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APPLYING DISTRIBUTED COMPUTER CONTROL TO MODERNIZE STEEL STRIP ROLLING MILLS W. E. Miller (.'(111.111//(/11/. / ' /11(" ,\'\ CI/II/m/ .
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Abstract. Very few new strip mills are being built, or considered. However, there is worldwide interest in modernizing the many existing mills to provide the high quality flat rolled products demanded by today's users while keeping to a minimum scrap and production losses. Islands of Automation , a concept introduced in the sixties with the early application of digital computers to process control, still provides the most cost effective approach to modernizing and upgrading the control of both discrete and continuous manufacturing processes. Distributed Computer Control Systems (DCCS) technology used in Islands of Automation permits step-by-step implementation to modernize and upgrade many existing strip rolling mills. Carefully planned programs can optimize the use of limited capital resources, and provide early benefits to fund the next step . And, the step-by-step approach provides an efficient method for training, and technology transfer for projects in developing countries. The Factory of the Future, and The Factory for the Future, in most cases, remain unrealized visions for the foreseeable future, even in developed countries. Millions of dollars have been spent to promote appealing "blue sky" concepts to sell hardware and software. Billions of dollars have been spent by technically unsophisticated users to install equipment to automate factories too worn out to ever operate automatically, let alone even operate satisfactorily without continuous human operator observation and intervention. Automation is not an easy Fix-It for fundamental problems. This paper is intended to provide basic guide-lines for the selection of potentially viable projects, to discuss project hazards frequently overlooked, and to present a basic system architecture utilizing today's technology, yet suitable for the future. The examples are from U .S. installations. Process examples are the steel hot strip rolling mill, and the tandem cold reduction mill. The outcomes and experiences could be repeated elsewhere, in both developed and developing countries.
Even a thirty year-old hot strip mill has high investment and high throughput values. Daily throughput is more than (U.S.) $1/day per tonne per year , more than $1 ,OOO,OOO/day. A 1% improvement in yield returns $10,000 per day, easily achievable by adding computer mill setup and control. On cold reduction mills, automatic gage control using both feed forward and feedback techniques can produce high quality strip from relatively poor hot bands. Hatness or shape control can help adapt the cold mill to the incoming hot band cross-sectional shape . On both mills the digital computer can provide an accurate mill setup for every coil rolled. Steel strip can be produced to tighter dimensional and metallurgical specifications. Mill production can be increased, and scrap losses reduced. Keywords. Steel industry; Rolling mills; Computer control; Multivariable systems; Thickness control; Temperature control; Tension control; Shape control. INTRODUCTION Islands of Automation, a concept introduced in the sixties with the early application of digital computers to process control, still provides the most cost effective approach to modernizing and upgrading the control of both discrete and continuous manufacturing processes. Distributed Computer Control Systems (DCCS) technology used in Islands of Automation permits step-bystep implementation to modernize and upgrade many existing strip rolling mills. Carefully planned programs
can optimize the use of limited capital resources, and provide early benefits to fund the next step. And, the step-by-step approach provides an efficient method for training, and technology transfer for projects in developing countries.
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THE ISSUES: - WHY AUTOMATE? Automate, emigrate, or evaporate" were the alternatives suggested to U .S. steel, aluminum, and automotive companies by major U.S. and Japanese automation equipment suppliers in 1983-85 presentations and advertising. These grim alternatives attracted attention, and were widely quoted, including the national TV network evening news. The proposed solution, the "Factory for the Future would provide a flexible manufacturing system to solve manufacturing problems, almost forever! The cost of such a system would depend upon the size and complexity of the manufacturing operation. H
While the appeal of such a system is great, we need to take a more critical look at fundamental problems and possible solutions. My nrty years of professional experience involved drive systems, automatic control, and automation of metallurgical processes. That experience includes the first successful application of feedback control to large industrial drive systems on five tandem cold strip mills in 1946-47. The first application of a digital computer control on a hot strip finishing mill in 1960. Our first computer, a 16K, 24 bit word, all drum memory machine, provided a real challenge. We made it work, and it was used for almost 20 years! Why did McLouth Steel purchase that fIrst computer control system for their hot strip mill? Because the General Superintendent was convinced that computer control would provide consistent strip quality, improve yield, and increase production. It did! Being [lISt, being correct, and being successful paid big dividends to McLouth! Located in Detroit, the automotive manufacturers favored Mc Louth for their uniquely uniform higher quality steel strip. So, why automate? Primarily to improve quality . increase yield. increase production, and save energy. What should we automate? We should look first at production processes with high throughput, high value of [mished product. and high equipment replacement cost. We should look for processC'S where we tind signillcant variations in performance between work crews, and during work shifts. There are three rolling mills that satisfy these criteria; the hot strip mill. the plate mill. and the tandem cold reduction mill. THE ISSUES: - QUALITY OF FINISHED PRODUcr
On a worldwide basis, in both capitalist and socialist economies, consumers are demanding better quality. In my opinion consumers make their. purchasing decisions [lISt on quality, and second on price. U.S. automotive manufacturers #1, #2, and #3 each claim product quality superior to their competitors. Though they correctly perceive the market need, meeting that requirement is a far more difficult problem. Improvements in product quality require improvements in manufacturing machinery and procedures. In the automotive industry minor design changes are made every year. Major model changes are likely every five or so years. The net result has been evolving, but not carefully planned automated manufacturing.
The raw materials for the automotive manufacturers are the finished products of the steel industry . Unfortunately, it was only in late 1985 that the critical manufacturing problems caused by thickness variations in the flat rolled steel products used on automated production lines were publicized. In a Plenary Session address at the Annual Conference of the Association of Iron and Steel Engineers, Roger Smith, the Chairman of General Motors, the largest automotive manufacturer, advised that flat-rolled steel products purchased in 1986 would be to one-half "commercial tolerance H, and in 1987 to one-quarter Hcommercial tolerance". The tolerances specified for 1987 had been achievable in the USA, EEC, and Japan for more than ten years, and more recently in South Korea and Taiwan. However, during these years, the steel companies would provide steel products to smaller dimensional tolerances only with excessive price additions. So, users accepted, and coped with the commercial tolerances established many years earlier, before even crude automatic control! Faced with the loss of a major market, U.S. steel companies responded. Existing systems were retuned to improve performance. New automatic gage control and computer setup systems were purchased to provide better performance .. Statistical Quality Control (SQC) became the "Hot Subject of the Eighties". In many cases the SQC software provided with the digital computer control systems of the sixties was used. We used it to prove to McLouth and later customers that the computer control system did produce steel strip within tighter dimensional and temperature speciflcations. In most cases after we left the plant, the SQC programs had been ignored! THE ISSUES: - QUALITY OF MACHINERY - QUALITY OF RAW MATERIALS Automation is not an easy "Fix-It" for fundamental problems. Poorly performing machinery, like a human being, needs a careful examination to correct ailments that contribute to its defIciencies . For example, is process performance severely limited because of inadequate power on one or more drives? Is down time excessive because of obsolete or worn out m-g sets or mercury arc rectifiers? Are poor plate or strip dimensional qualities primarily due to excessive wear in mill housings, bearings and screw gearing? Is screw down train backlash making it difficult to control gage? These questions and others require answers as inputs to the planning data base for viable and cost effective upgrade of existing processes. U.S. newspapers have reported "evaporation" of V .S. steel production due to imports. In my opinion, most of this 'evaporation" resulted from the shut-down of obsolete facilities, totally incapable of being modernized to produce the quality steel products required by today's market. Existing continuous hot strip mills and tandem cold reduction mills have high investment values and high throughput values. Many such mills have been remanufactured and automated to produce quality flat rolled steel products suitable for the world market, and usable for the automated manufacture of cars, trucks, and appliances.
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Within reasonable limits, a remanufactured and automated tandem cold reduction mill can correct for gage variation deficiencies of its raw material, the hot band. flatness or shape control is available to help adapt the cold mill to the incoming hot band cross-sectional shape. This function requires at least the addition of pasitive roll bendL"lg on all stands, and spray control on the last stand. Every manufacturing process must contend with the quality of raw materials used. The quality range must be defmed. The manufacturing process and its automatic control must be compatible with the raw material quality range and the machinery. THE ISSUES: - QUALITY OF DECISIONS One can profit from the experiences of others. or repeat them good and bad. Today with the relatively low cost and rapidity of communications and transportation, repeating the bad experiences is inexcusable. Conferences organized by the International Federation of Automatic Control (IFAC) , the American Automatic Control Council (AACC). the Association of Iron and Steel Engineers (AISE) provide a first level of information. However, success for an expensive automation project requires in-depth information and knowledge, and active participation of experienced and technically sophisticated people. Engineers are generally willing to share experiences on a people-to-people basis in meetings like this one . Let us take full advantage of our opportunities during discussions at this conference. Let us go back to earlier comments on the "Factory for the Future" with its computers , robots and flexible manufacturing. The U.S.'s largest automotive manufacturer is reported to have spent two billion dollars on equipment and installation of the "Factory for the Future Definitive results have not been published. However, the program and the expense were criticized publicly by the largest shareholder and Director. No one claimed the program a success. H
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The #2 automotive manufacturer and his consultants studied similar proposals. They evaluated the concept as unrealistic at that time for their facilities and practices. What were the results? 1. The market share of #2 has grown every year since 1985 at the expense of # I. 2. In 1986, 1987. and 1988 the protits of #2 exceeded the profits of # 1 for the first time since 1924. 3. In 1986 the Japanese and American equipment suppliers merged their automation equipment business operations. 4. In early 1987 the USA supplier ceased manufacture of robots, closed the plant, and put it up for sale.
A thorough evaluation of the alternatives is a necessity. We should divide risks into two categories: (1) those we must take, and (2) those we need not take. Avoid the down side risks. In our business these are likely to involve the 'latest and greatest, or novel technology"! I remember one we took about 1970. We were developing our first Programmable Logic Controller (PLC). The plated wire memory was selected for marketing novelty as the latest and greatest over the then widely used core memory. Unfortunately for us, the manufacturing process for the memory size and reliability that we needed turned out to be unproven, and not attainable. We ended up with a significant redesign to use the conventional proven core memory. TIlat choice was a down side risk that need not have been taken. Before signing a contract for a major program, a thorough investigation of the previous performance of the supplier on comparable projects is a must. Some of you may recall the start-up problems of the computer controlled Bay Area Rapid Transit System, or BART in San Francisco years ago. According to San Francisco Chronicle Staff Writer Demoro in a front page story on October 25, 1988. BART is in deep trouble again. "Ten years ago. things were so unreliable that passengers were very lucky to get a train". The system was fmally fued , and a decision made to expand and modernize. Now according to Demoro, "the new cars are years late and plagued by technical problems, and a computerized train control system is over budget and may never work. The FBI is now investigating for fraud." Computer control was very new when the first system was purchased from a systems vendor with questionable experience in computer control. A repeat experience of the magnitude reported appears to be inexcusable with the knowledge and experience available todav. Civil litigation over failure to meet performance specifications can drag on for five or ten years before a fmal judgment Or, even if the supplier does agree to remanufacture the equipment, production may be lost for one or two years. Fortunately, during my flfty years of practice, I have never had to take a customer through an unsuccessful venture. I don't mean to imply a total absence of problems. The few problems that did arise were solved to mutual satisfaction. PLANNING AN AUTOMATION PROGRAM The key to implementing a control upgrade in a real world plant is flexibility . Only in a greenfield plant is one likely to fmd the text book examples of multilevel, or distributed control systems. The economic solution to matching user's desires, vendor hardware/software, and effective use of existing equipment results in a system structure specific to each project. Experiences of users and vendors should be considered when planning a new program. THE SYSTEM STRUcruRE
Let us recognize that the quality of decisions is critical to long term viability of an enterprise. Few companies have the financial resources to plunge ahead, then withdraw and write off huge investments. My professional engineering experiences recommends a top-down long term plan with step-by-step implementation from the bottom up.
Functions are grouped into a three level hierarchy: basic drive, basic automation, and process setup and control. (Fig . 1) Because the hot strip mill extends over a distance of one km, the control system is distributed geographically as well as functionally.
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Basic automation functions such as drive sequencing, positioning control, automatic gage control may be performed in any of several categories of equipment drive control, Distributed Micro Controner (DMC), programmable controller (PC), or computer depending upon geographical location, accuracy requirements and update frequency. The structure of a system for a specific upgrade project will be influenced by several major factors: ·The process itself ·The existing machinery, and its condition ·The existing drive and control equipment, and its condition ·The size and scope of the project, Le. functions to be improved, or added ·The vendor's drives, control and automation equipment ·The vendor's previous experience ·The user's previous experience A number of world-wi.de vendors wi.th varying degrees of experience offer systems and equipments wi.th varying degrees of suitability for performance upgrade of large metal rolling mills. In this presentation, it is practical to present only one typical system. GE (USA) is a major supplier. My previous work experiences wi.th GE, and my last eight years as a consultant suggest that GE's current systems and products offer good value for metal rolling mill applications . While the system configuration described will be specific towards GE's current practice, one should be able to modify the configuration to suit offerings of several other vendors. For example , recent papers, publications, and press releases disclose that GE, Westinghouse, and ASEA BBC use Digital Equipment Corp V AX computers for mill setup and process control. All use Ethernet links between computers. GE and Westinghouse use peer-topeer data highway protocols implemented in slightly different manners. (Cowan, Foulds, Smith, 1988). GEFanuc and Allen-Bradley use Micro-V AX technology in their programmable controllers. (Collins, 1989). So, in the descriptions that follow the hardware technology will be common, even though the organization may be specific. The Process Control Level
Mill process control functions may be handled by one or several process level computers. (Fig. 2) The mill setup computer provides setup and temperature control of roughing mill, fmishing mill, runout table strip cooling, strip coiling, product tracking, mill pacing, performance evaluation, and communication wi.th a management information system (MIS) computer. The furnace computer provides furnace and slab temperature controL An on-line backup computer may also be provided. The computers are duplicates. The System Bus The system bus is the communication channel for information transfer between control computer(s) and DMCs, PCs, operator stations, drive controls and remote devices. Current systems are peer-to-peer, as contrasted to previous generation master-slave systems. The GE Control System Freeway (CSF) implements peer-to-peer communication via a token passin~ proto-
col. A global signal memory communication technique makes all significant control signals available equally to all stations on the system. This feature provides use of a given signal at several stations in the system - a characteristic typical of drive system control where the operator stations, computer control stations, and drives are physically distributed along the process. The system also supports directed message communication between two specific stations. For example, CPU to CPU communication may be used for program down loading from one of the process control computers to local control processors. The host computer, (top of Fig. 3) in addition to on-line control, provides CSF support functions. ·CSF system control and diagnostic support functions. ·System signal management: manages the identifi cation and use of all signals . ·Station program support: storage for, and down load, up load of DMC and PC programs.
1'wi.nex cable is used; signal transmission is carried over two conductors which are independent of the shield. Greater noise immunity is achieved; the shield which may carry ground currents is not used as signal return (as in coaxial cable). Two cables are used to insure communication integrity. Each station transmits on two cables; each station listens on two cables. If one cable is broken, a receiving station hears nothing coherent on that cable and marks it out of service. System diagnostics can display the location of the cable break. The token passing protocol includes a means to automatically reconfigure the logical token passing path to route around a station which exits the network for any reason. Likewi.se, when a station enters the network, the system automatically reconfigures the token passing path to include the new station. SYSTEM CONTROL STATIONS The CSF based system consists of standard control stations configured to meet the needs of the application. (Fig. 3) Computer BIU and Sig.nal Server provides the basic interface between the CSF and a host control computer, typically a V AX. The global signal memory is maintained in the common region of the control computer such that global control signals are readily accessible to all the application tasks wi.thin the computer. The Signal Server formats the CSF global signal memory for the target controller. The transfer of the control signals between the computer and the BIU is via a parallel direct memory access mechanism for appropriate system speed and to minimize load on the host computer. Bus Interfa~ Unit - BIU prcvides the control interface between the various types of stations in a typical drive system . The computer BIU is not the master of the system; it is another peer station. Operator Control Station Interface is a Distributed Micro Controller (DMC) based structure. It provides communications with basic displays and operator devices. It includes simplified table driven mechanisms to read the input hardware and transfer the signals to the
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global signal memory, and to drive the output hardware from signals selected from global signal memory. Drive Group Control communicates with the CSF and handles local drive communication functions through a parallel local bus which plugs directly into the drive regulator control. The drives in a system are typically grouped under local master control functions. The DMC handles the inter-drive regulating functions. Series Six BIU and Signal Server provides the interface between a Series Six Programmable Controller (PC) with its local VO and the CSF. The Series Six PC is frequently used for sequencing type control functions such as conveyor control, coil handling, etc. The Series Six VO may be configured for mounting a~ the Series Six CPU, or remotely where there is a separate concentration of I/O. DMC Based Control provides regulating type functions in a drive system , such as position regulation, gage control, tension control, and hydraulic control of roll gap . The I/O for the DMC may be mounted with the DMC, or may be located at a remote concentration of signals. Field VO Station is used to collect inputs from stations scattered throughout the installation , and which are used by a number of control stations. The field VO station is used to collect such inputs for the global signal memory , and to drive local outputs from signals gathered from the global signal memory. The handling of I/O includes the appropriate scaling and unit conversion. Specialized Stations may be configured to provide communication between the CSF and vendo r equipments utilizing RS-232 type interface, for example scales, Xray gages, etc. HOT STRIP MILL PROCESS CONTROL Let us briefly examine the operation of a computer controlled hot strip mill. (Fig. 4)
The slab enters a reheat furnace . After reheating, the slab is pushed from the furnace . It is reduced from 250mm to 30mm in the roughing mill. It slows down, or halts momentarily on the delay table. The front end is cropped. It enters the fmishing mill, where it is reduced to strip thickness, typically 3mm. It is conveyed over the runout table where it is flooded top and bottom with jets of water. Entering the coiler, the combination of fmishing mill, runout table and coiler accelerate to double or triple thread speed, reaching a typical maximum of 20 meters per second. As the tail end departs, each mill stand , table section, and coiler decelerates to receive the head end of the next strip. Within a few seconds after the tail end leaves a fmishing stand, the next front end enters. The cycle repeats, hour after hour. The total process from slab reheat furnaces to finish coil delivery conveyers operates automatically under computer control. Optimizing Process Performance !he computer controlled hot strip rolling process mcludes several hundred dc drives from I to 10,000
kw distributed over a distance of one km . This very successful application of modern control technology provides examples of the application of multilevel, interactive multivariable, adaptive, and optimal control. The system has three principal controlled variables: thickness, width and temperature, the control of anyone of which interacts upon the other. These can be subdivided into primary and secondary variables . (fable 1)
TABLE I Controlled variables Primary controlled variables
Finish thickness Finish width Finish temperature Cooling pattern on runout table Coiling temperature Secondaty controlled variables Temperature at roughing mill exit Temperature at furnace exit Finish strip shape Production rate Control algorithms and process models are documented in the literature (Fapiano, 1985; Foulds, 1988; Miller, 1981). In a short paper we can treat only the basic process control strategies. The criteria for optimum process operation are: 1. Required strip temperatures at exit from roughing mill, exit from fmishing mill, and at entry to coiler; 2. Required strip dimensions, thickness and width; 3. Adequate strip shape; and 4. High production. Let us examine production parameters. Assuming a balanced high production mill, the production capacity will be determined by the finishing cycle shown in Fig. 5. The fmishing cycle includes the expected rolling time ATl , the adjusting time to reset screws between strips AT2, and the delay between slabs or pacing tolerance AT3 . By continuously adjusting the furnace push rate to the momentary finishing mill capacity , the time of extraction of the next slab can be determined. This action reduces the pacing tolerance time interval, AT3. For the specified ftnish thickness and fmish temperature, the reduction schedule and slab entry temperature to the fInishing mill are calculated. The heat loss between the last rougher and the first fmisher is determined by heat loss due to descaling, steel thickness and travel time from the rougher to the frrst finishing stand. The target temperature at exit from the last rougher, the target temperature at exit from the furnace, and the firing schedule for the hold and soak zones of the furnace are calculated. Since as many as five slabs may be distributed along the mill at anyone time, the calculations pertaining to the furnace exit temperature, furnace firing and furnace push time must be performed some 10 to 20 slabs ahead of the actual rolling of the slab in the finishing mill. Feedbacks along the mill provide update information. Calculations are iterated as a slab progresses to strip to
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correct for stochastic variations encountered during rolling. Automatic control of the push rate (mill pacing) and furnace fuing can effectively increase total mill capacity and reduce fuel consumption per tonne of product rolled. Specific experiences are reported in the Proceedings, *IFAC Symposium on Automation in Mining, Mineral and Metal Processing, 1980*. For example, fuel savings at US Steel, Gary, IN were projected at 15% or $4,000,000 annually. Hoogovens, Netherlands commented on their experience of 10 to 25% fuel savings to provide a 1.5 year payback of the total hot strip mill computer automation system, plus a 10% increase in production (lFAC MMM , 1980). THE TANDEM COLD STRIP MILL The question - what to do to an existing mill to produce the quality strip required to sell in the world market? Many people in many countries ask this question. Howard Cox (1987) provides recommendations in a paper prepared for a People to People Program on Automation Technology . Basic Concepts First, strip thickness is directly proportional to roll speed. So, very accurate speed regulators and master reference control is the first step , and the foundation to build upon . The best available instrumentation for measurement of important parameters should be obtained. For control of rolling force , tension and gage, hydraulic cylinders are far superior to mechanical screws. Modern tension regulators maintain desired levels of tension during threading and running through control of both roll speeds and roll force . Automatic gage control utilizing both feed forward and feedback techniques can produce high quality strip from relatively poor hot bands . Flatness or shape control can help adapt the cold mill setup to the incoming hot band cross-sectional shape. This function requires at least the addition of positive roll bending on all stands and spray control on the last stand. Digital computer control can provide mill setup for each new coil. Greatest benefits will be obtained on mills producing heavier gage , for example with delivery thickness of 0.5 mm and greater.
Digital Speed Regulators The first step in an upgrade program is to install digital speed regulators throughout the mill. Primary benefits include constant regulator gain and system linearity, and extensive diagnostics . Tachs should be directly driven from the drive motor shaft; careful alignment is a must.
Instnnnentation The accuracy of control is dependent upon the accuracy and reliability of the instrumentation. Six basic measurements are used for instrumentation and control They may be implemented in steps depending upon the scope of the upgrade program. Gage. Measurement is possible to an accuracy of 0.1 % using high voltage DC X-ray gages. This gage has significantly less electrical noise in the signal when adjusted to provide the 0.01 second response time required on each side of stands 1 and 2 by the AGe control system. Tension: True dual range tensiometers are available for mills which roll a wide range of products . Electrical systems of newer tensiometers are much less temperature sensitive. It is important to remember that a tensiometer is calibrated for a specific tension triangle which must be maintained as roll diameters change . Roll Force . Hydraulic pressure sensors have joined Kelk and ASEA load cells as useable transducers for measurement of roll force . Roll-bite force , free of mill window friction, can be obtained from a combination of strain gages mounted on mill housings, and a control system which continually recalibrates the strain gages. Roll Surface Velocity. Strip velocity between stands can be measured consistently and accurately using the tensiometer rolls and pulse tachometers. A standard pulse tach may be driven by the tensiometer roll, or a proximity sensor may be used to count pulses from a gear tooth on the tensiometer roll. Strip Flatness. The most widely used shape sensor consists of segmented rolls capable of measuring the tension in narrow segments across the strip. A type with air bearings is widely used in the aluminum industry. These have proven successful so long as the air is kept extremely clean, and the rolls are not subjected to rough handling. Other types with less easily damaged rolls are available, but provide slower response signals , and have higher inertia. Motor drives may be required to avoid slippage and strip scratching. HYDRAULIC CYLINDERS Hydraulic cylinders, like speed regulators, are essential. High speed of response and reversibilty make them ideal for regulation of force and tension. New on the scene are tandem cylinder designs which avoid machining the mill housings . It is only necessary to remove the screw and nut, and insert the cylinders. Long stroke (200 mm) cylinders and hydraulic pressure of 25 mega pasca1s are available. TENSION CONTROL
Depending upon the quality of the main drive regulating systems replaced, improvement in gage uniformity may be significant, or minor . Speed regulator response is limited by the mechanical system to 10 to 15 radians per second. This response can be obtained with quality regulators, analog and digital.
Strip tension is a key control parameter. During threading, tension should be established a fraction of a second after the head end of a new coil enters the roll bite . At this instant, there is no forward tension pulling on the head end. Tension can be controlled only by adjustment of the speed of the upstream stand. Head end off-gage strip may result, but this is a secondary consideration as compared to the necessity for good threading.
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When tension exists on both sides of the roll bite (other than stand I) , and rolling speed is above a critical mini-
mum, tension control can be transitioned from speed to roll force . Operating the hydraulic cylinders in the wForce wmode provides a direct means to eliminate force and tension variations caused by eccentric rolls. AUTOMATIC GAGE CONTROL Automatic gage control consists of three basic subsystems. *The entry system begins corrective action at an early stage of rolling , *The delivery system makes vernier adjustments of the fmish gage. *The monitor system adjusts the set point of the entry system to permit the delivery system to operate near the midpoint of its range. Numerous configurations of this basic system exist. Only basic concepts can be presented in this overview. EotIy End Gage Control
Signals from the stand 1 entry gage are used in a feed fOIWard system to change the position of the stand 1 cylinders to maintain close to constant strip thickness out of stand 1. A tracking system predicts the instant a strip element arrives at the stand 1 roll bite. A roll force model provides the transfer function between cylinder position change and gage change. For the strip thickness and speed from stand 1 to remain constant, the strip entry speed must vary inversely with the incoming strip thickness. The feed fOIWard gage control provides signals to the payoff drive system to maintain constant strip tension between the payoff and stand 1. The gage deviation signal from the stand 1 exit gage is used in feedback control to modify stand 1 cylinder position to obtain the desired gage out of stand 1. This control is relatively slow because of the transport time from the roll bite to the gage. Variations in incoming strip hardness, and stand 1 roll eccentricity introduce gage variations out of stand 1. Gage deviation signals from the stand 1 exit gage are used to change the speed of stand 1. Since stand 1-2 tension is precisely maintained by fast hydraulic cylinders, there is a one to one relationship between gage deviation and the needed stand 1 speed change. For good performance, strip elements must be accurately tracked to the stand 2 roll bite , and signals to the stand 1 speed regulator must be precisely timed for all mill speeds. This control determines the basic quality of the gage produced by the mill. ~rnier Gage Control
The vernier gage control uses the X-ray gage after the last stand to adjust the speed of that stand. On sheet mills, the reduction taken in the last stand is usually very small, 5% or less. So in this case, the speeds of the last two stands are varied, and the tension between the last two stands is maintained constant by varying stand 5 motor speed. Roll force on the last stand is regulated to be constant to provide the desired fmish and roll crown.
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Gage can be held to ± 1.0% for a very large percentage of the coil, even on strip of 0.33 mm. FLATNESS CONTROL Cold mill operators must recognize that strip with entering crown cannot be cold rolled to strip of equal thickness across the strip. One must also recognize that the cold mill must be adapted to whatever crown is received from the hot mill. This adaptive process is made even more difficult by ever changing thermal crown and roll deflections. Roll deflection varies with strip width, roll force , and types of work and backup rolls . In most cases, roll bending on all stands and spray control on the last stand will provide sufficient flexibility to allow the cold mill to be adapted to the incoming crown. COMPUTER CONTROL The system configuration is similar to that already described for the hot strip mill. The major difference relates to the more limited geographical distribution of the cold mill. The highest order of control is the calculated schedule setup. With inputs of hot band thickness, width, hardness and ordered gage , the mill setup computer calculates the settings of the X-ray gages, the stand speeds, the interstand tensions, and the roll positions so as to distribute the load through the mill in the desired manner to provide the desired product. (Miller, 1978) The most difficult task is to predict the rolling force for threading the next coil. However, the fast tension regulators previously described make threading practical even with large force errors. The proper gage and tension control systems greatly reduce the burden of the model to predict roll force. The most recent models consider shape implications when assigning reductions to the stands. If the average incoming crown is known, the model attempts to assign reductions and roll bending to the stands to minimize the corrections that will be required by the shape control system ,
THE FUTURE InTech, the Journal of the Instrument Society of America categorizes our industrial progress during the last half of the 20th century as follows : 1950-60 Maturing of electronics 1960-70 Maturing of solid state electronics 1979-80 Maturing of computer technology 1980-90 Maturing of materials development 1990-2000 Maturing of systems technology We recently witnessed two exciting accomplishments in materials technology. Man peddled an airplane across the English Channel. American pilots Rutan and Yeager flew the revolutionary aircraft, Voyager, around the world, 37 ,000 km, without stopping, and without refueling . In our own field, Michael Babb, Editor, Control Engineering in his January 1989 editorial noted that control
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system suppliers use basically the same set of chips, which is a levelling influence as far as hardware is concerned. And users are less interested in what kind of microprocessor is used. They want to know what the equipment will do for their process, and how it will be done . These are the correct questions for which answers should be required. What will we see ten years from now? Will it be the WFactory of the Future" with robots and other automated machinery effortless turning out products from A to Z . Maybe, but I doubt it.
Miller, W . E. (1978), Cold strip mill automation - tech nology, quality assurance and performance, Gen eral Electric Company, GER 2894, 13 pp. Miller, W. E., and Price, J . C . (1981). Computer automation of hot strip mills, General Electric Comp@Y, GET-6620A, 17 pp. Smith, A. W. (1988) . Innovative distributed control system for an innovative flat rolled products plant, Conference Record 1988 IEEE IAS Annual M~.lID£, pp 1153-1156.
Our field of control science and system engineering is in a vibrant stage of rapid development. The frequency of introductions of new microprocessors, and increases in computer processing speed are incredible . Software is still very expensive. New software is usually late because of "bugs", but improvements in software engineering will come. Babb in January pointed out that Modicon and Allen Bradley now spend over half of the R & D budgets on software.
So, what is the outlook for the future? In five or ten years expert system overlays will link our Islands of Automation. A new generation of intelligent sensors will expand our control capabilities, improve system reliability and improve product quality . The man -machine interface will become more intuitive, more natural and more human. The next ten years should be challenging and rewarding. But, we dare not wait. Let us automate wisely on an island by island basis . We shallleam, as we eam new capital for future investments. REFERENCES Babb, M. (1989). Software, communications move into 1990s spotlight, Control.Engin~ering, January 1989, p.49 . Collins, R. P. (1989). GE-Fanuc disagrees with CE story, ContrQLEngineering, January 1989, p .21 . Cowan, J . c., Rihal , D. S., and Smylie, R. R. (1988). Electrical equipment at a modem seamless tube mill , Conference Record 1988 IEEE IAS Annual Meeting, pp 1181-1190. Cox, H. N. (1987) . Automation and operation of tandem cold rolling mills, Automation Control Technology Journal, 13 pp, People to People International, Spokane, WA. Demoro, H. W . (1988) . Embattled BART losing its General Manager, San Francisco Chronicle, October 25 , 1988. P 1. Fapiano, D. J. , and Steeper, D. E. (1985). Control of strip thickness in hot rolling, Iron and Steel Engineer, January, 1985, pp 34-43. Foulds, J. G., Mok, D. W. S., and Eaton, N. B. (1988) . Design of distributed thickness control systems for hot strip mills, Conference Record 1988 IEEE IAS Annual Mee!ing, pp 146-1152. IFAC MMM (1980). Proceedings of the IFAC 1980 Symposium on Automation in Minin-&.-Mineral and Metal Processin..,g, Pergamon Press.
Primary D.ta Input Slab Data . r------
I
Product Oata
A~~On~"C
I
I
__________________ . F_dbaeks G.ge~ Width, Temperature Force , Power ,
Roll Openi'lgS
l __~i~~~~_~~!:.o:~!.:~~::'______ J
r-------------------------j
..
:
------~ Preset
I Posll j~ n
Operator
Control
_
,
Feedbac k.s
L_~!~:.'~u.:o.:.!~o:~::.~~~ _________
!
. . . .----.:=i=;-:;-~~-~--:j-~-------------------! .. Manual Operator ContrOl
I I
r I I I
l ____ ~~~~~~~:o:~~__________ J I
Disturbances
Fig. 1. Functions are in a three level hierarchy: basic drive, basic automation, and process setup and control.
Control System Freeway (CSF)
Fig. 2. Computer arrangement for a fully automated hot strip mill.
;\pphillg Dislrii>lIled COIIl\lIlltT COlllrol 10 \IOdtTlli ~ t, Sliip Rollillg \Iill s
VAX Compute
I VAX Signal Server
DIU
I
Control System Freewav (CSF)
1
I
BIU
BIU
BIU
Drive Group
Series Six Signal Server
Operator Control Station
Control DMC
DMC
I
BIU
DMC Based Control Station
Field I/O
I
I/O
I
I BIU
Station
I/O
1/0
Series Six
I/O
I
I I
Drive
I Drive
I
1 Drive
J
Fig, 3, A truly distributed control system is conJigured to suit equipments . and plant layout.
5 REHEAT FURNACES
6 STAND RO UGHING :~ III
6 STAND
3
FINISHING
OOWH(OllERS
MIll
10 SCREWOOWNS
4 TABLES
4 SIDE GUIDES 6 .,.AIN DRIVES 3 ECGERS WIDTH GAUGE
12 TABLE SPRAYS wrDTH GAUGE
2 X-RAY GAUGES 12 SCREWOOWNS
2 TABLES
5 lOOPERS
7 SIOEGUIDES
6 KAJIi DRIVES
Fig. 4, Process schematic and basic drives for a continuous hot strip mill,
Finishing Cycle
11
Adjusting
Expected ROiling Time
Time
Pacing Tolerance
b.Tl
o
b.T2
b.T3
T3
Fig, 5, Finishing mill operating cycle is divided into three time increments. Computer control of aT3 can increase mill production up to 10%.