Distributed Process Control Report

177 Pages·1990·3.337 MB·English

by  Architecture Technology Corp. (Auth.)

DISTRIBUTED PROCESS
CONTROL REPORT
3rd EDITION
SEPTEMBER 1990
ARCHITECTURE DISTRIBUTED OUTSIDE THE USA/CANADA BY:
ELSEVIER ADVANCED TECHNOLOGY
TECHNOLOGY
MAYFIELD HOUSE
CORPORATION i-i crxnrn 256 BANBURY ROAD
t L 3 t V 1 t Κ OXFORD 0X2 7DH
SPECIALISTS IN COMPUTER ARCHITECTURE
ADVANCED
UNITED KINGDOM
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© Copyright 1990 Architecture Technology Corporation. All rights reserved. No part of this publication may be reproduced, photocopied, stored on a
retrieval system, or transmitted without the express prior written consent of the publisher.
DISTRIBUTED PROCESS
CONTROL REPORT
3rd EDITION
SEPTEMBER 1990
ARCHITECTURE DISTRIBUTED OUTSIDE THE USA/CANADA BY:
ELSEVIER ADVANCED TECHNOLOGY
TECHNOLOGY
MAYFIELD HOUSE
CORPORATION i-i crxnrn 256 BANBURY ROAD
t L 3 t V 1 t Κ OXFORD 0X2 7DH
SPECIALISTS IN COMPUTER ARCHITECTURE
ADVANCED
UNITED KINGDOM
P.O. BOX 24344 · MINNEAPOLIS, MINNESOTA 55424· [phone] TECHNOLOGY
© Copyright 1990 Architecture Technology Corporation. All rights reserved. No part of this publication may be reproduced, photocopied, stored on a
retrieval system, or transmitted without the express prior written consent of the publisher.
DISCLAIMER
Architecture Technology Corporation makes no representations or warranties with respect to the contents
hereof and specifically disclaims any implied warranties of merchantability or fitness for any particular
purpose.
Further, reasonable care has been taken to ensure the accuracy of the report, but errors and omissions
could have occurred. Architecture Technology assumes no responsibility for any incidental or consequen-
tial damages caused thereby.
Further, Architecture Technology Corporation reserves the right to revise this document and to make
changes from time to time in the content thereof without any obligation to notify any person or organiza-
tion of such revision or changes.
This disclaimer applies to all parts of this document.
FOREWORD
Distributed process controL.what is it?
It's a question that the reader might ask again at the end of this report; but one thing that it still isn't is direct
digital control (DDC), and that's explained in the text.
One term applied to the technology is integrated process control. That's still a good one. But with hundreds
of companies supplying some form of the technology to users in such diverse operations as papermaking and
aircraft parts machining, there are thousands of "experts" out there who are liable to call the technology
anything with the words "automated," "plantwide," or "distributed" as a part of the description. Even our EDP
friends are distributing their processing all over the place.
The tendency seems to be toward smaller, distributed cells, all reporting back to a supervisory computer.
Plantwide control is still blossoming, but now the emphasis is on cells working a particular group technology,
rather than one large, "flexible" system, which, incidentally, users are finding is not so flexible, after all.
Most of the work in setting up a distributed control system (DCS) amounts to configuring an engineering
database. Even before the system starts up, the company may cycle through a number of changes. Loops may
be reconfigured or, more frequently, the system is expanded with additional control loops. Unfortunately, each
change may be costly and time consuming, because it involves some awkward reconfiguring of the database
and rewriting documentation that goes with it.
Two conflicting objectives must soon come forward in any discussion of integrated computer control of
processing or manufacturing plants today.
One objective is to distribute the individual loop controllers back into the field, to mount them directly on
the machine or process they control, for maximum security of the loops and minimum loop cost. This
objective is rapidly nearing economic attainability in many systems. The second conflicting objective is to
achieve a true "global database" for the total manufacturing or processing plant. This objective gets a lot of
lip service and unrealistic claims by system marketers.
The true global database must be one in which data is essentially coherent within "fixed real time segments,"
and accessible to everyone who needs it. In simpler terms, accessible data, from management information
systems to real-time control loops, should be completely consistent at the time it is written or read.
Data is stored in a wide variety of computers, from DEC VAXs and IBM mainframes in the halls of
management, through programmable logic controllers (PLCs) and integrated DCSs, down to individual
microprocessor-based controllers scattered all over the plant.
Data coherency is practically nonexistent with such a chaotic database. Global database management is
impossible. Useful "information" about the status of the plant is hard to assess, and true "knowledge" of the
overall status is unattainable. Any attempts at control, based on such incoherent data are likely to fail, and
often are fraught with danger.
Try to keep these very real limitations in mind as you read control systems advertising. Don't let anybody
make it sound easier than it is.
Distributed Process Control
List of Figures
Figure 1: Control System Elements 1
Figure 2: Basic Control Loop Example 5
Figure 3: Process Control Systems Types 6
Figure 4: Volkswagon Automotive Paint Line 12
Figure 5: Distributed Process Simulation System 14
Figure 6: Bailey Network 90 DCS 17
Figure 7: GEMS Block Diagram 17
Figure 8: Operator Interface Unit Display 18
Figure 9: Bailey Block Diagram 19
Figure 10: Synchronous Operation 22
Figure 11: Integrated Plant Management System 32
Figure 12: Process Manufacturing Example 33
Figure 13: Foxboro's Plant Management System 35
Figure 14: Moore Products Company Network 38
Figure 15: PC Factory Network 44
Figure 16: Process I/O 51
Figure 17: MasterNet 68
Figure 18: Process Station 70
Figure 19: Plant-wide Network 73
Figure 20: Evolving "Personalities" 80
Figure 21: Plant Personality 81
Figure 22: Micromax Process Management Center 83
Figure 23: Sequential Function Chart Programming 86
Figure 24: Automatic Supervision for Base Regulatory and Sequential Controller 88
Figure 25: Plant Control System Hierarchy 118
Figure 26: Current System Architecture 119
Figure 27: Control System Failure Rate 127
Figure 28: Example Data Flow Diagram 135
Figure 29: Kodak Systems Architecture 141
Figure 30: Complex Recycle System 146
Figure 31: Control System Simulation 147
Figure 32: Typical Node Connected to the Carrierboard 155
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Distributed Process Control
1. Connecting the Systems and the Definitions
Distributed process control is the term applied to modern process control systems in which the direct
control function is performed independently for each control loop and is thus operationally and physically
remote from the central control room. Three specific conditions characterize a distributed process control
system:
1. Microprocessor-based controllers with multi-function computing capability, flexible
communications structures, and the capability of operating without direct central control;
2. A central control room which communicates with all process controllers and directs the
objectives of all control loop processors; and
3. A digital data highway which provides communication between the control center and all
assigned process units as well as between the control stations in those units.
Any discussion of a major advanced industrial technology such as distributed process control should start
with defining terms.
Decision
4
Actuation
Instrumentation System
Figure 1: Control System Elements
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Distributed Process Control
1.1 What is Distributed Control?
Control-In terms of the technology, the definition requires detailed explanation:
A measurement of a process variable must be taken. The process variable might be temperature, pressure,
rate of flow of a liquid through a pipe, or many other measurable variables. Once the measurement has
been taken, the value is compared with a predetermined standard or "normal" value called a setpoint.
The setpoint is that value which is considered correct for the process variable being measured. In a home,
for example, the setpoint for the furnace or air conditioner is the temperature value upon which the
thermostat is set.
When the value of the process variable has been compared to the setpoint, a decision must be made,
depending on the comparison: has the value of the variable increased, decreased, or stayed the same with
respect to the setpoint? The decision can be made by a variety of methods ranging from a person reading
a pressure gauge to a computer comparing thousands of input signals with thousands of stored setpoint
values.
When the decision is made, the process variable must be increased, decreased, or left alone. If the variable
has deviated from the setpoint, a piece of process equipment must be actuated to bring the variable back
to the setpoint. In the case of the home, the furnace is turned on when the room temperature drops
below the desired setting on the thermostat. All control systems, no matter how complex, embody the
measurement-decision-actuation functions. Measurement and decision, by themselves, constitute an
instrumentation system. Actuation must be a part of the cycle for a CONTROL SYSTEM to exist.
Process-Generally, a process can be described as the alteration of material(s) through the use of
production or manufacturing techniques-heating, machining, welding, refining- and the application of
labor. There are really just two kinds of processes: continuous and discontinuous. Discontinuous
processing deals with definable quantities and has been further subdivided into batch processes and
discrete manufacturing, depending upon the industries involved.
Continuous Processing-Continuous processing occurs when a raw material is fed into one end of the
production facility and finished or processed material is constantly delivered at the other end, in a
seemingly never-ending, continuous flow. Raw material cannot be uniquely tracked, and materials are
processed in an identical manner.
Because large continuous process control systems were developed as digital electronic replacements for
pneumatic analog controllers, their initial marketing thrusts were aimed at the replacement of "ancient"
pneumatic controllers with "modern" digital electronics technology.
Two of the most notable examples of continuous processing are the refining of crude oil and the
production of paper.
Batch Processing-There are several key concepts that distinguish batch processes from continuous
processes. They are:
1. Quantifiable loads (batches) of raw materials are introduced into the line for processing.
2. Each load of material being processed can be identified (counted) all the way through the
process, since each is kept separate from all others being processed.
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Distributed Process Control
3. Each load of material can be processed differently at various equipment areas in the line.
4. Movement of a load from one production step to the next cannot occur until the next step has
been vacated.
5. Batch processing requires more sequential logic than continuous processing.
6. Special processing steps can be taken to recover failures in the processing cycle.
Batch processing is derived from the relay logic and timed sequence side of control rather than from the
analog side. Hence, its origins are inherently rooted in logic-based or digital concepts.
Discrete Processing-Discrete processing is usually thought of as assembly line or discrete component
manufacturing and includes work done in machine shops and foundries, on plastics molding equipment,
transfer lines, and most other equipment associated with general machine shops and assembly plants.
1.1.1 The Roots of Distributed Control
In the not-too-distant past, all industrial control functions were performed at a site close to the portion of
the process being controlled. Operators relied on their training and experience to tell them when to
perform certain tasks. This type of procedure is still carried out today in many papermaking operations.
The operator would watch the color of a flame, for instance, and note the level of boiling in a liquid being
heated. When the liquid's boiling reached a certain intensity, which the operator's experience recognized
as "right," the operator would initiate the next operation. This was (is) true distributed control.
Then along came the pneumatic transmission of control signals, and the world of industrial control
changed forever. It became possible to sense variables and implement control strategies remotely, with
reaction times near the speed of sound. Sensory input signals and control output signals were routed all
over the plant to and from a common location. Centralized control rooms had evolved.
An operator no longer had to rely mainly on experience. One could examine a panel of instruments to
determine the status of the process without having to leave the control room. All necessary controls were
at one's fingertips. This wealth of process-conditioned information, coupled with the operator's years of
experience, enabled the operator to implement any corrective action required to maintain a consistent
level of production and quality.
Unfortunately, the speed of sound, coupled with the inherent loss of signal strength due to resistance to
the passage of pneumatic signals imposed by the tubing's walls and bends, limited the practical distance
over which input and output signals could be transmitted.
1.1.2 Enter Electronics
With the electronics revolution came the ability to send and receive signals at nearly the speed of light.
Distances over which signals could be transmitted also increased significantly. The plant area served by a
particular control room also increased. In some installations, plant-wide control was a reality.
As computers became practical for industrial control applications, the operator's experience was translated
into programs designed to encompass almost every possible contingency. The computer could evaluate
thousands of sensory inputs to determine, in seconds or faster, the proper corrective action. However, the
computer became more of a fine tuner than an operator. Most companies still relied on the operator's
instincts rather than trust the process totally to the computer. Centralized control rooms were still
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Distributed Process Control
identified by wall-sized control panels.
This lack of confidence in the computer was most felt in the nuclear power generation industry, and still
is.
If a computer had been qualified through Nuclear Regulatory Commission procedures, trusted to examine
the thousands of sensory input signals, and configured so that it could have provided the properly
formatted results to the operators at Three Mile Island (TMI), there probably would have been no
incident. In reality, the computer at TMI was used more as a data logger than a monitor, analyzer, or
decision maker. The TMI operators had no centralized information display available. Faced with dozens
of alarms and panels of flashing lights, and the fact that they had to dump the computer memory several
times, they could not assimilate the data into a concise picture of what was really happening "in there."
Because of this lack of information, the operators consistently made the wrong decisions and implemented
procedures which could not correct the true conditions in the reactor's core.
1.2 Why Distribute Control?
Because of the power inherent in the microprocessor as well as its small size and low cost, the actual
process controller can now be located very close to the process. Memory devices are now inexpensive and
rugged enough to support the microprocessor-based controller located in the field. The centralized control
room, now freed from the need to control every loop, has evolved into a supervisory-centralized operations
center.
In operation, the program controlling the process resides in the local controller. Should the data highway
connecting the local controllers to the centralized operations center be damaged, or if the centralized
operations center should experience some sort of failure, the local controller can maintain the operation of
a process or enter into an orderly shutdown sequence without further communications with the centralized
operations center.
The microprocessor has also made possible affordable equipment that can be programmed to provide
useful operator displays on color CRTs. Alarm annunciators can now indicate the sequence in which
alarms occur, making it easier for the operator to identify problem areas in the plant.
13 Control Comes Full Circle
Control has been distributed back to the process, where it originally resided-but with big differences.
The local controllers are now connected by a data highway to the central operations center. The only
information that must be sent from the controller to the centralized operations room is exceptional data,
i.e., data of exceptions to the desired norms. Normal control operations are handled by the local
controller.
With the implementation of distributed control, the centralized computer has been freed from the
responsibility of monitoring all inputs and outputs. It can now be configured to perform such plant-wide
supervisory tasks as energy management and optimization, providing a new hierarchy of control strategies
which can be implemented to increase product throughput while improving quality and minimizing waste,
either of materials or energy.
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Distributed Process Control
Supervisory
Commands
\
-Q Controller ^-
i Sensor \
s Process
Final
5 Feed
Control
Heater Temperature Controllled
^ Feed Output
Cold Feed
Figure 2: Basic Control Loop Example
1.4 The New Distributed Control
As described above, one might get the impression that distributed control is simply the physical
distribution of the various process controllers back to local sites at or near the process while retaining a
hierarchical control structure via a data highway.
This is the traditional view of distributed control held by many process control system manufacturers and
users.
Is it wrong? Not necessarily; just not complete enough.
Traditional process control systems generate databases upon operator/program requests by having a
frequently updated database resident in the host computer. The system copies this information for display
to the operator or for data logging purposes. When alarms are going off, this is an especially time
consuming task. Consumption of time is critical at this point, and data from the centralized database is
frequently not recent enough.
Therefore, to respond to time-critical situations, the database itself should be distributed throughout the
system and resident on the data highway. When called upon to display information, the system simply
assembles the requested data directly from the database. Hence data would be up-to-the-minute and the
information could be displayed to the operator in a substantially faster time.
Therefore, a proper definition for a DCS should refer not only to the physical distribution of the control
hardware but also to the distribution of the database.
1.5 The Configurations of Process Control Systems
Control Engineering magazine first defined the configurations of process control systems as Type 1, 2, and
3 in March 1979.
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