ADVANCED PROCESS CONTROL FOR ELECTRIC ARC FURNACES

CMP REPORT NO. 89-3 DECEMBER 1989

Prepared

Carnegie Mellon Research Institute Computer Engineering Center

4616 Henry SI. Pittsburgh, PA 15213-2683

Principal Investigator & Report Author

C. David Rogers

Investigator

Cheryl L. Cranier

Prepared foi

Center for Metals Production Carnegie Mellon Research Institute

4400 Fifth Avenue Pittsburgh, PA 15213-2683

Gary A. Walzer CMP Project Manager

LEGAL NOTICE

This report was prepared by the organization named below as an account for work sponsored by the

Center for Metals Production (CMP). Neither members of CMP, the organization named below, nor

any person acting on their behalf: (a) makes any warranty express or implied, with the respect to the

use of any information. apparatus, method, or process disclosed in this report or that such use may

not infringe privately owned rights, or (b) assumes any liabilities with respect to the use of, or for

damages resulting from the use of any information. apparatus. method. or process disclosed in this

report. __ ~~

Organizatioii that prepared this report: __

Carnegie Mellon Research Institute - Computer Engineering Center

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CMP PERSPECTIVE

Proiect Backmound Industrial process automation is an important aspect of current electric arc fumace (EAF) facility operations and many shops use computer systems to implement automation practices. These process control systems have made a major contribution to improved productivity and product quality. However, the degree of implementation of these systems appears to be highly variable throughout the industry. Also, wide choices available in computerized process control and current automation systems for electric fumaces add to the difficulty of determining which systems provide state-of-the-art technology.

Computer-based automation systems generally use technical models to calculate charge and refining requirements and to regulate power demand. However, steelmaking shop operations are subject to many poorly-defined constraints and disturbances that current automation systems do not comprehend.

Proiect Obiective A studv was undertaken to determine the state-of-the-art in automation svstems amlied to EAF steelmking and to determine the potential for applying recent developmknts in aiiomation technology, such as artificial intelligence and imaging techniques, to advance the state of electric fumace steelmaking. It is hoped that useful collaborative projects for advanced systems of interest to the steel industry will develop from this scoping work.

The state-of-the-art identified is based on findings from a comprehensive literature search, user surveys, site visits, and user and system supplier interviews. The process control system is sub- divided into six EAF process control areas. While the economic retum of investment in computerized process control may initially seem "nebulous", the long term payback in improved productivity and quality is real as evidenced in the report.

Opportunities for further development of process control equipment and techniques are identified in the areas of sensors, expert systems, and symbol usage (variable) standardization.

&@.j&

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ABSTRACT

The tecl~nical search, that i s the sabject of this report. was conducted by Mellon Institute -

Computer Engineering Center as t l ie first phase in a Center for Metals Production (CMP) Process ~

Control Program.

Process Control

deterniine areas in need of advanced process control development.

The purpose of this phase of the CMP program is to assess tlie current status of

for Electric Arc Furnace (EAF) sliops in North America and from this assessment __

The report that follows consolidates the current state-of-the-art in process control into representative

"core systems" and then discusses performance and limitations of these systems.

The state-of-the-art assessment was compiled on the basis of findings from an extensive literature

search, site visits, and user and systems supplier interviews. Because of limited response to a widely

distributed user survey form, assessment o f the state-of-the-art was restricted to prior mentioned

sources.

Generally i t was determined that application of state-of-the-art systems for the E M shops throughout

North America i s considerably behind that of overseas producers. During the study, a number of

factors surfaced that are likely contributors to this lag in technology:

1 . The nebulous economic return for EAF process control systems

2. A lack of user personnel, having degrees in process control systems, engineering that are available for assignment in the EAF areas

3. The wide range of available technologies and accompanying cost

4. The perceived more pressing needs for capital in EAF areas other than process control

The report provides conclusions and recommends development programs that would improve

performance of the EAF shop process controls. Some of the recommended programs are relatively

low cost and would significantly enhance domestic acceptance of state-of-the-art controls. Others are

longer-term programs that address improvements in EAF furnace arc controls, refinement models, and

EAF shop sensor systems.

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__

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ACKNOWLEDGMENTS

The report investigators wish particularly to acknowledge the helpful assistance from the following

people who contributed through their written work and/or meaningful discussion:

Norman Bliss, Milltech - HOH, Inc., Chicago, IL Kevin Duda, Florida Steel Corp., Tampa, FL

W. E. Dauksch, Nucor Steel, Darlington, SC Joe Goodwill, CMP, Pittsburgh, PA George Ghreichi.

North Star Steel, Corp., Monroe, MI Boris Hahn. ASEA, Sweden Todd Herd, Inland Steel, Corp.,

East Chicago, IL Dick Hurd, E & E, Corp., Bethlehem, PA Bob Jeffress, EPRI, Palo Alto, CA

Gregory Mason. Krupp Industries, Inc., Bridgeville, PA Ted McIntyre, Tekon Services, Whitby,

ONT Leo Jendra. USS Div of USX, South Chicago, IN George Moutafakis. North Star Steel Corp.,

Monroe, MI Jeff Musat. Timken Co., Canton, OH Max Pivik, Robicon Corp., Pittsburgh, PA Tom

Riley. LTV Steel Co.. East Chicago, IN Paul Sandaluk, Stelco Steel Div., Edmonton, Alb Lee

Schlabach. Robicon, Corp., Pittsburgh, PA David Schmauk, Macro Corp., Forsham, PA Bob Schmitt,

CMP. Pittsburgh, PA Dave Schroeder, Process Corp., Warrendale, PA Tom Schuerger, Penn State

Univ., McKeesport. PA Bill Schwabe, UHP International, Inc., East Amherst, NY Dave Simmons,

Lake Ontario Steel Co., Whitby, Ont. Ed Stockton, Robicon Corp., Pittsburgh, PA Gary Walzer,

CMP, Pittsburgh, PA Ted Williams, Purdue University, Purdue, IN

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The report investigator's wish further to acknowledge the helpful editorial comments received from

Dr. William M. Kaufnian, Dr. Ronald L. Krutz, and the CMP director and program managers:

J. Goodwill, R. Schmitt and G. Walzer. Last, and certainly not least, Donna Williams for her

patience i n puning the report into a proper format.

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ACKNOWLEDGMENTS

CMP acknowledges the efforts of Dave Rogers, Cheryl Cramer and Ron Krutz of the Mellon Institute Computer Engineering Center for preparing this report from a broad and diverse information base. We would also like to thank Mr. Tom Schuerger for his efforts in the initial stages of the project in developing its scope and focus, and identifying some of the more advanced EAF installations. Thanks also go to Prof. Ted Williams of Purdue University and Todd Herd of Inland Steel for their assistance in the initial literature search. CMP also appreciates the financial conmbution made to this project by the American Iron and Steel Institute. It is through all their efforts that this report was made possible.

...

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Table of Contents EXECUTIVE SUMMARY

1 INTRODUCTION 2 BACKGROUND 3 DEFINITION OF CORE SYSTEMS

3.1 Scrap Control 3.1. I Scrap Control Model 3 . I .2 Measurement Systems 3.1.3 Communications - Displays 3. I .4 Scrap Material Handling 3.1.5 Performance Characteristics of Scrap Control

3.2 EAF Electric Arc Process Control Core System 3.2.1 Host Algorithm - Electric Power Demand 3.2.2 Satellite Algorithm - Electric Arc Control 3.2.3 Regulator - Electrode Positioning Regulator 3.2.4 Actuator or Manipulator 3.2.5 Performance Characteristics of the EAF Electric Arc Control 3.2.6 Representative Options for Electric Arc Control:

3.3. I Overall Description 3.3.2 Options for EAF Refinement Models: 3.3.3 Performance. Characteristics of the Steelmaking Refinement Model

3.4 Secondary Steelmaking Process Control 3.4.1 Background

3.5 Secondary Steelmaking Electric Arc Control System 3.5.1 Host Algorithm - Electric Power Demand 3.5.2 Satellite Algorithm - Electric Arc Control 3 5 . 3 Regulator - Electrode Positioning Regulator 3.5.4 Actuator or Manipulator

3.3 EAF Steelmaking Refinement Model

3.6 Secondary Steelmaking Refinement Model 3.7 Overall Integrated Process Control System for EAF Shop

3.7.1 Background 3.7.2 Current State of the Art

4 COMMENTS ON INSTALLED STATE-OF-THE-ART EAF PROCESS CONTROL 5 CONCLUSIONS AND RECOMMENDATIONS 6 SUGGESTED DEVELOPMENT EFFORTS

6. I Currently Available Technology 6.2 Technology Available io Prototype Form 6.3 New Technologies 6.4 Technology Requiring Standardization andlor Guidelines 6.5 Sensors that Require Development

6.5.1 Scrap Area 6.5.2 Electric Arc Furnace Area

1. APPENDIX A

1-1 1-3 2-1 3-1 3-1 3-1 3-4 3-4 3-5 3-5 3-6 3-6 3-8 3-9 3-11 3-11 3-14 3-15 3-15 3-17 3-18 3-19 3-19 3-20 3-21 3-22 3-23 3-23 3-23 3-25 3-25 3-28 4-1 5-1 6-1 6-2 6-2 6-3 6-4 6-7 6-7 6-9 A - 1

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List of Figures

Figure I:

Figure 2: Figure 3: Figure 4: Figure 5: Figure 6: Figure 7: Figure 8: Figure 9: Figure 10:

Schematic Diagram Showing Developments in EAF Steelmaking and Improvements i n Energy Consumption, Melting Time, and Electrode Consumption Scrap Control Core System Core System EAF Electric Arc Control Example of Pre-established Energy Profile Core System Secondary Steelmaking Electric Arc Control Central Minicomputer Star Nehvork Approach LAN-Minicomputer with Star Nehvork Approach Distributed Minicomputer and Workstation Approach Electric Furnace Refinement Model Decomposed into Portable Subfunctions

Siniplified Representation of CASE Application

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3-2 3-7 3-10 3-21 3-26 3-27 3-29 6-5 6-6

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EXECUTIVE SUMMARY

In the past three decades we have witnessed, what may be generally termed, a ”cyclic” growth in

the application of process control throughout the steel industry. Simultaneously, the technology and

capability of steel industry processes have undergone significant changes. The steel processes that

once were very crude have been upgraded to highly productive processes that include the objective of

high quality. The modern steel processes now involve more rapid operations, yet require that precise

states be maintained in order to achieve the productivity and quality objectives necessary to remain

competitive in today’s market. Given this state of affairs, an effective steel mill operation requires the

use of computers and on-going advancements in process controls.

Most operations within the North American steel industry have recognized the need for, and

therefore, are applying modern process controls. However, the Electric Arc Furnace ( E M )

steelmaker has been hesitant to apply process controls throughout his shop and thereby realize the

many opportunities that remain. It is this consideration that motivates this current CMP Process

Control project and the development of this Phase I report.

The accompanying report was compiled on findings from a comprehensive literature search, site

visits, and user and systems supplier interviews, all conducted by Mellon Institute - Computer

Engineering Center.

I n order to maximize user input to the study, a user survey form was lo supplement the technical

search. The results from this survey were to convey user experience with installed sensor and

process controls. Most importantly, the survey was to provide measures of reliability of implemented

technology and to define the user process control needs, however only a few responses were received.

Nonetheless. the results from the other work conducted i n the technical search did raise a number

of concerns regarding current trends in applying process control in the EAF shop. For example; two

to three hundred thousand dollars ($200,000 to $300.000) has somehow become the magic number

for applying process control systems in the EAF shop environment. It was found that suppliers are

oriented to meeting this figure on a competitive level. In fact. some suppliers very willingly provide

complete “business-grade” Personal Computer (PC) hardware and software in the industrial EAF

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environment. Agreed, the business-grade process control system will provide capability for a high

degree of fttnctionality, birr application experiences are showing that this approach for process control

is plagued with problems in the areas of system reliability, .maintainability, expandability and network

communications, to mention a few.

The alternative is to spend the money on an industrial grade, intelligent, programmable logic control -.

(PLC) system (hardware. software and network) that includes a scrap charging model, steel refinement

model, etc. of reduced complexity. The alternative system would serve as a good foundation and

exhibit the system integrity (reliability, maintainability, etc.) required for the EAF shop. As additional

budget for system expansion becomes available, continue to expand the process control functionality

using industrial grade process control systems hardware, networking, and software.

This leads to the conclusion that in order to take advantage of advances in computer process

control, larger percentages of facility capital outlay must be allocated for hardware (systems and

sensors) and software. This is particularly true if the North American steelmaker is going to enjoy

continued profitable participation in today’s domestic and international marketplaces. It is well

publicized i n technical journals, reports of visits and other commentaries that foreign EAF shops are

generally better equipped with process controls than the domestic EAF shops.

The accoinpanying report first presents the results of the technical search in the form of six state-

of-the-art EAF process control areas. Subsequently, limitations in performance of these systems is

discussed. From this background, the future process control system needs are projected. The

conclusion of the report includes a list of recommended development projects for future consideration.

The report has been prepared as an informational guide and is not intended to be a detailed

accounting of either all process controls and sensors or all opportunities for process control

development. It is rather intended that this report will serve as a basis for expanding andlor

prioritizing those developn~ent areas that are vitally in need of programs in order to accelerate the use

of process control in North American EAF shops. The objective is to place these shops at the

leading edge of industrial competitiveness.

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INTRODUCTION

In the interest of defining the current status of process control for Electric Arc Furnace (EAF)

shops in North America, the Center for Metals Production of Mellon Institute, funded by the Electric

Power Research Institute and the American Iron and Steel Institute, contracted for Mellon Institute -

Computer Engineering Center (MICEC) to complete a technical search and consolidate the findings.

As a first step in the effort, the findings of a prior CMP contracted-for EAF process control

literature search was expanded to include current user and supplier information. (The preliminary

search was conducted by T. Herd, Inland Steel, T. J. Williams, Purdue University and

T. R. Schuerger. Pennsylvania State University.)

Once this expansion was completed, the results of the literature search, supplier and user interviews

and site visits were consolidated into generic state-of-the-art process control "core" systems. At the

same time, an indication was provided of the status and needs for process control within shops

throughout the North American steel industry.

From this overall assessment, a suggested list of development projects was compiled. This list

addresses needs for:

* expanding the use of state-of-the-art process control systems in EAF shops in North America and,

* conducting advanced studies to improve the performance of the available core systems.

The list may potentially form the basis for development programs keyed to demonstrate, for the North

American steel industry, EAF sbop performance improvements and cost effectiveness brought about by

modern vrocess controls.

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2

BACKGROUND

It has been repeatedly demonstrated that investment i n process improvements, including automation.

is providing EAF steelmakers with more stable operations, resulting in improved throughput and the

capability to produce higher quality steels. Generally, this improvement in stability of E M shop

operations translates directly to better utilization of electric power. As one EAF user has stated, "The

more we computerize, the more consistent we are."QJ

Productivity and stability of the EAF were included in the topics addressed in a recent CMPlEPRl

report, "Technoeconomic Assessment of Electric Steelmaking Through the Year 2000." 121 This repon

documents the wide range of both process and automation developments that has occurred in the EAF

segment of the steel industry. The report focuses on specific developments that occurred over the 20

year period from 1965 to 1985. Interestingly, the combination of these developments have led to an

overall performance improvement of at least 1M) percent in the operational aspects of the EAF

including:

* Tap-to-tap time

* Electricity consumption

* Electrode consumption

A family of curves was presented in the CMPlEPRI report and is also included as Figure I of this

report. The curves illustrate the performance benefits resulting from incremental improvements over

the 20 year time frame. If these curves were extrapolated into 1989. it would appear that the knee

of each curve has been passed and that further developments would therefore be beyond the point of

diminishing return. Significant

return is yet to be realized.

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This is not the case, however, in terms of advanced process control.

It is particularly important to note that about 90 percent of the developments listed in the

CMPlEPRI report, including state-of-the-art computer control, were implemented to realize throughput

(shorter tap-to-tap times) and stability improvements i n the overall EAF process. Experience has

shown that the more stable the process. the more opportunity there is for process control to achieve

the following:

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With the EAF process close to stability, providing decreased variability in the output product, the real

payoff remains to he realized. The time is right for the application of advanced process control

technology.

The above cited improvements in EAF shop processes have increased the need for state-of-the-art

and advanced process control as a result of the considerably reduced production cycle time.

Basically, the same number of operational events must be carried out, but within a significantly

shorter time frame. This leads to the situation described in a recent technical paper, where ”less

time is allocated for operator decision making, activities, andlor process observations” fi. Advanced

process controls are a cost effective means of increasing capabilities, providing automated monitoring

and, in cases, limited decision-making to assist the operator.

In general, the cumulative incremental cost for adding advanced process controls to achieve an

improved economic picture for the steel producer amounts to less than a few percent of capital. The

return from incremental enhancements in process control, improved market participation and the

capability to produce higher priced product will far outweigh the investment.

North American steelmakers have not been as quick as overseas producers to implement EAF

process control applications. There are a number of reasons for this including:

* the economic benefits brought about by tlie EAF process control system, including the degree of productivity improvement. decrease in energy usage per ton. bener quality, and lower maintenance, are not totally clear-cut and discernible from other EAF process technological improvements.

* the broad spectrum of technologies available, conihined with the wide range in process control system costs, makes it extremely difficult for the steelmaker to successfully identify the system that is best for his installation.

* rapid advancements i n process control technology can be confusing and also cloud tlie issue in identifying the proper system.

There is need for a methodology to bring short- and long- range planning for EAF shop process

controls into a focused perspective.

111 an effort to assist the steel industry i n utilizing advanced process control technologies to become

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more cost effective EAF steelmakers. CMP commissioned this current study. The study was intended

to accomplish two major tasks. The first task was to assess the current status of EAF shop process

controls in North America and. from this assessment, arrive at generic state-of-the-art representations

of the currently installed systems. The representations would include the various operational areas

within the EAF shop such as scrap processing. EAF refinement, secondary steelmaking, etc. The

second task would use these state-of-the-art representations to identify potential developmental studies

that would lead to EAF process control performance improvements. The identification of potential

developments was restricted to technology that is "generically" appropriate and of both immediate and

long-term interest to the EAF steelmaker. Thus, the project would serve as the needed focal point

for both short- and long-range planning for EAF shop process control.

This report is presented in four sections. The following lists each section with a brief description

of its content:

SECTION 3 - DEFINITION OF CORE SYSTEMS

* This section consolidates the results of the technical search into system modules or "core systenis" that are representative of the current state of the art in EAF process control. Also included are oplional extensions to the core systems, usually furnished by suppliers to enhance their competitive position. The purpose of this report is not to endorse any particular enhancement, but rather to typify the types of options that are available. The perforniance characteristics of each core system are examined.

* Six principle process control areas within the EAF shop are examined,:

1. Scrap Control

2. EAF Electric Arc Control

3. EAF Steelmaking Refinement Model

4. Secondary Steelmaking Electric Arc Control

5. Secondary Steelniaking Refinement Model

6. Overall Integrated Process Control System for EAF Shop

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SECTION 4 - COMMENTS ON INSTALLED STATEOF-THEART EAF PROCESS CONTROL

* This section discusses the current state and trends in E M shop process control from a computer engineering perspective. Particular emphasis is placed on small- to moderate- sized shops.

* A major problem encountered by such shops is the selection of the proper process control system to assure recovery of the investment and also satisfy the long-term requirements for system reliability, maintainability, and expandability. Additional concerns are raised when these potential users of process control technology become aware of:

I . the requirements to interface to other plant operations, business and specialized computer systems,

2. the relatively short life cycle of computer technology by comparison to other capital equipment,

3. the return on investment for the process control installation.

SECTION 5 - CONCLUSIONS AND RECOMMENDATIONS

* This section presents a discussion of the potential improvements in process control These improvements would impact technology identified within the scope of this project.

both short- and long-range EAF shop system performance.

SECTION 6 - SUGGESTED DEVELOPMENT EFFORTS

* In the interest of improving performance of process controls in the EAF shop, several developnlent efforts are suggested as programs . This section categorizes the developments by current state within each area of the EAF shop and describes the development efforts in an abbreviated form. It is anticipated that the EAF steelmakers would be polled to expand aiid modify this list and to set priorities that guarantee that the development projects will have beneficial objectives.

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3 DEFINITION OF CORE SYSTEMS

The definitions of the core systems are based on the findings from a comprehensive literature

search, site visits, user survey and interviews, and systenis supplier interviews. The ohjective of this

section is to consolidate the results of tliis technology search and to narrow the focus to include only

those technologies that have been determined to be immediately relevant to the direction in which

process control system design is moving. To the degree practical, specific references to literature and

technical brochures are cited within the text: however, the bibliography includes additional documents

that contain information pertinent to the project.

The core systems for EAF process control are configured as representative state-of-the-art systems.

This does not imply that the core systems described are the "best" systems nor that they are currently

implemented i n their entirely i n any one North American EAF shop. Once defined, the core systems

will be used as the basis for identifying areas for future developments and for modification andlor

enhancement of the technology being successfully applied in existing systems.

3.1 Scrap Control

The first core system discussed includes those operations associated with control of the scrap

As indicated in Figure 2, the core process control system for scrap control entering the EAF shop.

is partitioned into four function levels:

I . Scrap Control Model

2. Measurement Systems

3. Communications Display

4. Material Handling

3. I . 1 Scrap Control Model

As shown in Figure 2. scrap control is a supervisory function that is normally controlled by a

niodule within the overall EAF steel refinement model. In general. the model for selecting scrap

includes the steel grade specificatioii of the heat to he produced. the available additives, criteria for

packing the scrap charging buckets with an acceptable size distribution, and a performance description

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* EAF Steel Refinement Model

*-

SCRAP CONTROL OTHER MoDu_ : EAFMODEL

: FUNCTION5

tq- Weight

Chem Lab Analyses

MClSURMENT

SCRAP MATERIAL HANDLING FACILITY

Figure 2: Scrap Control Core System

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of the EAF. The model is used to determine the necessary combination of scrap and information is

displayed in the proper sequence for assembling the two or three scrap charging buckets for each

heat.

The fundamental input variables of the scrap selection process are the raw materials, anticipated

(historical) conversion energy, final properties required of the heat and additives. These variables are

nianipulated by the model in order to achieve the specification of the melt. The problem of

controlling and blending scrap is compounded, however, by large and rapid fluctuations in scrap

prices. An economic optimization of scrap selection must be an integral part of the comprehensive

scrap process control model. As a recent report has capably stated, "the cheapest scrap does not

necessarily lead to the lowest steelmaking c o s t . " a Constraints, including cost parameters such as

quality control, energy usage, process limits and refractory consumption @, are imposed on the input

variables to insure that the selected combination of scrap will lead to cost optimization of the heat.

A major element in scrap control is the grading of the raw materials. Variables associated with

scrap grading include:

1. supplier

2. chemical analysis

3. size. consist (density)

4. cost

5 . oxidation and moisture (water) content

6. oil content

7. residual elenients

8. type ( # I , #2, heavy melt - origin such as turnings. rail. wheels. autos. pipe, molds, etc.(note that type can also imply chemical analysis, oil, residuals. etc.)

9. historical information (if available, properties of final product, energy per ton to melt, yield, analysis confidence, density confidence, etc.)

The two characteristics that are of particular concern in EAF process control are the size of the scrap

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and residual elements in the scrap. Size segregation and pre-planned scrap packing are normally

utilized in the scrap manap len t process to improve arc stability in the EAF. Charging large scrap

to the EAF translates as a controllability problem in the electrode position control -algorithms.

however. this problem will be discussed at length in a later section. If there is high residual content

in scrap, on the other hand, process control. whether applied in the scrap yard or in the EAF shop

operations, cannot contribute significantly to improving the quality of the melt.

The problenis of scrap control are increased in the production of higher grade steels (other than

normal low carbon steels), where it is difficult to obtain a good correlation between the incoming

scrap, the EAF furnace performance and the grade specification. High variability between

characteristics of the incoming scrap and the more precise tap requirements, grade and steel

cleanliness becomes more of a concern in specialty steel operations.

3. I .2 Measurement Systems

Systems for measuring the characteristics of scrap to provide input variables to the scrap control

model are limited. This is due to the difficulty in obtaining representative samples for most scrap

types. The size consist, chemical analysis and residual element content are among the characteristics

that can vary widely within a given scrap pile or car. Some users audit scrap quality by testing

scrap samples in the chemical laboratory and by visual assessment. Portable spectrum analyzers are

also used; however. the size of the representative sample required for certain scrap types can become

unwieldy. Generally, scrap is supplied by an outside firm that assumes responsibility for the integrity

of the average size, cleanliness, chemical analysis, etc. of each load of scrap. The analyses of the

scrap quality, as furnished by the supplier and verified by spot testing, is normally used in place of

actual measurements as input to the refinement model.

3.1.3 Communications - Displays

In most installations, the crane operator is provided with the recommended loading sequence for the

type of scrap, rail car number (if appropriate). weight required, etc. This is acconlplished through

use of either a crane cab terminal, a “scoreboard” type display 122 in the scrap bay or an audio

contact via a phone/PA or other equipment.

Some installations utilize a scrap pulpit 181 equipped with appropriate CRT displays to indicate the

mix. The pulpit operators remotely control all scrap handling operations.

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3.1.4 Scrap Material Handling

A typical scrap yard may consist of piles of sorted scrap types or a siding of rail cars marshalled

according to the types of scrap required for the next eight hour turn. I n a typical scrap handling

operation, a scrap crane@) i s used to position and unload the ra i l cars into a scrap bucket. In some

scrap yards, crane scales are used, while in others a charging bucket scale or a weighed scrap bin

capable of dumping into charging buckets. i s used. The goal of the scrap material handling process

i s to pack the scrap buckets to insure uniform distribution of the scrap as the bucket empties into the

furnace.

I n some installations, the scrap bucket i s preheated by using the EAF furnace off-gas m. Preheating reduces the melting time, improving both the time to arc stability and furnace throughput

and also conserving energy. I n the Consteel process a conveyor i s used to transport scrap from the

scrap yard through a preheating section and to add the scrap lo the furnace in a continuous fashion

(10.11).

I n general, scrap material handling i s operationally straightforward. Automation i s not usually

applied: however, as noted previously, different approaches are used to utilize manpower effectively.

3. I .5 Performance Characteristics of Scrap Control

Effective performance of scrap operations is inhibited by poor knowledge of scrap composition.

Although it is generally accepted that improved knowledge of scrap composition i s needed. this i s

”difficult to obtain even with good management of scrap sources” m. To counter the difficulty

caused by the lack of a representative description, the same source suggested that “early sampling and

analysis of the liquid bath after an initial batch charge could allow adjustment of scrap feed in

subsequent charges” a. Following the suhsequent corrective charges and a resample of the liquid

bath. the scrap model would be solved using the new data.

The key element i n the effectiveness of the state-of-the-art scrap process control i s the collection and

application of historical data. Variabilily may be reduced through use of techniques such as Statistical

Process Control (SPC) that take into account variables as scrap composition. yield, melt energy

req 11 irenieii 1s. erc .

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3.2 EAF Electric Arc Process Control Core System

The second core system includes the control system directly associated with electric power (arc)

The two fundamental objectives of the electric arc process control control specifically for the EAF.

system are:

1. to operate in a manner that utilizes energy cost advantages from the electric utility.

2. to insure minimization of melt time by maintaining the arc length on each electrode or phase to ensure maximum power transfer into the melt. This would include minimization of circulating currents within the phases (phase imbalance).

The diagram in Figure 3 shows the overall electric power system partitioned into its four basic

functional components:

I . the host algorithm

2. the slave or satellite algorithm

3. the regulator

4. the final actuator or manipulator

3.2.1 Host Algorithm - Electric Power Demand

The host demand algorithm addresses the global aspects of electric power utilization for the arc

As indicated in Figure 3, this algoritliin applies at least the following two levels of furnace shop.

constraints:

1. The supplier of the primary power establishes graduated rates on the network as a function of the demand period (demand charge). If power usage exceeds the amount allocated by the supplier, depending on the time of day, extra rates are charged and this is reflected as a considerable increase in conversion costs. (Dollars per ton)

2. A typical steel plant has several operations that consume electric power within the plant electric power perimeter or network. The algorithm must take into account the power requirements of all necessary plant operations over the same interval of time that the EAF is operational (l4,15,16).

Output of the demand algorithm is normally inipleniented as an override to the energy setpoint for

the electric arc control that originates either from the operator or from a melt or steel refinement

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HOST ALGORlTHlM - DEMAND CONTROI

UTILITIES NETWORK

DEMAND CONTROL

1 .................... ~ ..... ~ ........ I

PLANT NETWORK

DEMAND CONTROL

1 SATELLITE ALGORITHM

SOLUTION FOR THE

ELECTRIC ARC EQUIVALENT

Resis. Source

REGULATOR

ELECTRODE POSITIONING

ALGORITHM

I ACTUATOR OR MANIPULATOR

ELECTRODE

POSITIONING MECHANISM

Figiire 3: Core System EAF Electi-ic Arc Coiitrol

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model. Implementation of the override may be as "soft" as a warning device for the operator or as

"hard" as an automatic setpoint change (with accompanying automatic change of the transformer taps

to a lower voltage) or the opening of a contact in the main breaker control circuit.

3.2.2 Satellite Algorithm - Electric Arc Control

The satellite algorithm is nornially the solution of an equivalent circuit for the electric arc. The

objective of this algorithm is lo solve for and provide as output the electrode positions (arc lengths)

that optimize the power factor as the heat progresses through the different stages and, thus, to

determine optimum power utilization for a heat. In the fully implemented satellite system, the energy

setpoint calculation includes the cumulative energy requirement for the current stage of the heat. To

determine this requirement, a detailed energy balance, that includes all heat added such as oxy-fuel

burners, scrap preheat, etc. and all heat loss such as cold scrap, off gas, cooling panels, etc., would

be solved. This energy balance would be an integral function within the EAF refinement model that

will be discussed later. The model would therefore provide, as a fundamental setpoint, the cumulative

energy requirement. Overrides lo this setpoint would include the host power demand, cooling panel

temperature limits, etc.

The satellite algorithm may reside in either a programmable controller that provides the regulator

setpoint 1111 or within the regulator itself m. The current trend is for regulators to provide

sufficient "intelligence" via microprocessors or single-board microcomputers to conduct the functions

associated with the satellite algorithm. It is thus becoming more difficult lo distinguish between the

satellite algorithm and the regulator functions.

Several approaches are being used as a satellite algorithm for controlling electric arc power transfer

into the melt. In all cases, the current and voltage for each phase of the secondary circuit are

monitored and are used to estimate the length of the arc on the basis of an arc impedance m, resistance 0. and/or a form factor computation associated with the waveform a. I n some

installations, a refractory-wear index (RI) approach is utilized 123.24.25). This approach involves

solving the equations i n real time for the equivalent circuits for each phase from the secondary of the

supply transformer. The square of the distance from the electrodes to the furnace side wall (square

law) and tlie measured voltages, currents. and power factor provide the necessary parameters to solve

for the length (or electrical resistance) of the arcs that will develop the best power transfer (power

factor) into the melt.

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A more recent approach conducts real-time analyses of the harmonics in the voltage and current

waveforms. As the harmonics approach a preset limit (the indication that unstahle operation i s

imminent), the setpoint to the electrode positioning regulator is held constant @. This assures that

the highest power factor (prior to arc instability) is maintained. The findings reported in a recent

Bureau of Mines study of furnace arc stability Q7J support this approach. The study concluded that

"Viewing the arc as a chaotic, deterministic system of discrete events, i t i s possible to evaluate

electrical waveforms and expect short-term precursors (half-cycle) to indicate the possibility of arc

disruption."

Another approach utilizes empirical methods based on historical performance @J. Overall melt

performance, as measured by the rise in furnace wall. temperature and the rate of electrode

stabilization, i s monitored through specific stages of furnace operation. The resulting profiles chart

preferred energy versus stage of melt. These event-actuated profiles provide the control signal to .the

operator for manual changes of transformer taps and the setpoint signal to the electrode positioning

regulator. A typical energy profile i s shown in Figure 4.

I n a related approach, feedback from the operation of the melt in progress is used to niodifj the

energy profile. This approach recognizes that disturbances, including incorrect slag level, changes in

fume loss, length of oxy-fuel burn time, etc. m, impact power transfer into the melt and affect the

overall power profile (or trajectory). As significant disturbances occur. therefore, the profile i s

adapted to compensate for the changes that are occurring.

3.2.3 Regulator - Electrode Positioning Regulalor

Regulators are applied to convert the electric arc positioning setpoints of each phase to an output

signal for the electrode positioner (actuator or manipulator). Within the regulators are algorithms or

circuitry to compare the input setpoint signal from the satellite controller and the feedback signal from

l l ie electrode positioner. As a result of an analysis of the error (usually via a PID digital algoritlini

or analog circuit). an appropriate output signal i s sent to the positioner. Simple regulators are limited

to accepting a fixed, event-actuated profile for controlling operations during the boredown and the

subsequent melting stages. More complex regulators incorporate other control signals (such as

overrides and l imits) into the conversion algorithm. As indicated previously, l l ie trend is for electrode

positioning regulators to have sufficient "intelligence" to be able to perform the functions of the

satellite algorithm,

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Program Transformer Power Stage Tap Setting Setting (MW)

1

2

3

4

5

6

7

8

9

20

24

26

32

34

33

30

26

24

24

26

30

32

32

34

30

28

22

20 ' * 1 2 3 4 5 6 7 8 9

Melt Stage (Step)

Figure 4: Example of Pre-established Energy Profile

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Other regulators are, by comparison, simpler. These regulators are limited to the capability to

accept a given event actuated profile for controlling operations during the bredown and for the

melting stages.

A regulator normally includes the interface for delivering the output signal that controls the tap

changing of the incoming power transformer and, in some cases, regulators also include an algorithm

for generating the signal. The algorithm is typically designed to conduct transformer tap changing as

a function of the stage of the melt. During the early boredown stage, the tap setting is normally low

to minimize the effect of disturbances. As the melt proceeds, the tap change advances with each

additional bucket of scrap until the liquid stage is reached.

3.2.4 Actuator or Manipulator

Actuators are used in electric arc control for manipulating the position of the electrodes individually

andlor for changing the taps on the incoming power transformer. Electrode positioning is

accomplished by either an electric motorlpulley arrangement or an electrohydraulic drive consisting of

an AC motor and a variable speed DC motor driving hydraulic oil pumps supplying a hydraulic

cylinder. Feedback signal(s) to the regulator's positioning circuit are provided by either a position

sensor installed on the electrode mast@) &9) or an inferential measurement of the electrode position.

The current trend is toward high speed electrohydraulic cylinders with servovalve control on each

electrode mast. The maximum speed for electrode positioning, however, is governed by mechanical

limitations.

The actuator for power source transformer tap changing is normally an electric motor or a selsyn.

In the case of an open loop electric drive, tap position is determined by checking the secondary

voltage or a tap associated interlock.

3.2.5 Performance Characteristics of the EAF Electric Arc Control

Were i t not for the massive excursions in power due to the electric arc intercepting the furnace

walls, the "high points" in a coarse scrap burden, and random scrap cave-ins. the equivalent series

resistance and inductive reactance circuit that is developed for each phase would be straightforward. A

representative average current could be easily measured by a conventional transducer and the regulator

could position the electrodes (arc length) to maintain a consistent power transfer into the melt (power

factor).

3-11

Control of the electric arc is not so simple, however. The lack of arc stability during initial stages

of the melt (boredown and additions of coarse scrap) causes strong load swings and depresses the

level of power. This slows tlie melting process QlJ and translates directly to loss in production

throughput.

The large excursions in arc current, analogous to multiple and random short circuits in parallel

The following two significant with the equivalent circuit, cause severe harmonics in the waveforms.

effects result:

* Severe harmonic distortion is present within each half cycle of the current and/or voltage waveforms, making it very difficult to determine the average current (which is the controlled variable in the electrode position control loop).

* The change in arc circuit impedance is reflected back through the transformer into the primary power network.

Altliongh these two effects interact and thus lead to formidable problems in process control of the

electric arc circuit, the discussion that follows will treat each effect separately.

I . Improvement in Controllability of the Electric Arc Circuit

Process control of the electric arc circuit is extremely difficult since the response time (bandwidth) of the manipulated variable (electrode positioner) is very slow by coniparison to the variations that occur in tlie measured variables (arc current and voltage per phase). Despite the addition of higher speed electrode positioners, the large masses involved on each phase will always limit the capability of the system to compensate for short term (high frequency) disturbances in power caused by arc instability. This has led to a search for algorithmic rather than mechanical solutions (although rapid electrode motion is always advantageous for disturbances such as cave-ins, programmed arc striking, positioning for boredown, etc.).

Because of the comparatively low bandwidth of the electrode positioner control loop, the measured values (arc current and voltage per phase) used for determining the control variable (arc length) in the arc control loop are averaged values. In the presence of high frequency changes in harnlonic distortion. determination of a precise average from the typical power (current and voltage or potential) sensors applying rectification is unlikely. An approach being used to overcome this limitation is to utilize a sensor or circuit without rectification that has the capability to conduct the equivalent of a Fast Fourier analysis of the harmonics within the signal. A more precise average can be determined for use as the control variable for the arc control loop. A liniited implementation of this approach is being furnished by a supplier whose regulators use a "waveform analysis"

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approach to obtain a more representative average current andlor voltage in the electric arc control loop Q2J.

Despite these alternative solutions, the response capability of the regulator loop (including the actuator) remains slow by comparison to the rapid changes that occur i n the impedance of the electric arc circuit. As a result, several operating practices have focused 011 mininiizing the high frequency impedance changes brought about by arc instability. The following alternative practices have been suggested 1211:

a. I f metallurgically acceptable, operate with a foamy slag to confine the arc to the electrode face and the immediate vicinity of the bath.

b. Shroud the electrodelbath arc with a gas to constrain the path between the electrode and the bath or supply a gas in the immediate vicinity o f the arc that wil l promote ionization in the arc path from the electrode to the‘ bath.

c. Operate with a hot heel to reduce the incidence o f “high spots” in the scrap burden.

d. Determine a method to reduce the circuit inductance within the electrical circuit o f the secondary power transformer.

e. Use preheated scrap in order to reduce the time from solid scrap to liquid bath.

The success of these efforts to physically andlor metallurgically diminish high frequency disturbances will result in fewer harmonics within the current and voltage signals. The cleaner signals wil l resemble more closely the signals originally supplied by the primary source power and will permit more precise determination of arc impedances and more stable control o f the arc. Attention can then be focused on controlling low frequency disturbances.

2. Reduction of the Effects of Reflected Impedance Changes into the Primary Netwoft

Due to the action of the electric arc. rapid and significant changes occur in load impedance at the secondary of the transformer. These impedance changes are. effectively. reflected back into the supplier network at the primary of the transformer. Introduction of large excursions in inductive reactance into the primary network will cause phase distortion and, as a consequence, produce undesirable effects for other electric power customers on the network. Depending on the stage of the melt, testing has determined that the second through the fifth harmonics are present. To reduce adverse effects on the network, series resistancelcapacitance filters, having the appropriate time constants. (static var compensators) are sometimes added to the primary of the transformer.

Disturbances on the primary network are becoming of greater concern with the introduction of more andlor larger EAF steelmaking installations. ”Flicker” monitoring is

3-13

being used to provide a relative measure of the disturbances on the primary network. This measure is then used as feedback to improve the performance of the network 0. Flicker monitoring also indirectly measures the effectiveness of the process control system. As was the case with environmental restrictions that were imposed once reliable and repeatable measurement devices became readily available, there is potential that government and utility standards for "flicker" will eventually appear. If so, considerably more focus will be placed on controllability of the electric arc.

To insure efficient utilization of electric power in the EAF, process control of the two functional

units, the electric arc (transformer secondary) circuit and the supply network (transformer primary)

circuit, must be implemented in an integrated manner. Because of the interaction between both

circuits, controllability improvements in either circuit will impact performance of both circuits. For

example, an incremental improvement i n the satellite algorithm providing longer periods of electric arc

stability (improvement in the electric arc circuit) would also be reflected as an improvement in power

utilization in the supply network circuit. In addition, such an improvement would decrease the need

for line compensation and thus reduce maintenance costs for the E M operator and the electric utility

company

3.2.6 Representative Options for Electric Arc Control:

* Power Demand:

- An algorithm that takes into account. in real time, the rate of change in plant and EAF power usage over time and predicts future energy requirements. Using this algorithm, heats can be started and run to con~pletion without interruption and the cost penalties imposed by power companies for exceeding the demand limitation can be avoided.

- In order to ensure that the power allocated by the supplier is used in an optimal manner, a scheduling or predictive algorithm applying linear programming or a similar technique is sometimes implemented (36.37.38). This algorithm allows advanced scheduling of all plant operations (EAF, ladle and reheat metallurgy stations, casting, rolling, reheating. etc.) to utilize electric energy i n the most cost effective manner.

* Regulators:

- Overrides to handle exceptional conditions. For example. a pressure sensor (for electrohydraulic actuators) or s o h a r e that compares electrode position to the position setpoilit to detect a stall condition in forward positioning and to signal withdrawal of the electrodes.

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- Programmed position slow-down andlor speed-up to insure that motion of the electrodes prior to and during arc ignition with the bath and withdrawal from the bath region occurs at the preferred rates m.

- Cave-in detection with maximum speed of electrode withdrawal a. - Application of an algorithm to analyze the temperature rise of groups of water cooled

panels during boredown. I f the rate of temperature rise of the panels in tlie vicinity of an electrode exceeds a preset limit, the rate of power input i s overridden for that electrode a.

3.3 EAF Steelmaking Refinement Model

3.3. I Overall Description

Among the many advantages provided by EAF steelmaking refinement models, two stand out for

special mention:

1. The operating practice is made more consistent. The same set of analytical equations is used to determine scrap input (size, cleanliness, consistency, chemistry, etc.), additives, electric energy input, and other inputs necessary to produce any grade of steel desired. Since the operator's "black book" can only consider a limited number of discrete cases and cannot deal with all possible input perturbations, the refinement model provides a higher degree of flexibility and greatly reduces or eliminates a potential source of product and process variability.

2. Temperature and chemistry are determined analytically. Therefore, inaccuracies may be systematically reduced by observing the historical performance of the model and by applying statistical methods to adapt the constants in the model by a defined and repeatable methodology.

Most process control models for EAF steel refinement are static models having a first principles

model foundation. Static mass, chemical, and energy balances are solved incrementally as the furnace

proceeds through the various stages of the me11 to determine the operating parameters for the EAF.

These balances are fundamentally textbook equations that therniochemically relate:

* the mass. composition, cleanliness. size (packing) and quantity of input scrap,

* tlie quantity and cheniistry of the additives.

* the amount of energy added and removed.

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* and the amount removed by deoxidation,

to obfain interniedinte aiid tap clieniical conipositions and/or temperatures of the Iient. Adaptive

constants used within the equations for each balance are derived empirically to make the model fit the

specific EAF operation, characteristics of the additives and raw materials, etc.

With the exception of tuning constants and/or relationships, the fundamental technology applied in

all first principles models used in steel refinement is the same. Models furnished by various

suppliers normally differ in the details of input materials, additives, and use of the output variables.

Further differences include the manner in which the input variables are entered (automatically or

manually) and how the output variables are displayed (operatorlmachine interfaces).

Because steel refinement models for E M operation typically contain five interdependent internal

functions, the overall core EAE refinement model will be partitioned into the five following functions

(functions over and above the core model are considered "Options" and will be discussed later):

1. Energy (Heat) Balance:

* An energy balance around the furnace to determine the energy requirements for This function works in conjunction with the various stages of the melt 0.

electric power control system to provide the cumulative energy setpoint.

* The energy balance includes as variables the following sources and sinks of heat transfer:

a. heat of reaction

b. gain from hot scrap

c. wall and roof cooling

d. loss to cold scrap

e. loss to slag and additions

f. loss to furnace off-gas

g. electrical power

h. oxy-fuel burners (if used)

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2. Bath MasslChemistry

* Balance of all cheniical ingredients of the steel bath, including incoming scrap, additives, oxygen, and refractory wear and losses into slag and off-gas.

3. Slag MasslCheniistry

* Balance of all chemical ingredients of the slag, including gain from steel bath, additives, scrap, refractory wear, and oxygen.

4. Scrap MasslChemistry

* Determines by weight the composition of input scraps of various types for use in the metallurgical chemical balances.

5 . Energy and Trim Calculation

* On the basis of the solution for the above functions, the amount of additional energy or the quantity of additives required is determined and can be used to guide the operator. The computed energy requirements may be easily provided as a setpoint for the satellite algorithm for the electric arc power control.

Process control models for steel refinement are key elements in the development and consistent

implementation of a wide range of melting practices. For example, the focus of a recent CMP

project was to define the repeatable heating cycle necessary to achieve low nitrogen from the EAF

pg.

In addition to providing improvements in EAF operational consistency, steel refinement models are

becoming increasingly important as predictors of future events. As the EAF cycle time decreases,

timing and preparation for action are required to maintain high rates of productivity, but events are

often occurring tcm rapidly for the operator to make decisions and implement the appropriate action.

Steel refinement models can be instrumental i n providing the operator with a display of events that

will be happening "soon," as well as directing action for events that must happen "now" m. 3.3.2 Options for EAF Refinement Models:

The basic objective of the core refinement model is lo solve for the parameters necessary to

S o h a r e to perform functions

In the case of the options listed below,

produce a heat of steel having a specific composition and temperature.

beyond this objective is considered an option or add-on.

however. the options are as important as the basic refinement model.

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* Least Cost Additive Optimization: In this option, various constraints and parameters are defined and used to determine the combination of additives that will achieve optimum cost. 'Cost' i n this case may include properties of the finished product, minimum heat time. cost of additives, and other performance criteria that are associated with process and product.

* Statistical Analysis Packages: These packages perform analysis of real-time andlor historical process variables using Statistical Process Control (SPC) methods. Functions embedded in a typical optional package include trending, adaptive control (adjustment of constants for adapting the model), statistical analysis in SPC quality analysis terms, and reporting. The packages are normally supplied with a user-friendly interface to provide optional selection of the variables to be analyzed andlor displayed.

3.3.3 Performance Characteristics of the Steelmaking Refinement Model

Because the models are static rather than kinetic, they do not precisely account for phase transitions

that occur in real time during the intermediate stages of the melt, particularly in the slag model.

The adaptive constants must be adjusted to compensate for the rate at which reaction has occurred

between incremental solutions of the model. 111 addition, the models must be retuned every time

there is a change in additive characteristics or process equipment or enhancement with new process

technology.

In general, process control niodels for steel refinement are not overly complicated, although a

degree of complexity is usually associated with obtaining representative samples of scrap, off-gases,

slag, and bath. Complexity is also associated with need to obtain reliable measurements of

temperatures, weights, gas volumes (flow rate) and other important variables. Unfortunately, many

steel refinement variables cannot be sensed directly but must be estimated or inferred. The inability

to conduct measurements restricts model accuracy and increases the need for constant retuning of the

model. A recent AIS1 program has focused on continuous analysis of the molten steel bath, but

considerable development effort remains to bring continuous measurement into practical reality.

Interest has also been focused recently 011 the need for adequate characterization of the EAF off-gas.

The real-time effect of the oxygen-fuel burners. and their placement, and the potential of iron oxide

removal with scrap preheating both offer considerable motivation for fully characterizing and modeling

off-gas.

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3.4 Secondary Steelmaking Process Control

3.4.1 Background

There is continuing growth in the application of secondary steelmaking facilities in EAF shops.

Process control of the secondary steelmaking process represents a significant opportunity Io bring each

melt to specified chemistry and quality. This segment of process control is as important, if not more

so, as any other process control system within the EAF shop environment for four fundamental

reasons:

1 . The capability to refine in the ladle is reflected as a direct increase of EAF shop throughput. The EAF is used as the nielter and the secondary steelmaking facility is applied as the refiner. Throughput increases are projected to be as high as 30 percent with the addition of secondary steelmaking. This increase is due to shorter tap-to-tap times at the EM.

2 . With the exception of additions made to the tundish or casting mold and ingot mold, secondary steelmaking operations provide the last opportunity to refine the steel in order to achieve the target chemistry and properties in the hot state.

3. Secondary steelmaking operations can reduce or fully compensate for variability in the heat cheniistry introduced by the variations in composition of the incoming scrap.

4. The capability to reheat the steel provides a buffer for synchronizing upstream and downstream operations m.

The third reason is of particular importance. Applying process control to secondary steelmaking

operations to compensate for variations in the incoming scrap and to produce a variety of tap

chemistries and temperatures reduces the need to control a large number of scrap blends in the EAE.

In a sense, the objective for operating the EAF is reoriented to produce heats that are metallurgically

“vanilla:” the heats are then “flavored” for the correct chemistry and properties at the secondary

steelmaking facility. This in turn reduces the types of scrap required. significantly impacting the cost

of scrap processing. The energy cycle at the EAF becomes more clearly defined. increasing llie

opportunities lo utilize pre-programmed. repeatable melt cycles and leading to more consistent

operation and effective energy utilization. Although sonie of the savings would be offset by the cost

of additives. capitalization of additional equipment. etc.. the additional (secondary steelmaking) facilities

would facilitate increased productivily concurrent with the capability to produce a more extensive

product niix that includes llie more profitable steel coniposilions.

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Implementation of process control scheduling algorithms increases the usefulness of the secondary

steelmaking process as a buffer in the overall steelmaking operation. For example, use of a

continuous caster requires that batches be scheduled to provide a continuous flow of material to the

caster. Scheduling algorithms can insure that the steel arrives at the proper alloyed state and transfer

temperature at the required transfer time. I f necessary, ladles of steel can be held andlor rotated for

reheat to compensate for problematic delays downstreani from the secondary steelmaking operation.

Secondary steelmaking is a more stable process than the EAF. Thus, there is more of an

opportunity to conduct precise process control of energy utilization, to obtain representative process

measurements, and to synchronize both EAF and secondary steelmaking operations with the

requirements of the downstream process (particularly in the case of the continuous caster).

The overall process of secondary steelmaking can be composed of any combination o f a number of

subprocesses, and as a result, there are a variety of installation types. For the purposes of this

project. therefore, secondary steelmaking wil l be considered as a single process entity, and the core

system defined below wil l provide control of all secondary steelmaking conversion processes, including

ladle trim or metallurgy, degassing, heating and reheating and stirring. The components of the

secondary steelniaking core system will be defined in the same sequence as the EAF core system,

3.5 Secondary Steelmaking Electric Arc Control System

As shown in Figure 5, the core system functions of secondary steelniaking arc control are arranged

identical to those o f the EM. Because the secondary steelmaking operation requires less power than

the EAF, however, the host algorithm functions as a subset of the EAF power demand. I n addicion.

fewer input variables are required for arc control due to improved arc stability in the secondary

steelmaking operation. The core system for secondary steelmaking electric arc control includes the

following:

I. Subfunction of the Electric Power Demand (Host Algorithm)

2. Satellite Algorithm for Electric Arc Control

3. Electrode Position Regulator

4. Actuator 61' Manipulator

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HOST ALGORITHIM - DEMAND CONTROL

UTILITIES NETWORK

DEMAND CONTROL

.................................... I'

PLANT NETWORK

DEMAND CONTROL

1 SATELLITE ALGORITHM

SOLUTION FOR THE

ELECTRIC ARC EQUIVALENT

Line

Transformer

REGULATOR

ELECTRODE POSITIONING

ALGORITHM

ACTUATOR OR MANIPULATOR

r -

ELECTRODE

POSITIONING MECHANISM

Figure 5: Core System Secondary Sleelliiaking Electric Arc Control

3-21

3.5.1 Host Algorithm - Electric Power Demand

As a consiimer on the plant electric power network, tl ie secondary steelmaking process affects the

overall power demand. Normally, the host algorithm for power demand control i s associated with the

EAF since i t is the major consumer of electric power in the shop. The host algorithm was discussed

under Section 3.2.1 of the report. Subfunctions within the EAF power demand algorithm provide

control of tlie electric power for the secondary steelmaking process(s).

The host algorithm contains the necessary real-time and/or predictive functions io provide a

shutdown or cutback override to the secondary steelmaking satellite algorithm. An example of an

override might be a warning or display i n the operator pulpit calling for a reduction in the

transformer tap setting.

3.5.2 Satellite Algorithm - Electric Arc Control

Electric arc control i n the secondary steelmaking process is similar to the EAF process, but the

complexity of the algorithm i s greatly reduced. This i s the result of

I . greater arc stability due to lack of arc path interference to the furnace walls and roof, the absence of incoming coarse scrap and scrap cave-ins

2. the ability to conduct interim slag height measurements

A satellite algorithm for control of the arc is normally required because of the movement in bath

surface due to stirring (gas bubbling and electromagnetic stirring) and electromagnetic effects caused

by the arc current m. The satellite algorithm solves the equations for the equivalent electric circuit

in tlie secondary of the supply transformer. In general, the arc impedance or resistance is

determined and maintained constant by varying the, arc length. Initial and interim measurements of

ladle slag depth are sometimes used to calibrate the relationship between arc resistance and the

required arc length from the electrodes to the bath.

The satellite algorithm is sometimes implemented within a PLC that i s interfaced to analog circuitry

of the electrode positioning regulator. I n more recent regulators. the satellite algorithm i s

incorporated into a microprocessor that i s supplied as ai l integral part of the regulator. The power

factor and arc resistance changes in the equivalent electrical circuit are computed based on the input

from current sensors (per phase) and sampling of the secondary voltage. In st i l l another application.

3-22

the functions of the satellite algorithm for arc positioning are performed by a computer that provides

process control of all phases of the ladle steelmaking.

3.5.3 Regulator - Electrode Positioning Regulator

As wilh the EAF arc control system, secondary steelmaking regulalors are applied to convert the

electric arc positioning setpoints of each phase to an output signal for the electrode positioner

(actuator or manipulator). The regulators contain algorithms or circuitry to compare the input

setpoint signal to the feedback signal from the positioner to derive an appropriate output signal to be

sent to the positioner. This output signal may also reflect any overrides andlor limits that have

occurred. As noted in the section above, some regulators have sufficient "intelligence" to perform the

functions of the satellite algorithm.

A regulator normally includes the interface, and sometimes the complete algorithm, for sending an

output signal to conduct the tap changing of the incoming power transformer. This algorithm is

programmed on the basis of the stage of the refinement or reheating requirements.

3.5 .4 Actuator or Manipulator

The actuator, manipulator, and device for remote tap changing of the power transformer, are

(The actuator section relating to Electric functionally identical with those described in Section 3.2.4.

Arc Control.)

3.6 Secondary Steelmaking Refinement Model

Secondary steelmaking refinement involves a number of sequential steps, normally referred to as a

profile. The profile may vary depending on lhe specific type of facility involved and the type of

refinement that is to be conducted 0. To examine all process control for all types of secondary

steelmaking would be an extensive undertaking beyond the scope of the current project. In the

developnient of the core system, therefore. only a few of the more representative steps will be

addressed:

I . argon bubbling

2. f lux addition

3. aluminum addition

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4. initial heating

5 . secondary heating

6. argon stirring

7. desulpliurization

8. alloy addition trim

With the exception of initial heating and secondary heating, these actions are single event-actuated

changes in state. The initial and secondary heating, however, are time versus temperature profiles

calculated to add a prescribed amount of heat or electric energy to the ladle over a specified period of

time. In most cases, a set of thermochemical balances is used to determine the amount of energy

needed to remove the remaining impurities and to conduct the necessary alloying of elements. These

equations are derived from the fundamental first principle mass, thermochemical. and energy balances.

As with the EAF refinement model, the constants are derived empirically to fit the specific operation.

Normally, all alloy additions are conducted through the use of automatic bin feeders and weigh

conveyers andlor the use of wire feeders. In one installation applying computer-based automation of

alloy additions, the time required for additions was reduced to seven minutes from the original twenty

to twenty-five minutes m.

The rate at which energy is added to the secondary steelmaking process is normally a function of

two constraints:

1. the final temperature required to complete the desulphurization

2. the availability of the downstream process (continuous caster or teeming crane)

Within bounds, therefore. the secondary steelmaking operation may be conveniently applied as a

temporary buffer to adjust productivily to match the EAF with the continuous caster or other

downstreani operations.

The energy profile calculated by the secondary steelmaking model is applied as the setpoint for the

satellite algorithm, or alternatively. the regulator. Length of the arc and tap setting of the

transformer are regulated to satisfy the required energy level over time.

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The stability of the secondary steelmaking process leads to very efficient process control and thus

the opportunity to reduce variability in the prodiict prior to cnsting.

3.7 Overall Integrated Process Control System for EAF Shop

3.7.1 Background

Until recently, EAF shop process control systems were integrated using one or more large centrally

located minicomputers 0. These central minicomputers handled the overall productionlprmss

control tasks including the refinement model, tracking, data base management, communications

management, and similar "high level" functions. As shown in Figure 6, the large minicomputers

applied "star" networks that provided separate wiring to each' individual CRT, hard-copy terminal or

other device having an 32-pin connector.

Stelco Steel, Inc.. Edmonton Works, Edmonton, Alberta, Canada is a typical application of the star

configuration.

As a result of the introduction of high data rate network hardware and software protocols, a new

configuration evolved, based on a network of host minicomputers and satellite process control

niiniconiputers and terminal servers (Figure 7). The satellite minicomputers contain the functions

associated with real-time process control algorithms, status and alarms. The displays associated with

the satellites are large, color graphics monitors equipped with speed key screen selection. Scrap,

EAF, and/or secondary steelmaking pulpits are usually equipped with two types of CRT terminals: the

conventional monochromaticlalphanumeric and the color graphics terminals.

The monochomaticlalphanunieric CRT terminals are interfaced via terminal servers to the host

minicomputer. A forms management routine is usually employed as an operator interface, resulting

in a fill-in-the-blanks approach. Thus. EAF shop operators could easily communicate with and apply

the most highly complex steel refinement models in existence. Additional terminals, supported by

terminal servers and networked to the main minicomputers. provide the necessary communication with

the process control computers for quality assurance, chemistry lab. operating management, and others.

Because of the high electrical noise levels. these networks require a protected environment. and long

indi\,idual current loops must be used to connect terminals to the servers.

3-25

Host

Minicomputers

I

n..

Graphics

Hiway mgr

Hiway Hiway CRT Terminals

PLCs. Sensors PLCs. Sensors

Figure 6 : Ceiilral Minicomputer Star Network Approach

3-26

Production/Business Systems Mainframe or Minicomputer

---?--- Gateway Q

I I U :Local Area Network

n n

Color Graphics

Satel l i te

I

Hiway

Satel l i te Terminal

I Hiway mgr

PLC Hiway

y10-0/ PLCs, Sensors PLCs, Sensors

CRT Terminals

(Other users)

Figure 7: LAN-Minicomputer with Star Network Approach

3-27

This approach was applied at Timken's Faircrest Plant in Canton, Ohio and also at Babcock and

Wilcox's EAF Shop i n Koppel, Pennsylvania.

The satellite computer i n each area supports the color graphics monitor in the pulpit. This monitor

normally displays a graphic layout of the process with variables, alarm indications. etc. superimposed

on the display. Speed keys enable the operator lo page through the process graphs to specific areas,

such as EAF furnace, power demand, controller and indicator faceplates, utilities areas, etc.

3.7.2 Current State of the Art

As computer hardware technology continues to advance, the trend is shifting lo more powerful area

computers that are applied distributively. As shown in (Figure 8). the current state-of-the-art

computer configuration for the EAF shop is typically a distributed control system that applies

functions, although not necessarily hardware, in a hierarchical/distributed fashion. Local functions are

consolidated and the functionality of satellite computers is expanded. This type of configuration

reduces or eliminates the levels of hardware between the production and/or business computer(s) and

the process control computers.

A key element leading to the change in process control system architecture has been the

introduction of networks capable of high speed transactions and transfer of information between the

area minicomputers. Because of the improvement in hardware and the development of accompanying

software protocols. the networks may be physically located within the EAF shop. A single cable loop

may be used to provide multiple interconnections between several computers. An EAF shop may thus

apply a ruggedized version of coaxial cable for a network and achieve sufficient immunity from

electrical noise plJ.

The network, in combination with area computers that are powerful, physically small, and have

mainframe capability, has led to marked changes in process control configurations. These

configurations permit operators to interact. i n real time. with functions resident in any computer on

the network.

The configuration of the EAF shop process control coniputer installation at North Star Steel in

Monroe. Michigan approaches the hierarcliical/distributed approach. The North Star approach is

somewhat unique since it applies ethernet over ruggedized coaxial cable in the EAF environment.

3-28

bvorkstation I Quai. Assur L - 4

ProductionlBusiness Systems Mainframe or Minicomputer

Gateway

I - Y U

n n n

Graphics Graphics

Terminal Server

Hiway mgr

H"BI-1 CRT Terminals (Other users)

PLCs, Sensors PLCs. Sensors

Figure 8: Distrihuted Minicoinputer and Workstatioa Aliproach

3-29

Because of the increase in computing power and the reduction in physical size of minicomputers,

increased intelligence of Progrnmniable Logic Controllers (PLCs) and the increased capability of

networks, process control systems are in the midst of a major transition i n technology. Complex

process control models are being executed by the operator's hardware associated with the local area.

At the same time, operators also have access to programs or software processes that execute on other

computers on the network. This transition has changed the visualization of the operatorhachine

interface (OMI) from one or more CRTs to a single "Workstation" 0. One part of the

Workstation approach is the introduclion of larger color monitors capable of "windowing" more than

one display or process onto a single screen within the pulpit. The screen may be subdivided into

both color graphics and alphanumeric windows, and the Workstation interface to the large color

monitor contains functions to enable the operator to view activities within his immediate responsibility,

as well as functions to provide simultaneous display of peer downstream and peer upstream operations.

The information can aid the operator to make rapid decisions about the local process and also to

adjust the local process to better suit the overall EAF shop operation.

Although not applied in an EAF shop, a computer configuration that is very close to that described

here is installed and operational in the LTV Secondary Steelmaking facilities at East Chicago, IL.

Parallel metallurgy stations are used with two separate Workstation-based consoles. The operator at

each console may easily observe his, as well as the parallel process.

The term "Workstation" is not to be confused with the Personal Computer (PC). Workstation, in

the industrial sense, denotes an industrial-grade computer (including memory and ancillary hardware)

and an industrially hardened multi-task operating system, network hardware and network protocol. In

the fully implemented Workstation application, the computer unit in each area is sufficiently powerful

to support a multi-user, multi-tasking environment, including execution of a locally resident complex

process control model.

Although there is not currently an example of a fully implemented multi-workstation approach to

inlegrated EAF process control, the trend among suppliers of process control systems is toward such

an approach. For the purposes of this report. the multi-workstation approach will be used to define

the state-of-art overall integrated process control system. In this system. each of the core systems, as

described i n preceding subsections of the report, functions as one of the distributed components of the

3-30

44

oveiall configuration. The following four essential types of hardware components (excluding sensors

and nctontorslniani~iil~tors) are included in the EAF shop configuration and are shown in the sketch

in Figure 8:

I . broadband network

2. local micro-minicomputers equipped with large, color graphics CRTs and Workstation front-ends

3. Either "smart" regulators or a combination of intelligent PLC's and analog regulators

4. network interface to inputloutput servers

Since this report has focused on direct process control for the EAF steelmaking shop, the

information handling aspect has not been included as a major topic. This is not to de-emphasize the

importance of information systems linking all accounting, scheduling. inventory, laboratory, and other

functions. A great deal of information interchange is necessary to support integrated process control

of all unit operations. Of equal importance is the considerable operatorhachine (screen) interface

design that is required to ensure that all models receive and display the correct information in a

timely manner and that the operator applies the process control systems effectively.

4 COMMENTS ON INSTALLED STATE-OF-THE-ART EAF PROCESS CONTROL

Viewing North American industries in general, the technologies applied in process control

computerization are accelerating rapidly. Both cost and variety of process control approaches are very

wide spread. As a result, the EAF steelniaker is faced with a selection from an assortment of

models, hardware, operatorhachine interfaces and computer communication systems. Although this

wide variety exploits the competitive enterprise system, this also tends to lead the typical EAF steel

producer to a conclusion that process control systems are becoming overly-complex, expensive, and

difficult to maintain. In conjunction with lliis conclusion. the fu l ly iniplemented state-of-the-art

integrated process control becomes associated with facilities that have a main focus of manufacturing

critical steels. Unfortunately these issues are further clouded as attempts are made to bring the

economic benefits accrued by EAF process control syslenis. including improvement i n productivity.

decrease in energy usage per ton, bener quality, and lower maintenance. into a proper perspective.

These benefits are not totally clear-cut and discernible from other EAF process technological

4- 1

improvements.

risk investment.

Therefore, each new implementation of process control becomes, for the most part, a

In both the greenfield and retrofit EAF shop process control installation, the small and moderately

sized EAF steel producers will seldom commit lo a large, up-front hardwarelsoftware investment (7 to

9 percent of capital is the domestic steel industry process control average) for computer- and ~

intelligent Programmable Logic Controller (PLC)-based process control. In general, the domestic EAF

shop investment in process control amounts to less than 3 to 5 percent of capital. As a contrast, it

is noted that overseas investment in process control within the steel industry is as high as I I to 14

percent of capital.

~

Hesitancy on the part of EAF steel producers to invest in needed process controls has led to

implementation of lower cost systems that are developed at the "job shop" level. Such systems often

utilize business-oriented hardware and software that are not "computer engineered" for the industrial

environment and for compatibility with long-term system needs. Although the common belief may be

that "it is easier to teach a metallurgist computer programming than it is to teach a computer

engineer n~etallurgy", the end result of the "job shop" mentality is frequently a process control

coniputer system that does not fully conform to industrial systems design requirements of:

1. safety

2 . reliability

3. maintainability

4. interconnectability

5 . expandabilitj

6. portability

I n the interest of minimizing costs, some recent and projected EAF process control installations are

configured i n ways that also minimize their reliability and expandability. It is not uncommon to see

application of

I . incompatible hardware

4-2

2. "business" (or ofice) oriented application and operating. system software

3. "corner computer store" grades of networking hardware, wiring and software protocols

4. a wide variety of applications software, variable naming conventions, software structures and file organizations

As a result, the performance of many process control systems fall considerably below expectations and

enter what may be termed "EAF Systems Technology Saturation." This factor also tends to drive

away potential implementors of EAF process control systems.

The fault does not necessarily lie with either purchaser or supplier, but the fact remains that proper

process control systems design requires computer system engineering by a limited and highly qualified

segment of engineers. In the course of the present technology search and assessment, four scenarios

emerged to explain the limited access to expertise, improper system specification, and low level of

acceptance of process control systems encountered in the small to moderate sized EAF shop:

1. The typical EAF process control user does not have immediate access to in-house personnel equipped with the detailed technological skills to assist with process control specifications and to provide long-term day-by-day support requirements for all levels of the technology involved. The user is forced to depend on the advice and the judgment of in-house businessloffice computer, quality assurance, facility engineering, and metallurgical departments and advice of suppliers when attempting to specify and select an appropriate process control system.

2. The supplier of small to moderate size EAF process control systems usually does not have sufficient resources to maintain a staff of degreed systems engineers in addition to programmers (who are not usually degreed industrial systems engineers).

3. Large industrial process control systems houses normally supply a wide range of systems for a variety of operations and industries. As a result, the staff is not normally fully equipped lo handle long-term support of the specific technology appropriate for the EAF furnace shop.

4. The large domestic and overseas turn-key supplier of EAF melt shop equipment and process control systems is usually out of the price range of the small to moderate size steel producer. In addition, large suppliers normally expect that sufficiently knowledgeable (supplier trained) in-house personnel will be available for long-term day-by-day supporl.

4-3

5 CONCLUSIONS AND RECOMMENDATIONS

The information developed during the technology search and presented in the earlier sections of this

report indicate that there are:

1. Opportunities for implementation of state-of-the-art process control systems in existing and planned North American EAF shops.

Needs exist for standards and guidelines to assist the EAF steelmaker with tlie methodology for process control project organization and management. These documents would contribute toward the assurance that viable systems are implemented and supported over the long-term. The application of computer process control technology to the E M shop should be illstalled within the framework of an industry standardized set of "ground rules" that will result in more effective functionality of. both currently installed and future systems.

2. Opportunities for development of advanced process controls and sensors to ensure continued long-term EAF shop process control enhancement in order to maintain competitive positions.

Development programs are critically needed in both sensor technology and testing of available advanced process control technologies. Regarding sensors there is need for programs that would include the iniprovement or adaptation of existing sensors and the development of new sensors.

Although it has been concluded that the technological opportunities are many. there is need for a

viable method to overcome the limited access to necessary expertise and to encourage the transfer of

new technologies into industry.

One possible solution is for North American EAF users and suppliers to collaborate in tlie

development, demonstration and economic evaluation of process control technology. Those

technologies would bc pursued that promise high return in terms of industrial competitiveness and

utilization of energy, resources. and manpower. The collaboration would serve lliree niajor purposes:

1 . to expand the identification and specificatioii of the suggested development efforts that are included i n this report. Projects would be organized to develop, prototype. econoniically evaluate, document and denionstrate botli state-of-the-art and advanced generic process control technology.

2. to accelerate the transfer of state-of-the-art and developed technology into North American EAF Shops.

5-1

3. to insure that current and future process control implementations in North America are developed using sound process control engineering.

As a recoiiiiiieiidatioii. a suggested list of development projects is included as the final section.

This list of opportunities was compiled as a starting point for potential review and expansion into a

viable collaborative program by a team of industry experts.

6 SUGGESTED DEVELOPMENT EFFORTS

In the process of identifying the "core" process control systems for the EAF facility and some of

the significant options available for their enhancement, opportunities for future developments have

become apparent. The purpose of this section is to begin to identify state-of-the-art and advanced

process control technologies that are appropriate to, but have not yet been, implemented in EAF

sbops.

Various industries are currently realizing a high degree of success in applying a vast assortment of

new automation technologies. Many of these technologies are potentially appropriate to the EAF

faciliry and might be easily integrated into existing or future process control systems with little cost.

In niany other cases, potentially appropriate technology will require extensive development to be

properly conditioned and ruggedized before installation in the EAF environment.

Potential technological developments for the EAF facility can be divided into the following

categories:

I . Technology that is currently available and being used in other applications but that requires prototype development, evaluation and testing in the EAF environment.

2. Technology for which prototypes are currently available and which require testing in the EAF environment.

3. New technologies that must be prototyped prior to testing

4. Existing system technologies that are i n need of EAF shop and industry standardization andlor guidelines.

5. Sensors that require development - development of new sensors and/or of new uses for existing sensors.

6-1

Each of the technological developments discussed below was selected for its potential to provide

immediate and/or long-term improvements in performance, maintainability and reliability of process

control systems. These improvements will result directly in improved productivity, more efficient

utilization of power, resources and manpower, and higher quality steel.

6. I Currently Available Technology

* Utilization of new sensors and integrated sensors to provide improved control and stability of the electric arc.

* Investigation of fundamental electric arc processes and conditions of the melt surface that may affect the performance of the electric arc control systems (satellite and regulator).

* Determine optintuin actuator speed of response vs. stage of melt characteristic(s).

* Evaluation of the relative effectiveness of the Self-Adjusting Model Algoritlimic Control (SAMAC) for a complete family of regulatorlactuaror conibinations (See Appendix A for a complete description of this project).

* Evaluation of the sensitivity and accuracy of the EAF shop steel refinement slag models to hoth static and kinetic representations. A research effort at the Institute for Materials Science and Engineering (IMSE) of the National Institute for Standards and Technology, funded by a Congressional mandated steel initiative. addresses kinetic modeling of AI-Ca- Fe-K-Mg-Na-Si oxide systems p7J. This work is appropriate for modeling of the dynamic phase transitions in slag: therefore, the approach may be more accurate than the current static first principles slag models. NIST currently has a portable slag model that may be transferred into an EAF environment. The model would be adapted, tested, evaluated and demonstrated.

* Evaluation of the applicability of neural network technology to control of arc stability This is mentioned in a later section.

6.2 Technology Available in Prototype Form

* More reliable sensors for nionitoring status of the shop and providing direct inputs to the computer niodel. A current project at Carnegie Mellon University - The Robotics Itistitute, funded jointly by an electric furnace systems supplier and the Ben Franklin Partnership, Commonwealth of Pennsylvania, is applying scene imaging and pattern recognition to this problem. (58.59).

6-2

6.3 New Technologies

* Manufacturing activities, resource planning and scheduling analyses to determine optimum utilization of the unit operations that comprise the electric arc furnace facility.

* Expert systems to:

1 . Assist the operator i n making corrections to a process in progress, improving energy and cost efficiency.

Expert systems are frequently employed to help determine the actions necessary to

operate a process in a preferred state. A knowledge base i s implemented, built by consolidating the expertise of highly experienced process operators, process engineers, and technical experts. I n situations where an. operator's knowledge is limited, the knowledge base can supply supplemental information about how to reach the preferred operating conditions. Expert system technology is normally implemented as operator "help" screens that query the operator for information concerning the status of current operating 'conditions. The expert system combines these sensory observations with real-time measurements and calculates one or more desirable solutions which are provided as options from the operator can select.

2. To diagnose the historical performance o f the process control model and assist the operator with rudimentary tuning of the equation constants to arrive at improved levels of performance m. This type of expert system focuses on maintaining performance of the refinement models over long periods of time. Because of the empirical nature of refinement models, routine tuning of the constants is necessary to insure that the models continue to provide valid results when characteristics of the process change. Two levels of tuning would be required:

a. Tuning by plant personnel when operator observations, accumulation of model statistical performance or real-time measurements of process variables indicate degradation in the performance of the model.

b. Tuning by a process expert when level one tuning fails to correct problenis.

A local expert system would be implemented for the first level. A series of user "help" screens, drawing on the expert system's knowledge base, would guide the operator through the model tuning procedure. The knowledge base would include a

series of queries. presentations of graphic functions. various interini tests to be conducted. etc. and would be developed by interviewing operation and process experts, Results of the adjustnieiits made by the operator would be compared against historical information and ail automatic evaluation would be made. I n the event this

6-3

assessment indicated that the tuning procedure was unsuccessful, the system would signal the need for a level two analysis (a process expert to conduct higher level tuning).

6.4 Technology Requiring Standardization andlor Guidelines

* Computer network planning to ensure both immediate and long-term compatibility. Interfacing between the EAF facility and other plant operations, including productionfplanning, accounting, etc.

* Uniformity in symbol usage (variables) across process control, process model, scheduling. and accounting operations. Such uniformity might be provided by a common data dictionary, wrinen to an industry standard, that would assign symbolic names to the variables used in applications software. I n conjunction with this dictionary, a computer- based software editor having an integral speller would be developed. This would translate to direct savings in manhours for software integration, debugging, and maintenance.

* Structured programming and commenting, enhanced portability, Computer Aided Software Engineering (CASE).

A recently completed software portability study, funded by the Association of Iron and Steel Engineers (AISE). addressed the principles involved in reusable software and estimated the savings that might be realized m. The study explored both North American and international efforts and methodologies for implementing portable software. Although AISE has distributed documents and video-tapes to encourage transfer of this technology into industry, there i s need for a demonstration project that would develop the principles and demonstrate their applicability to advanced technologies in the E M shop process control environment.

Concerns about software portability and maintainability are encouraging the use of standardized software engineering tools, including Computer Aided Software Engineering (CASE), for software development m. The EAF refinement model provides a hypothetical example of the application of software engineering principles to software development. The refinement model involves the solution of a series o f first principles thermochemical, energy and mass balance equations that provide the process control parameters to arrive at desired interim and final characteristics of the heat (chemistry, temperature, energy required. etc.). I n the applicatiou of structured programming techniques. the EAF first principles functions are decomposed into individual modules, each of which completely documents that function. Each module i s comprised of a number of routines and subroutines. any of which may be used in more than one of these modules. As shown in Figure 9, the labeled module may be considered as a "block" or symbol having input and output requirements. Standardized software engineering practices can be automated using CASE tools. One application of CASE techniques would be to select the modules necessary to accomplish a particular EAF

6-4

EAF STEEL REFINEMENT MODEL

SUB FUNCTIONS

Energy : Chemical : Mass : Slag : Scrap

Balance 1 Balance : Balance ' Model : Selection

Figure 9 Electric Furnace Refinenient Model Decomposed into Portable Subfunctions

function and to join tlieni together in a data flow diagrani as in Figure 10. The result would be an applications program consisting o f individual modules. each further broken- down into subfunctions. that could easily be transported. either wliole or in part, to other applications. These laner target applications would not necessarily be EAF applications and might be any applications requiring solution of one or more of the sanie first principles equations.

Tlie advantages of tlie CASE approach Io software design and development increase as its use in a given teclinologv' matures. As specialized functions are developed. an extensive data base of applications roiitines is gradually built up for future use. Because each of tlie functions i n tlie data base has been pre-progi'aniiiied. debugged and tested, tlie tinie required far applications prograniniiiig time is reduced considerably. Prograniniers can build programs using CASE tools in niucli tlie sanie nianiier as nieclianical parts or electric circuits are designed using Computer Aided Design tools. Programs are "built" through the combination of symbols as opposed to niany lilies of code.

6-5

Energy Removed

Energy Added Function

Chemical Convergence

Function Meastire Scrap

Additives

Chemicaf Temperatwe

Chemistrk

Figure 10: Siniplified Representation of CASE Application

A project to dentonstrate tlie use of standardized software engineering and CASE tools in the deve~opment of process control sohare would be highly conipatible with the effort discussed above to standardize variable naming conventions. The sohare resulting from this demonstration effort would repeatedly fall into the same basic, highly recognizable format. regardless of supplier. This change would encourage the selection of sohare based on its appropriateness to the application rather than on familiarity with the style and methodology of a specific supplier; software support personnel would be first application oriented and only secondarily supplier oriented. The hours once spent deciphering the layoiit of documentation could then be spend focusing on software problems. modifications. or enhancetiients.

* Guidelines for use of PCs (including industrially hardened) and definition of requirenients for process control software.

Application of PC hardware and software iii tlie EAF shop environiiieiit i s increasing at a rapid pace. motivated in large part by t l ie convenience of transferring PC applications from t l ie desktop or laboratory IO tlie industrial setting. There are a number of design

6 -'6

precautions that should be taken prior to the transfer of PC hardware and software into the industrial process control environment, but these precautions are largely ignored. Experience has shown that business oriented PC software packages used for the communication interface, data analysis and control, and operating systems can lead to unsafe conditions and disrupt the process under control. Unlike industrial hardened software, business oriented software packages are nornially lacking in the following areas:

- Internal check-out and fail-safe protection. Since business applications are developed for the oftice environment, a user error in input or output will not have catastrophic results such as personal injury or equipment or product damage.

Coniniuiiication of information between devices or other computers is not as time critical as the process control application.

- The operating systems do not necessarily implement interrupt handling for prioritized and real-time niulti-tasking and other process control functions.

- Version control is limited.

A demonstration project would be useful to demonstrate and document the need for design precautions and to develop the guidelines for their implementation.

6.5 Sensors that Require Development

As the speed of EAF steelmaking operations increases and quality requirenients become more

stringent, the need for improved sensors will also continue to increase. In addition, the introduction

of a greater number of continuous processes, such as scrap preheating, places more demand on

sensors and sensing in order to provide improved process controls l$3J.

6.5.1 Scrap Area

* Considerable sensor development remains to be done in the scrap area in order IO

implement better feedforward and feedback controls to application of the scrap process model. Sensors provide a primary means for improving predictions and thereby reducing overall EAF shop variability.

1. Scrap Size Analysis

Sensors to monitor inconling scrap size would he beneficial in optimizing the packing of scrap charges, particularly with the new continuous scrap preheat equipment. Considerable state-of-the-art technology is available in the area of computer-based pattern surveillance and recognition, including image analysis algorithms for determining size distribution @4J

6-7

The technology is used daily for a wide spectrum of applications and could be adapted and industrially hardened for use in the EAF plant environment.

2. Scrap Chemical Analysis

A key measurement problem that remains to be solved is to automatically obtain a representative chemical analysis of the incoming material. The problem will become even more acute as the EAF industry adopts continuous feed techniques. Ideally, measurements of chemical content would be conducted in a manner to provide feedforward information into the refinement models. Feedfonvard prediction and verification of scrap shipments is currently accomplished by using portable, manually operated emission spectrometers (available from a number of suppliers) to "spark" scrap samples. For a carbon measurement to be representative. however, the sample surface must be ground to eliminate effects of surface coatings and oxidation. An alternative is to apply feedback information taken from periodic bath samples to update the scrap analysis.

Automation of a rapid and accurate method for the chemical analyses of scrap would lead to significantly improved predictions in steel refinement. This would in turn result in better utilization of energy and higher quality steel. These significant benefits warrant a collaborative research effort, involving the federal laboratories, to address the problem of on-line and automatic chemical analysis of cold and/or preheated scrap.

3. Preheated Scrap Temperature Measurement (At Charging)

When preheat scrap feeding is used, the representative temperature of the scrap must be determined as it is charged into the EAF in order to conduct an accurate energy balance around the furnace. In addition. the temperature, flow and analysis of the furnace off-gas entering the preheater is necessary to develop a thermodynamic model for adequate process control of the preheat system. These measurements must be taken in an area that is highly contaminated with furnace off-gas containing particulates. Further, the emissivity of the target is highly variable. Conventional technology for infrared measurement has reportedly been tried but has not succeeded in this application.

However, other, more advanced approaches to temperature measurement have evolved from steel and space research programs. Two technologies that hold promise for application to the EAF problem are:

a. The use of noncontact infrared fiber optic transmission to view the scrap bed. The signal conversion electronics are remotely located.

b. Laser pyrometry for spot temperature measurements. A scanning laser would be used to provide temperature imaging without having a priori knowledge of the localized emissivity of the target @SJ. The signal conversion electronics are remotely located.

6-8

6.5.2 Electric Arc Furnace Area

I . Detection of foamy slag conditions and degree of arc stability.

Initiation and maintenance of foamy slag is principally a function of providing the correct additives in combination with operator skills. As the pace of EAF operations becomes more rapid, the amount of attenlion an operator can devote to each activity decreases and furnace operations are likely to be less consistent. The alternative is to unburden the operator by implementing automatic controls that will accomplish the same functions as well or better. Automatic control of foamy slag represents one potential opportunity to apply advanced process control technology to achieve such an objective.

The control problem involves several interactive independent and manipulated variables whose effects vary in magnitude and time response depending on the stage of the refinement process. Further, some operator expertise and observation is needed to successfully reach the desired foamy slag condition. Development of a solution to this problem is complicated by the need to develop a completely new strategy should the furnace operation be upgraded to include a new technology (improved additive, oxy-fuel burner types etc.)

The application of sensors providing inputs to a control model that combines artificial intelligence (expert systems) and neural network technology is a promising approach to addressing this complex control problem. In addition to the conventional power and temperature sensors, it is likely that additional advanced sensors would be necessary for tuning the control:

* Acoustical sensors to provide periphery profile of the arc

* Video observation of bath characteristics in the vicinity of the electric arcs.

Discussions with suppliers of electric regulators and recent technical publications have alluded to the existence of electromagnetic fields in the vicinity of the arc that affect the distance between the bath and the electrode (arc length). This effect translates as "hunting" i n the electrode positioning control loop. Systems are available to conduct video analyses with pattern recognition. This study would focus on improvement of electric arc stability through control algorithms that comprehend other process variables. This would be reflected as a direct decrease i n melt time.

2. Continuous liquid steel temperature measurement

For about three decades, various approaches have been offered for continuous iiieasurenient of the niollen steel bath. More recently. both the Departilleilt of Energy and National Institute for Standards and Technology have publicized methods for high temperature bath measurements. A program should address application of this technology i n the EAF environment.

6-9

3. Continuous Slag Analysis.

A current AIS1 collaborative research program is addressing the continuous chemical analysis of molten steel during refinement. A breakthrough in this program with a carry- over into continuous slag analysis would provide the necessary input to a kinetic slag model, previously discussed as the IMSE - NIST program.

4. EAF Off-gas

a. Chemical analysis

A long-standing problem has been the difficulty of conducting a representative chenlical analysis of off-gases from the EAF. The factors that impede gas analysis in the EAF environment (Le., particulates) are not unlike those of other environments, however, and considerable ongoing research is addressing this problem. It is likely that at least one of the general solutions developed, such as sonic methods for measuring gas concentrations m, might be applicable to the EAF.

b. Pressure

A reliable and representative measurement of off-gas pressure would be useful for scrap preheat and for oxy-fuel burner control. Pressure regulation of the off-gas would regulate the flow rates. A reliable pressure measurement could also be used differentially for determining flow.

c. Flow

Success i n measurement of off-gas flow has been somewhat limited because of the reduced reliability in the high particulate atmosphere. .A recent Ames Research Center study used seeded particulates to determine flow by laser-speckle velocimetry m.

d. Temperature

Availability of a reliable and representative off-gas temperature measurement would provide a key element in a heat transfer model. In addition to providing an input for the EAF energy balance model. this measurement would be of significant use for measuring heat loss of the off-gas during the scrap preheating process. This measurement would be applied as the control variable for oxy-fuel burner regulation in the EAF and for the auxiliary burners in the scrap preheat operation.

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I . APPENDIX A

SELF-ADAPTING CONTROL FOR

ELECTRIC ARC FURNACE REGULATORS

National Science Foundation --

I n a recent study funded by the NSF, a self-correcting adaptive control algorithm was developed for

use i n EAF furnace regulators m. A digital computer simulation was used to model the EAF

electric power circuit, a computer-based regulator, and an amplidynelpully electrode positioning

acfuator. Three regulator control algorithms were compared:

* a conventional control system

* a model algorithmic control (MAC)

* a self-adjusting model algorithmic control (SAMAC)

Experience has shown that the sensitivity of the electrode positioning regulator should be adjusted to

suit the stage o f melting. While conventional controllers operate with fixed gain settings, the self

adjusting control is capable of constantly changing the control loop gain as a function of an analysis

of the change in process dynamics. The simulation results indicate that the performance of tlie

adaptive controller resulted i n a five second improvement i n response to setpoint changes over

conventional feedback control. This leads to the following two significant conclusions:

I . For EAF electrode positioners having relatively slow acting amplidynelpulley actuators and microprocessor-based regulators, the five second improvement in response time can be achieved by changing the conventional control algorithm to a self- correcting adaptive control algorithm. Each time a significant move in electrode position setpoint i s conducted, this response time improvement would accuniulate as a direct reduction in

overall in heat time.

2 . For EAF electrode positioners having fast acting actuators. such as an elecfrohydraulic system, and a microprocessor-based regulator. the t ime saving i s likely not as significant per move. However. t l ie algorithni s t i l l self-adjusts for the non-linear dynamics of the loop and provides a response fliat i s near-optimum. This improved stability would reduce, i f not eliniinafe, the under-damped (oscillating) andlor over-damped (sluggish) confrol system responses that can cause equipment damage and electrode breakage. (If would be

A - 1

a straightforward operation to change the simulation used by the NSF investigators to one representing the actuator dynamics and thereby determine the time improvement in the loop response per actuator configuration.)

Because the self-adjusting model algorithmic control (SAMAC) has been shown to compensate for

the non-linear dynamics characteristic of the electrode position regulator control loop, it may be a key

element i n reducing or eliminating "hunting" of the positioning system. "Hunting" or cyclic

operation in a feedback control system is normally due to incorrect feedback conipensation parameters

for the loop state. The sustained cycling is an undamped response at or near the natural frequency

of the closed loop. Capability of the SAMAC to analyze the dynamics of the loop and adjust the

parameters for changes would tend to minimize "hunting" problems.

Most state-of-the-art regulators are furnished with single board digital computers or microprocessors.

Depending on reprogramming capabilities, a suitable algorithm for input conditioning, non-linear

control or conditioned output may be installed.

A-2

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6. Same as 3

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9. IBID

IO. Vallomy. J . A., "The Consteel Process in North America," 43rd Electric Furnace Corfercnce Proceedings, Iron and S/eei Socie/y of AIME, Vol. 43, December 10-13, 1985, pp. 17-23.

1 I . Spivey. P. B. and Vallomy. J. A., "Operation of the Consteel Process in North America," Irori and Sfeel Engineer, September 1987, pp. 27.

12. Technoeconomic Report (same as #3) pp. 4-29.

13. IBID

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REF-1

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19. IBID

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26. Same as 22.

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30. Same as 17

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REF-2

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32. Same as 21.

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35. Scliwabe, W. E., "Measurement and Evaluation of Arc Furnace Related Network Disturbances in North America," Aurontared Sysrcm mid Process Technology," Dec. 9, 1988, Section 11.

36. Pongia, V. J . and Battish; J . P.. "Electrical Demand Management at Phoenix Steel, Claymont Plant," Iron mid Sreel Engineer, September, 1983, pp 34-38.

37. Brochure. "Demand Tech 11". MiUrecli - HOH, February, 1989,

38. Schroeder, D. L.. "Electric Furnace Control Using Personal Computers", Sysrenis for Elecrric Furnace Sreelnwking Syniposiunt, Section I, December 9, 1986, pp 2 and 3.

39. Same as 17 (Electrode Stalling - Krupp)

40. Brochure, "Arc Furnace Regulators", Robicon Cory., December, 1988.

41. IBID

42. Same as 17

'43. Same as 16

44. Same as 17

45. Summary of Activities, "Nitrogen Profile in EAF's." Ccnfer .for Mcrals I'roducrion Ncpor'l.

August 1988.

46. Same as 4

47. Wilhelni, M.. "The Use of a Ladle Refiner i n Conjunction with an Electric Furnace and Caster." Irorl a i d Sfcelnmko; July 1985, pp24-30

REF-3

48. Thomas, L. W. and Lavers, J. D. "A Finite-Element Package for the Analysis of Electromagetic Forces in Power in an Electric Smelting Furnace." IEEE Transactions on hidi~stry Applications, Vol. IA-22, No. 4, JulylAugust 1986, pp578-585.

49. Same as 46

50. "Process Control Computer Technology for NK-AP System - Introductory Overview," Davy Mc-Kee Corp.. April 5, 1985, 19 Pages.

51. "Alloy Charging of an AOD at Latrobe Steel," lron Age Magazine, September 6, 1985.

52. Same as 16

53. Same as 17

54. Rogers, C. D., "Report of Trip to North Star Steel - Monroe, MI," Forthcoming.

55. Rogers, C. D., Houk, R. C. and Hudak, J. J., "The Application of Advanced Workstations for Process Control Systems," Proceedings of the 7th Annual Control Engineering Con&, Chicago, IL, June 7-9. 1988, Section XIII, pp19-24.

56. Schroeder, D. L., "Workstations as Applied to Steelmaking," Automared Systems and Process Technology Seminar, December 5 and 6, 1988, Section 4, ppl-9.

57. Hastie, J. W. and Bonnell, D. W., "A Predictive Phase Equilibrium Model for Multicomponent Oxide Mixtures," High Temperature Science, Vol. 19, 1985, pp275-306.

58. McManus, G. J.. "Computers".Iron Age Magazine. June 1988, pp17-18.

59. Same as 56.

60. McCarroll, B. "Expert Systems - Early Warning for Process Control", Manufacturing Systems Magazine. March 1989. pp46-51.

61. Svolou, A., Hudak, J. J., Leonard, R. J . and Soffa, M. L., "Software Portability Methods and Tools: Reusability, Rapid Prototyping, and Expert Systems," AISE CurtJereuce, Chicago, IL, September 22-23. 1986.

62. Hanner, M. A.."CASE Tools - Productivity for the Masses." DEC Pro[miortal, December 1988. ~ ~ 3 8 - 4 4 .

63. Kappnieyer, K. K. and Rall, W. "Process Control Needs for Future Steelmaking". /984 ASM Metals Cortgrrss, Detroit MI. September 15-20. 1984. Paper No. 8408-005

64. Brocliure, "High Performance Image Analysis", Tracor Nortltern, 1989.

REF-4

65. Elleman, D. D., J. L. Allen and Lee. M. C.. ”Laser Pyrometer for Spot Temperature Measurements”, National Aeronautics and Space Administration, JPL /wenlion Repor/,

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66. Sanie as 48.

67. Hallewell, G. D., ”A Sound Method for Measuring Gas Concentrations”, Research mid Developnvrrr Magazine, September 1988, pp98-101.

68. Smith, C. A,, Krothpalli, A. and Lourenco, L. M. M., ”Measuring Flow With Laser Velocimetry”. NASA I‘eclmical Briefs, October, 1988. p 56.

69. Nadira. R. and Usoro. P. B., “Self-Adjusting Model Algorithmic Control of a Three- Phase Electric Arc Furnace,“ Transacrions of the ASME, Journal of Dynamic Sysrems, Measirrcmenr mid Corrrrol, Vol. 1 IO, December 1988, pp361-6.

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