Design and Realization of the Iron Melt Transport Simulation System LUO Shou-zhang 1, LIU Feng 2, CUI Jian-jiang 3, ZHOU Ming 1, ZHOU Ren-yi 1

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1 Design and Realization of the Iron Melt Transport Simulation System LUO Shou-zhang 1, LIU Feng 2, CUI Jian-jiang 3, ZHOU Ming 1, ZHOU Ren-yi 1 ( 1 Baosteel Technology Centre; 2 Baosteel Transport Dept. ; 3 Research Center of Control & Simulation, Northeastern University) Abstract:In this paper an iron melt transport system is analyzed. In allusion to the characteristics of the system, which is a hybrid dynamic system, different from railage system, and includes human factors; an iron melt transport simulation system is established. By the solving and application of a series of key techniques to the simulating system, the simulation system can analyze the characteristics of present systems and of those under construction. The conclusions can not only serve as decision-support principles but also provide parameters and references for the optimization of iron melt transport system in locale. Keywords:Iron melt transport system; railway system; logistics; simulation system; hybrid dynamic system Introduction Simulation technology is extensively applied in various areas of industry. Entire proceeding oriented simulating system provides reliable tools for solving practical problems. There are three blast furnaces in Baosteel. Through the railway, the iron melt [1-2] filled in torpedo car (TPC), powered by locomotives, are supplied to three steel plants, two iron foundries and a commercial foundry shop, shown as Fig.1. According to plan, the No.4 blast furnace will be built, then the logistics of current iron melt system would be adjusted. The transport capacities of iron melt and transport organization should also be changed. The logistics of iron melt will be more complex after the No.4 blast furnace construction. Before No.4 blast furnace construction, for the purpose of ensuring that the iron melt transport will meet the production demands of iron-making and steelmaking, we must rationally arrange the railway net in No.4 blast furnace area, study the cross effects between railway transport and road transport, and study rational reform plans of railways in No.2 steelmaking area. Simulating research has been carried out for iron melt transport system [3-4]. Because of its limits of research range and methods, it cannot be applied to researching entire iron melt transport system. For studying the entire proceeding of iron melt system, the iron melt transport simulating system was developed. It can be used to analyze the current or future iron melt system and to research the iron melt transport capacity scientifically and systematically with characteristics of no risk-taken, low cost and reappearing. According to the system simulating report, we can optimize designs of railway and road, optimize allocation of transport facilities, optimize railway transport project, verify the feasibility of project and system capacity, and provide decision support for system design. 1

2 Front Desulfurizing Back TPC Slag tipping TPC pouring shop No.1 steelmaking locomotive Front Desulfurizing Slag tipping Back No.2 steelmaking TPC pouring shop electric furnace TPC pouring shop Fig.1 proceeding of iron melt transport 1 Analysis of iron melt transport system 1.1 logistics analysis of iron melt transport system The iron melt transport system is an important component of Baosteel logistics. If iron melt is regarded as the logistics in this system, on the whole, it flows with one direction. The routes are irreversible and not closed (Shown as Fig.2). Source 1BF 2BF 3BF 4BF Iron melt transport system Leak 1SM 2SM 3SM 1IC 2IC CW Fig.2 principles of Baosteel iron melt logistics Where: BF denotes blast furnace, front number denotes order, SM denotes steelmaking, IC denotes iron foundries and IW denotes commercial foundry shop. If TPC is regarded as logistics object, then the logistics is cycling, and the routes are closed, shown as Fig.3. Obviously, this dual logistics object has essential distinctions to ordinary logistics circumstances. Together with multi-source, multi-leak and overlapping each other, the sophistication of this question was increased. 2

3 Fig.3 principles of Baosteel TPC logistics 1.2 State performance analysis of iron melt transport system Release and occupation of lines, start and arrival of trains in railway transport, are expressed as state variables of dispersed system. Another kind of variables event variables s (such as: semaphore) occurence will trigger changes of system status directly. Rapid expansion of this kind of system and continuous demands for performance will promote the research works on Discrete Event Dynamic System (DEDS). For the dispersed property of state variables, many new questions have arisen in its theoretical research. Practical applications of DEDS have a lead over its theoretical works. Hybrid Dynamic System (HDS) is a combination of Continuous Variable Dynamic System (CVDS) and DEDS. Obviously, the method of HDS tallies with many practical systems s inherent law. The move of train in iron melt transport process and the process of iron melt desulfurizing can also be regarded as CVDS. As a result, desired precision and effects can be obtained only by using methods of CVDS. The iron melt transport system is a complex continuous dispersed event hybrid system which mainly contains dispersed events, not a simple DEDS. 1.3 Comparison and analysis The programming and operation of Baosteel iron melt transport system belong to plan and scheduling of railway transport. But there are some differences comparing to common railway transport as follows: (1) There are processing progresses in logistics, for example: desulfurizing and so on; (2) Comparing with the regularity and periodicity of railway transport, the iron melt transport system has properties as randomness, uncertainty (Changes of demands effect the whole system, make the system unstable), non-periodicity. It is typical of multi-target, multi-factor and multi-level; (3) The balances of quantity, composition, time and temperature of iron melt demanded should be considered preferentially; (4) For reasons of effects by steel using plan, limited operating area, many rail lines, railroad switches, multiplexing lines, locomotives and TPC, this system s scheduling is much more difficult than common railway scheduling; (5) It is difficult to increase the railroad transport capacity because of exists of many road junctions and its high occupation; (6) Many advanced theories and methods of modeling and computation which involve many domains should be applied for the complexity of system; The target of this system is to realize maximum transport capacity of railroad nets, decrease consumption of materials and energy, based on ensuring safty in production and logistics balance, energy balance, resource balance, time balance, etc. 2 Modeling of iron melt transport simulating system Based on similar theory, system technology, information technology, through computer and varieties of physical facilities, using mathematical models, the practical or virtual systems are experimentally researched by system simulating. According to system procedure, by simulating practical process through computer programs, 3

4 the dynamic behavior of system can be obtained, then function indexes can be generated. Through analysis of iron melt transport system, the modeling of this system contains: (1) With regard to objects such as iron tapping exit, iron tapping line, desulfurizing workshop, TPC pouring workshop, front and back slag-off workshop, slag-tipping workshop, electric furnace, ingot mould, pig machine, furnace kiln and so on, the Petri net modeling method is adopted for characteristics as asynchronism, distribution, uncertainty and parallelism; (2) Centering on time and iron melt quantity, not on industrial progress, so the operation models for each processing site are established by statistical chart; (3) As to continuously changed objects such as moving locomotive, the mechanization modeling method is adopted; (4) As to objects intervened by human being, such as route choosing of locomotives, the rule based model is built by imbedding expert system. 3 Implementation of simulating system by stages For avoiding risks in developing process, and taking concerted action with design and argumentation of practical system, the simulating task was carried out by two stages. First stage: centering upon No.4 blast furnace area, the plans for railway net and transport scheduling after No.4 blast furnace construction were investigated. Technologies formed in this stage can be used in next stage. Second stage: simulating frame was expanded to the entire system on the basis of first stage. 4 Frame of the simulating system The topological structure of Baosteel iron melt transport simulating system is shown in figure 4. The system is combined by simulating computer, database computer and animating computer. The simulating programs run in simulating computer, at the same time data generated are writen into database computer. The animating computer acquires simulating data from database, and shows them on interface by animations. The logical structure of this system is shown in figure 5. Database Hub Iron melt simulating Animation Fig.4 topological structure of simulating system 4

5 Condition set up Iron melt transport simulating models State display of processing sites Initialization Input interface Database Output interface Queues running display Manual intervene Results analysis Chart & graphics 5 Functions of simulating system Fig.5 logical structure of simulating system The iron melt transport system is a large scale and complex system. Module decomposing method which bases on mechanism or function can be used in complex system modeling. Module decomposing method based on fuction can realize correspondance with practice, local sub-system simulating and application of stage results. Moreover, it can also shorten the period of application of simulating results. Fig.6 functions of simulating system By module decomposing method based on function, the simulating system is separated into some independent modules. Relations between these modules are shown in figure 6. Based on function the whole system can be divided into five layers: System management layer: it realizes total control and coordination; Scheduling management layer: it realizes management of schedule events; Running management layer: it realizes management of train moving; Auxiliary layer: realizing auxiliary functions; Basic layer: realizing management of railway net in simulating system. The modules can also be classified as modules for constructing simulating platform and modules corresponding to functions of practical objects. The functions of main modules: Initialization module: providing initialization parameters such as layout of railroads, capital repair plan, output of blast furnaces, output ratio of iron melt, verifing rationality of parameters set by logistics balance; Simulating module: constructing simulating circumstances, controling and scheduling modules when system running accrding to simulating tactics; 5

6 Status evolution module: Changes of object from a state to another are called status evolution. Realizing automatic status evolution of blast furnaces, middle processing sites and TPC pouring factories; Sheduling module: it can be divided into three layers as logistics balance layer, process decision layer and transport job scheduling layer. Logistics balance layer sets up initial process data and verify logistics balance. Process decision layer does Marco coordination and process decision. Transport job scheduling layer sends orders to selected locomotives according to process information, then the locomotives do transport jobs after receiving these orders; Anti-collision module: resolving route conflict when locomotives are moving. In the iron melt transport simulating system, the locomotives are independent to each other, move safely through anti-collision module; Locomotive and TPC module: According to combination style of locomotive and TPC, model of locomotives, the locations of locomotives and TPC are computed and refreshed; Route choosing module: providing initial move routes, anti-collision routes or new computed routes to locomotives; Railroad net module: expressing railroad net in the abstract, recording attributes of railroads, state and statistics infrmation. Fig.7 program flow chart of simulating system In addition, manual intervening function permits users to pause the running simulation, adjust scenes in simulation, and then refresh the simulation and change flexibly the process of iron melt transport simulation system. The program flow chart is shown in figure 7. The animation of simulation is shown in figure 8. 6

7 Fig.8 simulating animation 6 Conclusions The system simulated for six kinds of conditions, analyses iron melt transport capacity, dynamical generation-transport-use performance of iron melt system, the rationality of iron melt scheduling, transport style, and railroad programming. Simulation system is an analogue process to practical system, not a kind of system optimization method. Although it cannot obtain optimum value, we can change parameters and simulate repeatedly according to results of system models. System simulating is an indirect kind of method for system optimization. As concerning the multi-target, multi-factor and multi-level system, absolute optimum solution is not existed. The optimization is relative, so it has a practical significance to study complex system, and to seek optimization methods by simulation. References: [1] Wang wenrui. Iron melt control and management system in Baosteel [part one] [J]. Metallurgical Industry Automation, 2001, (4): [2] Wang wenrui. Iron melt control and management system in Baosteel [part two] [J]. Metallurgical Industry Automation, 2001, (5): [3] Xu dong, Fei binquan. Computer control and research of iron melt transport system [J]. Journal of Shanghai University (natural science edition), 1999, 5(2): [4] Zhang Shuguang, Fei Binquan. Research of train control models of iron melt transport in concentrated area in steelmaking plant [J]. Journal of Shanghai University (natural science edition), 2000, 6(1): LUO Shouzhang, male, born in , senior engineer, Ph.D. graduated from Central-South University, between and did research work in manufacturing department of Baosteel, after do research work in Baosteel technology center. Mail address: 1306#, Technology Building, Baosteel Technology Center, Fujin Road, Baoshan, Shanghai, P.R.C szluo@baosteel.com Phone: ,