LN-1.1.4-Simulation of Industrial Processes

7/29/2019 LN-1.1.4-Simulation of Industrial Processes

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Simulation of Industrial ProcessesTaken from the white paper of authors:

Juan Atanasio Carrasco andMatti Paljakka

ICS41: Computer Modeling and Simulation Lecture#4: 1

Table of Contents

Introduction Introduction to Process Simulation Simulator Approaches using Control

Systems Useful Standards for Automation Simulation

Works


Research and Development Needs inAutomation Simulation


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Introduction

-simulation

most significant breed of simulation from theautomation point of view.

simulation facilitates the realization ofen ineerin activities related with the


installation and optimization of control

systems in real plants.

Introduction to ProcessSimulation

.

Demonstration

Are normally used for the description ofindustrial installations.

The accuracy of the models is not important,and simple balance of mass based models arenormally enough.


The display of the simulators is very importantand the use of multimedia aids in thesesimulators is being constantly increased.


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Introduction to Process

Simulation

.

Engineering

Are usually focused on the development ofdetailed studies of industrial processes.

The aim of engineering simulators is to evaluateand compare alternative process and controlsolutions.


The mathematical models are the mostimportant part of the simulator and they are

usually very accurate.

Introduction to ProcessSimulation

.

Testing

Simulation is often used for testing the designand implementation of process and automation.

The accuracy requirements vary depending onthe test case.

In automation tuning, the process model needs


to give a realistic dynamic response. In testing the automation implementation,

qualitative behavior is often enough.


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Simulation

.

Training

Are normally focused in the initial training of theoperation personnel of an industrial installation(although installations may need continuoustraining).

The human machine interface is crucial while the


accuracy of the mathematical models can belower.

When the simulator is focused on other types ofpersonnel (e.g. maintenance) the accuracy canbe even lower.

Introduction to ProcessSimulation2.1 Uses of Simulation

Operation Support Simulators are used in supporting operative tasks.

By using predictive simulators, operators canestimate consequences of alternative actions, andproduction management can test and optimizeproduction plans.

As the simulation speed must be faster than real


,strict.

It is sufficient if the simulation model can predictpotential problems and estimate productionmeasures.


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Simulation2.2 Simulation Features

Initial Condition A set of data that represents the status of the

reference unit from which real-time simulation canbegin.

It is useful to have the possibility of adding new setsof initial data during a simulation session.

This possibility is usually known as the Save of


.

Some simulators also allow to make a snapshot of

the main simulation variables When a series ofconsecutive snapshots is available, we can talk aboutthe replay option.

Introduction to ProcessSimulation2.2 Simulation Features

Backtrack

The ability to reset the simulation to some prior timein operation.

Some simulators provide the possibility of returningto a previous moment of the current session withoutthe need to save and restore an initial condition.



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Freeze

The controlled cessation of the simulation facility.

When Freeze command is executed, the simulationscenario is stopped.



Run

Transition to a live simulation scenario.

This transition is usually made from freeze status.

Every simulator usually has commands for makingpossible a run/freeze transition.



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Override

The ability to interrupt or modify the I/O data transferbetween the simulator mathematical models and theinstrumentation which is contained in the panel.



Speed Up and Slow Down

In many uses of simulation, it is desirable to be ableto change the execution speed.



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Simulation2.3 Functional Decomposition of a Simulator

Models of the Process

Simulation models of the installation

Models of the Control Systems (controllingthe installation)

These models of the control should represent allthe layers that appear in the real control system:


o MMI s, process automation, sa ety systems,communication, field devices.

Introduction to ProcessSimulation2.3 Functional Decomposition of a Simulator

Simulation Management Functionality

In addition to the models there is necessarymanagement of the main simulation functionalitypreviously defined.

Instructor Oriented Functions

When training is included in the purposes of the


,helping the work of the instructors.


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Simulator Approaches Using

Control Systems

These are the standard set b ISA for s ecif in FossilPlant simulators:

a. Simulation

which uses alternate hardware and softwareprogrammed to emulate the instrumentationsystem including the man machine interface,


w ou necessar y rep ca ng a s unc ons

Simulator Approaches UsingControl Systems

Plant simulators:

b. Partial Simulation

which uses the actual system hardware andsoftware to replicate the man machine interface.

However, actual functions e. ., control loo s,


efficiency calculations) are emulated in thesimulation computer.


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These are the standard set b ISA for s ecif in Fossil


Control Systems

Plant simulators:

c. Stimulation

which uses the actual system hardware andsoftware, modified to function properly in thesimulator environment.


Typically, the interface of the automation andprocess is defined in a manner that the fielddevices and hard-wired automation areincluded in the simulation model .

3.1 Simulation Method


Advantages

Ease of accommodating simulator modes ofoperation and malfunctions.

Cost effectiveness, especially if emulation software isavailable off the shelf and simulation computerresources can be shared.

Hardware maintenance trainin and s are arts


costs are lower than in other methods.

The simulator can be built in a relatively short time.


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Control Systems

Advantages

The scope and extent of the simulation is notconditioned by the tools.

The schedule for the simulation system isindependent from the schedule of the controlsystem, which enables the use of simulation in theevaluation and optimization of the control system


before commissioning.



Disadvantages

The simulation model of the control application maydiffer from the reference system.

Relatively high software maintenance costs as thesimulation model of the automation system includingthe MMI's must be maintained separately from thereference system.



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3.2 Partial Simulation


Control Systems

Advantages

It is easy to accommodate simulator modes ofoperation and malfunctions.

Partial stimulation provides high visual fidelity.

The lowest combined software/hardwaremaintenance costs are associated with partialstimulation. It is obvious that the cost of less


equipment should result in a smaller maintenancecost although this assumption can be affected by the

strength position of the control system supplier.



Advantages

The lowest combined software/hardwaremaintenance costs are associated with partialstimulation. It is obvious that the cost of lessequipment should result in a smaller maintenancecost although this assumption can be affected bythe strength position of the control system supplier.


The control system displays can be tested in thesimulation system before installing them on theplant.


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Control Systems

Disadvantages

Possible discrepancies between simulated and actualsystem functions

Possible interface throughput: limitations for largescreens.

As basically every function displayed on the screenneeds to be im lemented in the simulator the


simulation model scope and extent cannot be freelychosen.

3.3 Stimulation Method


Advantages

Stimulated software and configurations are easier tokeep up to date with the plant

Plant spare hardware can be used for the simulator.

Stimulation is potentially more cost effective, sincesystems are getting more and more complex and,therefore more costl to emulate.


The entire automation system can be tested in thesimulation system before it is installed on the plant.


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3.3 Stimulation Method


Control Systems

Possible limitations in the communication throughputbetween the stimulated system and the simulator maylimit update rates to the point that the simulatedprocesses are difficult or impossible to control (distributedcontrol systems). Communication delays can causepotential problems especially in pulse control and in fastcontrol loops.


the stimulator modes of operation are strongly dependenton the system internal architecture and can be extensive.


Tecnatom BWR simulator


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The selection of any of the three methods requires a


Control Systems

care u ana ys s o e comp e e e-cyc e cos sassociated with each item for a specificapplication, including:

a. Hardware equipment;

b. Software design, development, and testing activitiesincluding user involvement (e.g., design reviews, datacollection);


c. Hardware and software maintenance and updates;

d. Training; and,

e. Documentation

Other cost-related factors should be considered,


where application, such as:

a. Availability of in-house spare equipment;

b. Importance of visual fidelity versus functionality; and,

c. Acceptability of a limited functionality during certainmodes of operation (e.g., backtrack/replay).



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The cost-effective build-up, maintenance and use of

Useful Standards for Automation

Simulation Works

simulation systems consisting of software andhardware by multiple vendors is possible onlybased on the use of standards and other vendor-independent specifications.


4.1 OPC

Useful Standards for AutomationSimulation Works

stands for OLE for Process Control

the most widely used vendor-independent specificationfor communicating control system products, normallydrivers between field equipment and control or humaninterface devices.

objective of the OPC Foundation:

OPC will bring the same benefits to industrial hardware


and software that standard printer drivers brought toword-processing.


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4.1 OPC


Simulation Works

when OPC is in simulation, an interface for controllingthe simulation features is needed.

3 ways to design an interface:

as a non-standard extension interface,

as data items that are toggled or given differentstring values to correspond the operations, or

as OPC commands in accordance with the upcoming


.

4.1 OPC


it should be noted that the OPC standards are merelyinterface specifications, which specify how to find thedata, how to read it, write it and subscribe to it. Inthe task of integrating a simulation system this is agood start, but also the data semantics and contentshave to be agreed upon in order to make a fullyfunctional system.



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4.2 CAPE-OPEN


Simulation Works

CAPE stands for Computer Aided Process Engineering

The CAPE-OPEN specifications address thefunctionality within a simulation engine, e.g. thesolution of material properties and chemical

reactions.


4.3 HLA


s an s or g eve rc ec ure

is a general purpose architecture for simulation reuseand interoperability.

The HLA specifications have been adopted as the IEEEstandard 1516.

The HLA standard specifies rules for joining a softwarecomponent in the distributed simulation system(federation): how the accessible data and supported


events are expressed and published on the interface ofeach component (federate). Furthermore the standardspecifies how the simulation system is executed in arun time infrastructure (RTI).


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4.4 Product and rocess data standards


Simulation Works

Typically a simulation model is sophisticated and accurate

enough for automation system checkout and operatortraining can be built entirely based on process designdata: the interconnections of process components,their dimensions and basic correlations e.g. pumpcurves. Measurement data from the actual plant is


requ re or ne- un ng on y.

4.4 Product and process data standards


ISO TC184/SC4, i.e. ISOs sub-committee 4 (IndustrialData) of technical committee 184 (IndustrialAutomation Systems and Integration) maintains thefollowing standards concerning the process andautomation data life cycle management:

Standard for the exchange of product data (STEP) - ISO 10303


In addition to the exchange of data the standardprovides information models on data representation.

STEP comes in dozens of parts specifically targeted forrepresentation of e.g. geometries or materials.


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Simulation Works

Parts library (PLIB) - ISO 13584 is targeted for part librarydata exchange between suppliers and users in a computer-interpretable format.

Industrial manufacturing management data (MANDATE) -ISO 15531 is a relatively new standard whose scope coversdata related to e.g. the use of resources and material flow.


-production facilities - ISO 15926 is maintained and enhancedby the Norwegian POSC/CAESAR project.

The standard has been developed based on the datawarehousing needs of large multi-supplier projects in the

process industry.



Process specification language (PSL) - ISO 18269 defines aneutral representation for manufacturing processes.

Integration of industrial data for exchange, access, andsharing (IIDEAS) - ISO 18876 aims at better interoperabilityof applications and organizations that implement differentstandards.

All of the above standards are extensive; implementing any of


t em in a pro uct is very a orious. Furt ermore evenimplementing a standard in a product does not necessarilyconnect it seamlessly to the data flow of the process lifecycle. The process design data is semantically rathercomplicated, and the conceptual levels of data are differentin different applications.


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-


Simulation Works

. IEC 1131-3 is the common name of the software section

of the IEC 1103, which is the most important standardinto the PLC (Programmable Logic Controller) arena.

This standard defines 5 different program languages. Italso specifies how the configuration of the software inPLCs should be implemented in order to make possiblethe concurrent use of different languages in one PLC.


The languages defined in the standard, which can betext based languages or graphical languages, are:

-


.

Text languages

Mnemonic (List of instructions)

Structured Text

Graphic languages

Ladder diagrams


Sequential function chart


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5.1 Benefits of simulation-assisted automation testing

Using Simulation in Automation

Testing

Simulation can be used for the following types of automationtesting:

Validating the overall plant concept and control systemrequirements before the selection of the automation supplier

Testing of control strategies before the implementation ofthe automation application

estin of Human Machine Interfaces.


Simulation-assisted Factory Acceptance Test of theautomation configuration

Input-output equipment testing

Other equipment testing (non Input-output equipment)

5.2 Guidelines for planning and executing the tests

Using Simulation in AutomationTesting

There is basically no standard way to select test runs when usinga simulation assisted automation system.

The selected configuration for the simulator will condition the typeof tests that could be performed within:

When the simulation option mentioned previously isselected, the use of the simulator for testing is more limited

In the artial stimulation and full stimulation a roaches the


human machine interface of the control system can be fullytested.

In the full stimulation approach and in the approach basedon using a simulation tool for the control system the testingoptions are much wider and easier.


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5.3 Current and future use of Automation Simulators

Using Simulation in Automation

Testing

Three (3) approaches used in the industry to implement theautomation functionality in simulation systems:

the approach based on using a simulation tool that simulatesthe whole control system (e.g. DeltaV or metsoDNA)

the approach of using real control systems or parts of them

the approach based on the use of soft controllers for


(e.g. ABB ).

5.1 Benefits of simulation-assisted automation testing

Research and Development Needs inAutomation Simulation

Standardization of automation Simulation terms.

Standardization of interfaces between automation systemsand simulators.

Easy and fast model generation.

Development of guidelines for practitioners in the area, i.e.automation engineers who do the testing.


inside automation systems to support simulation aidedtesting.

LN-1.1.4-Simulation of Industrial Processes

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