules or their sets are used rather often. For instance, in modelling the interaction of various systems in the CTC of steel melting shops, these rules implemented by logic algorithms were used for simulation of control inputs [Vlasov and colleaques (1981 »).
To generate CA related with the model, it is possible to use a method based on human operator observations. We know from practice , also for CTC in metallurgy [Vlasov and colleaques (1981), (1992»),that this method is much labourconsuming. The efficiency (or production capacity [Vlasov and colleaques (1992»)) is not the only indicator of the system performance, there are a number of other critical problems which have to be solved at different stages of the CTC life cycle (e.g. in design, strategic planing and current planning). The artificial intelligence concepts and software tools have demonstrated their potential to resolve the above issues. The approach is illustrated in e.g. [Su-Shi-Quan and Zhao Lin-Liang (1992)] .
Special interest in terms of obtaining efficient control systems present those cases when none of the regular CA in the KB associated with the given simulation model resolves the situation, when the control inputs are inefficient. We will refer to such situations as conflict ones. They can be resolved by an expert designer upon the respective request by the model. If this is the case, the rule for resolving a conflict situation as offered by the expert will be stored in the CA KB thus supplementing it.
When embarking on this approach, one has to find ways to use such creative potentials of man, like eurlstlcs, imaginative thinking and sensations. It is proposed, specifically to use in design special command processors which automatically generate procedures for developing complex systems of the CTC type based on the knowledge of the object models and methods of developing them .
Ideally, the model of CTC controlling subsystems which interacts with CA DB and CK KB should not have conflict situations. There are two possible approaches to the using the resolution of conflict situations: conflict history or not using it.
•
In the latter case a decision is made by analyzing only the current state and situations already planned by that time. Technically, this is the simplest approach.
In this case, however, it is preferential to resolve the above problems not by developing specialized equipment, but rather, by developing algorithmic and software tools which expand the capabilities adding intelligence to the standard computing tools. Here, we have to re-emphasize again that it is
If, however, in the computer simulation of CTC we want to consider the reasons for getting into a conflict situation, then we have to develop
167
reasonable and advisablle machine systems.
to
develop
man-
developing systems with the above properties. Software for these investigations may be demonstrated on the technical exibition MMM95 Symposyum.
It has been stated earlier that knowledge used by man in design or planning is difficult to automate completely.
REFERENCES
The best solution is seen in the following concept of creating intelectual decision making support systems (IDMSS).
Vlasov S.A , Belov AD. , Computer Simulation Applied to CAD of Computerized Technological Complexes in Metallurgy. Preprints of 7-th IFAC Sympo~um on Automation in Mining , Mineral and Metal Processing.Beijing, China, 1992. Merkuryeva G.V., Merkushev Yu.L. Expert Systems of computer simulation. Tekhnicheskaya Kibernetika. 1991. N3. Vlasov S.A., Maly S.A , Tomashevskaya V.S. , Tropkina A.1. Integrated design of metallurgical complexes. M: Metallurgiya Publishers, 1981. Su Shi-Quan, Zhao Lin-Liang. Artificial Intelligence Techniques In CIPS (CIMS) for Mining Mineral and Metal Processing: A Review and Future Direction. Preprints of 7th IFAC Symposium on Automation in Mining, Mineral and Metal Processing.Beijing.China, 1992.
In this case the experience of creating simulation systems can be utilized with the utmost efficiency, - since they in essence are also systems for support of decision making during the simulation experiment. The IDMSS for production planning should have the following capabilities: support of knowledge base (KB); support and check-up of the planned decisiones library; hight-quality logical analysis of the decisions made; review of the plan. The structure of information and software support of simulation systems developed at the Institute of Control Sciences for CTC of continious-discrete types of productions r - - - - - - - - - - - - - - - - .. - - - - - - .. - - - - - - ...
ere for Steel-Making Plant -------~----------------------
: - - - - - - - - - - - - - - - - -1- - - - - - - - - - - - - ~
Fig.l
168
Initial DATABASE for used to simulate CTC versions
Procedure for developing a
~--------------------------~ CTC Tecnological diagrams
~ CTC version and generating a data file for it
1
Equipment set-ups CTC versions Parametrs of input and output material flows CTC equipment parametrs Parametrs of material processing operations Parametrs of auxilary operations (maintenance of equipment, transportation, etc.) Control algorithm parametr values Description of initial states of CTC components
~
SIMULATION MODEL
r+~------------~ Modeling of: CTC equipment functioning Material flows Datajlows Control algorithms
,
Procedures for maintaining the original DATABASEfor ....---I~ software used to simulate CTC versions
SOFTWARE', for 'system monitor
Procedures for ANALYSIS and SYNTHFSIS ofCTC modeling versions
USER
,
1 DATABASE OF RESULTS OF CTC VERSIONS MODELING AND SYNTHESIS Calculated annual efficiency: of individual systems, gruops of equipment , CTC as whole; Parametrs of the main technological operations; Parametrs of auxilary operations; Characteristics of reaching the planned targets of production; Data for analyzing the efficiency of control algorithms; Schedules for functioning equipment units in the simulated versions; Schedules for processing material flow units in the simulated versions; Fig.2
169
Long termed target for CTC "Sheet-Rolling Mill"
Capacity of the CTC "Sheet Rolling Mill"
I
t 1
1
+
-.L
I
t
+
I· 1
I
Versions of the work schedules Section Mill 1 1
1
1
1 1
1 1 1
A
-----------1 +
+
1
Versions of short term functioning the CTC systems Rolling Plant 1 1
1
1 I
I
I
'"
t
Versions of the schedules for functioning CTC Casting
1 1
1 1 1 1
I
. 1
. ~~ysis &'SynteSi$
of Planes ' 'os.' '"manifactory'i' 'of SteelMaldng Plant
Versions of short term functioning the CTC systems Steel Making Plant
+, Anal~~ .~$~tesis 'fUriCtiQrun~:, of'~JTCSteelMaking Plant
ere
t
I
+
Versions of schedules for functioning the CTC systems Steel Making Plant
Fig.3
'"
I