Market-Driven Systemsarchive.control.lth.se/media/Education/Engineering...– Matemacal Models –...

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Market-DrivenSystemsMarknadsstyrdaSystem

FRTN20Lecture1

Market-Drivensystems•  Aim

ToteachthebasicprinciplesforautomaBonsystemsinthemanufacturingindustriesandtheirdynamicinteracBonwithmarketfactorssuchasvariaBonsindemandandpricesforrawmaterial,transports,andinventory.Togiveinsightintocurrentproblemsandtrendsofcompaniesinregion,throughguestlecturesandprojects.ModernproducBoncompaniesinteractwiththemarketinmanyways,someexamplesareinternaBonalstandards,industrialtrends,fluctuaBonsindemands,andvariaBonsinraw-materialprices.

A/gekunskapomgrundläggandeprinciperförautoma:onssystemi:llverkningsindustrinochdessdynamiskasamspelmedmarknadsfaktorersåsomvaria:onerie>erfråganochpriserförråvaror,transporterochlagerhållning.A/genomgäsAöreläsningarochprojektgeinblickiaktuellafrågeställningarochtrenderhosföretagiregionen.Dagensproduk:onsföretaginteragerarmedmarknadenpåmångaolikasä/,någraexempelärinterna:onellastandarder,industriellatrender,varia:onerie>erfråganochråvarupriser.

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Market-DrivensystemsAimII:Thecoursehelpsfuturemanagerstounderstandtheroleandvalueofcontrol

inmoderncompaniesaswellastogivethemanintuiBonabouttheparallelsofcontrollingtechnicalsystemsandmanaginganenterpriseinthemarket.Assuchithelpstobuildabridgebetweenmanagersandengineers.

Kursensmålsä/ningärävena/hjälpafram:daledarea/förståreglertekniksrolloch

värdeidagensföretag,samta/geförståelseförparallellernamellana/styrae/teknisktsystemrespek:vea/ledae/marknadsföretag.Påde/avishjälperkursen:lla/skapaenbroemellanledareochingenjörer.

Market-DrivenSystemsAimIII:•  ToprovideamanagementperspecBveonindustrialproducBonandautomaBonsystems–  PartI

•  Toprovidesometoolsandmethodsthatarerelevantforfinancialengineeringingeneral

•  Gametheory•  Model-PredicBveControl•  DistributedControlusingPriceMechanisms

–  PartII

ReglerteknikAK PID

Market-DrivenSystems

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Contents

•  CourseFormalia•  ProducBonSystems–  ConBnuous/Discrete/BatchSystems–  ProducBonStrategies

•  ProducBonSystemsModels– MatemaBcalModels–Topology–  EnterpriseModels

•  OpBmizaBoninProducBonSystems•  ConBnuousProducBonSystems

Lecturers&Exercises•  CharloZaJohnsson–  [email protected]–  046-2228789–  Courseresponsible–  Lectures,projects

•  BoBernhardsson–  [email protected]–  LecturesonGameTheory

•  JosefinBerner–  [email protected]–  Exercisesandlaboratories

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GuestLecturers•  KristerForsman–  CorporateSpecialistatPerstorpSpecialtyChemicals–  IndustrialITandControl–  Guestlecture

•  AnnaLindholm– Modellon–  IndustrialIT–  Guestlecture

•  KurtJörnsten–  ProfatNorwegianSchoolofEconomics– ModernProducBonManagementandLogisBcs–  Guestlecture

Lectures•  13lectures

+onelecturewheretheprojectsareintroduced+twolecturesfortheprojectpresentaBons

•  Nominallecturehours:–  Mondays10:15–12:00inM:L1–  Fridays13:15–15:00inM:L1

•  Changes:–  Friday25/3ismovedtoWednesday23/3at10.15.12.00inM:L1–  Monday28/3ismovedtoTuesday29/3at10.15-12.00inM:L1

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Exercises•  Approx.13Exercises•  Nominallecturehours:

–  Mondays13.15-15.00in,M:M2–  Fridays15.15-17.00inM:M2

•  Changes:–  Friday25/3ismovedtoWednesday23/3at15.15-17.00inM:M2.

–  Monday28/3ismovedtoTuesday29/3at13.15-15.00inM:M2.

JosefinBerner

Laboratories•  Lab1:BatchControl–  4hours– Week4/4–8/4–  Signupatthecoursehomepage–  Responsible:JosefinBerner

•  Lab2:LinearProgr.andMPC–  4hours– Week25/4–29/4–  Signupatthecoursehomepage–  Responsible:FredrikMagnusson

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Projects•  Twotypes:–  ”Industrial”–  ”Department”

•  Learntoknowanindustrialcontrolsystem•  Ingroupsofaround4•  Projectsintroduced8Apr•  Projectspresentedinmid/endMay–  (datetobedecided)

•  Requirements:– WriZenreport–  OralpresentaBon–  Approx.oneweekofwork

Exams

•  MondayJune2,14-19,SpartaA,SpartaC•  Re-examinaBoninAugust

•  Closedbookexam

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CourseMaterial•  Folderwith–  Coursetexts–  Copiesofslides–  ExerciseswithsoluBons–  Labmanuals

•  Freeofcharge•  HandedoutonWednesday–  Thematerialwillbecompletedwithmatrialshandedoutatthelectures

•  Coursematerialalsoavailablethroughthecoursehomepage

CEQ•  ”WhathasthiscoursetodointheI-programme’sFinanceandRiskspecializa:on(toomuchautoma:on)?”–  ProducBonsystemareaveryimportantpartofSwedishindustryandseveralofyouwillprobablyendupasmanagersintheproducingindustry

–  ThecoursehasbeenremovedfromtheI-programme’sFinanceandRiskspecializaBonandisopentoallstudentsatLTH.

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CEQ

•  ”Coursematerialsystemdidnotworkwell.Fewstudentsmanagedtofilltheirbinderswithallthematerial.”– Allmaterialthatishandedoutandinthebinderisalsoavailablefordownloadfromthehomepage

Contents

•  CourseFormalia•  Produc4onSystems–  ConBnuous/Discrete/BatchSystems–  ProducBonStrategies



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Market-drivensystems

•  System=industrialproducBon•  Market-driven=interacBonwiththesurroundings/market– Prices– Demands– CompeBBon– LawsandregulaBons– Standardsandguidelines– Trends

IndustrialproducBonWhatindustrialproducBonsectorsarethere?•  Food&Beverage•  PharmaceuBcal•  Metal•  Pulp&paper•  ChemicalandPetroChemical•  Refining•  AutomoBve•  Biotechnology•  Machineparts•  Etc…

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IndustryvsAutomaBonlevel

IndustrialProducBonTheindustrialproducBonsystemsallhavethesameoverallgoal;

tomakemoney!

ProducBonProcess ProductsMaterials

•  Thisisdonebytransformingraw-materialsintoproductsthroughtheuBlizaBonofmaterial,energy,equipment,personnel/manpower.

•  MinimizeCAPEXandOPEX•  CAPEX–Capitalexpenses

•  Costsassociatedwiththeacquirementorupgradeofphysicalassetssuchasequipment,property,orindustrialbuildings.

•  OPEX–OperaBngexpenses•  Theongoingcostforrunningaproduct,business,orsystem

•  However,theconBnuous,discreteandbatchproducBonprocessesaredifferentinkeyaspectsoftheiroperaBons.

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IndustrialproducBon

HowcantheproducBonbeperformed?•  ConBnuous•  Discrete•  Batch

=>TherearethreetypesofproducBonprocesses

ConBnuousProducBonProcessesInaconBnuousproducBonprocesstherawmaterialsareconsumedin

aconBnuousstreamandaproductresultasaconBnuousouulow.

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ConBnuousProducBonProcessesGeneralCharacterisBcsofconBnuousproducBon

processes:•  ConBnuousflowofmaterial(ovenfluid-

based).•  ConBnuousproducBonofproduct,i.e.

conBnuousouulow.•  Open-endedproducBonruns.•  Theprocessismostoven”invisible”.•  Disassembly-orientedproducBonisnot

unusual.•  Theequipmentoperatesinsteady-state.

DiscreteProducBonProcessesAdiscreteproducBonprocessistheassemblyofpiecepartsinto

products.TheproductisadiscreteenBty.

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DiscreteProducBonProcesses

GeneralCharacterisBcsofdiscreteproducBonprocesses:

•  DisconBnuousproducBonofproduct,i.e.

discreteoutput.•  DisconBnuousflowofmaterial(ovenpieces

andparts).•  Assembly-orientedproducBon.•  StagedproducBonthroughworkcells•  WelldefinedproducBonruns.•  Theprocessismostoven”visible”.•  Theequipmentoperatesinon-offmanner.

BatchProducBonProcessesInabatchproducBonprocesstheproductismadeinbatchesorlots.

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BatchProducBonProcesses

GeneralCharacterisBcsofbatchproducBonprocesses:

•  ProducBonofproductsinbatches•  DisconBnuousflowofmaterials.•  ProducBonrundeterminedbyBme/

endpoint.•  ProducBongoesthroughstepsof

operaBons.•  Fluidanddryprocessing.

ProducBonStrategies•  Twomaintypes:– Make-to-stock

– Make-to-order

Abusinessproduc:onstrategythattypicallyallowsconsumerstopurchaseproductsthatarecustomizedtotheirspecifica:ons.Themaketoorder(MTO)strategyonlymanufacturestheendproductoncethecustomerplacestheorder.Thiscreatesaddi:onalwait:mefortheconsumertoreceivetheproduct,butallowsformore

flexiblecustomiza:oncomparedtopurchasingfromretailers'shelves.

Atradi:onalproduc:onstrategyusedbybusinessestomatchproduc:onwithconsumerdemandforecasts.Themake-to-stock(MTS)methodforecastsdemandtodeterminehowmuchstockshouldbeproduced.Ifdemandfortheproductcan

beaccuratelyforecasted,theMTSstrategycanbeanefficientchoice.

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Make-to-stock

RawMaterial Customer

Demand

Stock

•  Pushmodel•  Necessarywhenittakeslongertoproducethanthecustomer

iswillingtowait•  Reliesontheaccuracyofdemandforecasts.

–  Inaccurateforecastswillleadtolossesstemmingfromexcessiveinventoryorstockouts.

•  Approaches:–  MRP(MaterialRequirementsPlanning),MRPII(Manufacturing

ResourcesPlanning),ERP(EnterpriseResourcesPlanning),SCM(SupplyChainManagement)

•  Usingcontrolterminologythiscorrespondstofeedforward

Make-to-order

RawMaterial Customer

Demand

Stock

•  Pullmodel•  PossiblewhentheBmetoproduceisshorterthanthecustomers’

acceptablewaiBng•  DownstreamproducBonunitsareviewsascustomerstoupstream

producBonunits•  Shortchangeover/setupBmesanecessity•  SmallerbatchesàlessinventoryàshortercycleBmesandfaster

detecBonofdefects•  Approaches

–  JustinTime(JIT)producBon(Kanban,Toyota),Leanmanufacturing,….•  Usingcontrolterminologythiscorrespondstofeedback

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Make-to-StockvsMake-to-Order•  InpracBceitisovenacombinaBonofmake-to-stockandmake-to-order

•  Make-to-stockhasareputaBonofbeingslightlyold-fashioned

•  Make-to-orderhasbeenthefocusofresearchthelast10-15years

•  However,thecurrentlowcapitalcostshasmademake-tostockmoreinteresBngagain– Assumingthattheproductwilleventuallybesold–  ”Double-batching”

Contents


•  Produc4onSystemsModels– MatemaBcalModels–Topology–  EnterpriseModels


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ProducBonSystemModels•  MathemaBcalModels

–  Model-based•  DesignofproducBonsystem,inclproducBonunits•  Analysis•  Planningandscheduling(opBmizaBon)•  Reliabilityanalysis•  ……..

–  Alargevarietyofmodeltypes(determinisBc/stochasBc,discrete/conBnuous,linear/nonlinear)

•  EnterpriseModels–  A"model"ora"framework”whichrepresentstheenterpriseatone

pointinitslifecycle,isneeded.This”model/framework”iscalledanEnterpriseArchitecture.

–  Assistwithplanningandanalysisoftheenterprise,toselecthardwareandsovwareproducts,todesignorganizaBonal"reporBngstructures",andtostudyflowofmaterialsandinformaBonthroughtheenterprise.

–  Thefocusofthiscourse

MathemaBcalProducBonSystemModels•  Topology–  Showshowtheunits/machinesareconnectedandtheflowswithinthesystem

•  Machinemodels– ModeltheoperaBonofthemachines/unitswrt.producBvity,reliability,quality

•  Media/productmodels– Modelsthebehaviour/dynamicsoftheproductsflowingthroughthemachines

•  Buffermodels•  ModelsfortheinteracBonbetweenbuffersandmachines

•  Performancemeasures– MetricsquanBfyingtheefficiencyofthesystemoperaBon

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Topologies:SerialProducBonLine

•  ProducBonunits:– Machines,workcells,equipmentunits,processcell…..

•  Bufferswithstoragecapacity:– Materialhandlingdevices,e.g.,boxes,conveyors,autonomousguidedvehicles(AGVs),trucks,…

–  Buffertanks–  FilteroutproducBonrandomness(disturbances,variaBons,…)

BufferProducBonUnit

Topologies:SerialProducBonLinewithFinishedGoodsBuffer

•  FGB-FinishedGoodsBuffer–  Inventoryoffinishedproducts– FilteroutproducBonrandomess(disturbances,variaBons,…)

– CompensateforvariaBonsindemand

FGB

Demand

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Topologies:AssemblySystems

•  Twoormoreseriallines(”componentlines”)•  TwoormoremergeoperaBons– Componentsareassembledormixed

MergeoperaBon

GeneralTopology

RecyclesSplit

operaBons

SynchronousproducBonunits

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EnterpriseModels•  A"model"ora"framework”whichrepresentstheenterpriseatonepoint

initslifecycle,isneeded.This”model/framework”iscalledanEnterpriseArchitecture.

•  Thisframeworkcanbeusedtoassistwithplanningandanalysisoftheenterprise,toselecthardwareandsovwareproducts,todesignorganizaBonal"reporBngstructures",andtostudyflowofmaterialsandinformaBonthroughtheenterprise.

•  WithoutanEnterpriseArchitecturalmodel,execuBves,managers,andtechnologistsinanenterpriseareessenBally"runningblind":makingdecisionsbasedontheirpersonalpercepBonoftheenterprisewhichisovennotsharedwiththerestoftheorganizaBon.

HowcanindustrialproducBoncompaniesbemodeled?

•  PERA–PurdueEnterpriseReferenceArchitecture•  PERAwasdefinedin1980s.•  ThePERAgenericenterprisemodelseesanenterpriseascomposedofthreemain

components–  Physically(ProducBonFacility)–  OrganisaBonally(People)–  FuncBonally(ControlandinformaBonsystems)

•  UEML–UnifiedEnterpriseModelingLanguage•  UEMLisaniniBaBvefundedbytheEuropean

ResearchProgramsFP5andFP6.•  Theaimistoprovideanunderlyingformal

theoryforenterprisemodellinglanguages.AmajormoBvaBonwasenterpriseintegraBoninthefaceofawidevarietyofenterprisemodellinglanguages.

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PERA•  ThePERAmodeldescribesthecompletelifecycleofanenterprise;from

enterprisedefiniBon(whatshouldtheenterprisedo),throughconceptualengineering,preliminaryengineering,detailedengineering,construcBon,tooperaBons,andfromoperaBonsthroughdecommissioningtoenterprisedissoluBon(teardownofanenterprise).

PERA•  FaciliBes:describesthestructureofthecompanyanditsequipment.In

addiBontoagenericphysicalstructure,amoredetailedstructureisused:–  conBnuousprocessingfaciliBesaredescribedwith"ProcessFlowDiagrams”–  discretemanufacturingisdescribedwBhMaterialFlowdiagrams.–  batchprocessesaredescribedbysequences.

•  People:describesthepeopleworkingatthecompanyandtherealBonshipsamongsthem.TheorganizaBonalstructuremayberepresentedbyaseriesof"OrgCharts”.

•  ControlandInformaBonSystems:mayberepresentedthroughaControlandInformaBonArchitectureDiagram(CIAD)oraControlandInformaBonNetworkDiagram(CIND).

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OrganisaBonalModel(People)ofanEnterprise

•  Notincludedinthecourse

PhysicalModelofanEnterprise

ENTERPRISE

SITE

AREA

PROCESSCELL

UNIT

PRODUCTION UNIT

PRODUCTION LINE

WORKCELL

Lowerlevelequipmentused

inbatchoperations

Lowerlevelequipmentusedinrepetitiveordiscreteoperations

Lowerlevelequipmentusedincontinuousoperations

STORAGEZONE

STORAGEUNIT

Lowerlevelequipmentusedininventoryoperations

UNIT

Workcenters

Workunits

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PhysicalModelofanEnterpriseENTERPRISE

SITE

AREA

PROCESSCELL

UNIT

PRODUCTIONUNIT

PRODUCTIONLINE

WORKCELL

STORAGEZONE

STORAGEUNITUNIT

EquipmentModule

ControlModule

EquipmentModule

ControlModule

Device

ControlModule

Workcenters

Workunits

Example–AstraZenecaProducBonSites

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AstraZeneca,GärtunaProduc4onSite• ReceivingGoodsArea(red)• Produc4onArea(green)• ShippingArea(orange)

Example–AstraZenecaProducBonAreas

maycontainControlModule maycontain

maycontainEquipementModule maycontain

ProcessCell

maycontain

Unit

MUSTcontain

Site

maycontain

Enterprise

Area

maycontain

AstraZeneca

GärtunaProducBonSite

ProducBonArea

Example–AstraZenecaProcesscells

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maycontainControlModule maycontain

maycontainEquipementModule maycontain

ProcessCell

maycontain

Unit

MUSTcontain

Site

maycontain

Enterprise

Area

maycontain

Example–AstraZenecalowerlevels

FuncBonalModelofanEnterprise

Level4

Level1

Level2

Level3

BusinessPlanning&LogisBcsPlant Production Scheduling, Operational Management, etc

ManufacturingOperaBonsManagementDispatching Production, Detailed Production Scheduling, Reliability Assurance, ...

DiscreteControl

1- SensingtheproducBonprocess,manipulaBngtheproducBonprocess

2- Monitoring,supervisorycontrolandautomatedcontroloftheproducBonprocess

3- Workflow/recipecontroltoproducethedesiredendproducts.MaintainingrecordsandopBmizingtheproducBonprocess.

TimeFrame

Shivs,hours,minutes,seconds

4- Establishingthebasicplantschedule-producBon,materialuse,delivery,andshipping.Determininginventorylevels.

TimeFrame

Months,weeks,days,shivs

Level0 0- ThephysicalproducBonprocess

ConBnuousControl

BatchControl

Level5CompanyManagement

5- Receivesalesorders,assureshippingandcustomerrelaBons.

TimeFrameYears,Months

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FuncBonalModel–NNEExample

Historian System

Finance Management

Production Management

Maintenance Management

Learning & Training

Quality Management

Electronic Document

Management

Laboratory Management

MES Spec

Management

MES Resource

Management

MES Planning & Scheduling

MES Execution

MES Data

Collection

MES Analysis

MES Tracking

BMS System PEMS System DCS System SCADA System

PLC System

PAT System

Q

PRISM

S9

5 L

evel

2

S9

5 L

evel

3

S9

5 L

evel

4

Typicalcontrolhierarchyofachemicalplant(Skogestad)

Scheduling(weeks)

Site-wideopBmizaBon(day)

LocalopBmizaBon(hour)

Supervisorycontrol(minutes)

Regulatorycontrol(seconds)

Controllayer

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Typicalcontrolhierarchyofachemicalplant(Skogestad)-extended

Scheduling(weeks)

Site-wideopBmizaBon(day)

LocalopBmizaBon

(hour)

Supervisorycontrol(minutes)

Regulatorycontrol(seconds)

Controllayer

Planning(years,months,weeks)

Strategy(years)

KNOW-WHY

KNOW-HOW

Contents



•  Op4miza4oninProduc4onSystems•  ConBnuousProducBonSystems

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PlanningandScheduling•  Goodplanningandschedulingareoventhekeyto

successfulproducBon•  Decide

–  Amountofrawmaterial–  WhentoperformtheproducBon-scheduling–  WhichproducBonunitstouse–  WhichoperaBngpointtouse–  Howtodotheclosedloopcontrol

•  Example:Model-PredicBveControl(MPC)–  …

•  VariousopBmizaBontechniquescanbeused–  Linearprogramming,ModelPredicBveControl,Gametheoryetc.

Contents



•  OpBmizaBoninProducBonSystems•  Con4nuousProduc4onSystems

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ConBnuousProducBonProcessesGeneralCharacterisBcsofconBnuousproducBon

processes:•  ConBnuousflowofmaterial(ovenfluid-

based).•  ConBnuousproducBonofproduct,i.e.

conBnuousouulow.•  Open-endedproducBonruns.•  Theprocessismostoven”invisible”.•  Disassembly-orientedproducBonisnot

unusual.•  Theequipmentoperatesinsteady-state.

ExampleofaConBnuousProducBonProcess

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ThebasiccontrolenBtyinconBnuousprocessingisthePIDcontrollerandthefeedbackcontrolloop(ReglerteknikAK)

IniBally,companiesthatbecameinvolvedwiththeautomaBonof

conBnuousprocesseswherecompaniesthatmadeinstrumentaBons:Honeywell,Foxboro(todayInvensys),Bailey(todayRockwell),etc

+

-1

ProcessPIDcontroller

Howdowecontrolaplant?DesignofProcessandControlSystem

Step1:SelecBonofcontrol-parameters:chosethemeasured-variablesandsensors

Step2:SelecBonofmanipulatedvariables;selecttheactuatorsStep3:Controlstructure;combinethesensorswiththeactuatorsStep4:SelecBonof(opBmal)working-point(arbetspunkt)Step5:Controller;selecBonofcontrollerandtuningStep6:EvaluaBon:control,processandeconomy

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Step1:SelecBonofControlParameters

ControlParameter Whattomeasure

ProducBonrate Flow

Inventory-variables Gas–pressureLiquids–levelSolids-weightConcentraBons-analysisEnergy–temporpressure

Surroundingvariables Temperature–temperaturePressure–pressureConcentraBon-analysis

Productquality Physically-physicalproperBesChemical-analysis

Economics


ControlParameter

Whattomeassure

ProducBon

Inventoryvariables

Surroundingvariables

Quality

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ControlParameter

Whattomeassure

ProducBon Flow4

Inventoryvariables

Level1,6,10

Surroundingvariables

Temperature3,7,9Pressure5

Quality ConcentraBon2,8,11Temperature12

•  Shouldmeasurethecontrolparameter

•  SensiBvityandreliability•  Dynamiceffects•  Costo  CommonExamples:level-,

flow–,temp-sensorsandinstrumentsforanalysis

Step2:Actuators

Step1:Sensors

•  Themanipulatedvariables

shouldbecontrollable•  Capacity,precisionand

reliability•  Dynamiceffectso  CommonExamples:

Valves,pumps

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Step3:Controlstructure

Whatmakesaprocessdifficulttocontrol?•  Timedelays–  TheamountofBmeittakesfortheprocesstoreacttothechange

•  Lag– Ameasureofhowquicklyaprocessrepondtoachange(e.g.,volumeofatank).

•  Nonminimumphase(zerosinRighthalfplane)–  ThestepresponsestartsinanegaBveway.

•  Slowfeedbackloopbutquickdynamicsinthedisturbances


Mightrequireprocessredesign:•  Replacesensorsand/oractuatorsinordertomodifythedynamics.

•Movetheplacementofsensorsand/oractuatorsinordertoavoidBmedelays.

•Addsensorsinordertomeasureclosertoimportantdisturbances.

•

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Thereareseveralpossiblecontrolstructures.Oneexampleis:

Pairsensorswithactuators•  ProducBon,Fut–ouulow•  Inventory,Lref–inflowB•  Surrounding,Tref–flowtothe

jacket•  Quality,Cref–inflowA

Step4:SelecBonofworking-point

•  Whataresuitablenumbersonthereferencevariables?

Step5:Controller

•  Selectcontrollertype(e.g.PID)•  Tunethecontrollers,i.e.,findvaluesfortheP,I,andDvariablesofthecontroller.

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Step5:Controller

Step6:EvaluaBon

•  EconomicsIsthebudgetfortheprocessandcontroldesignphasemet?

•  SafetyIstheplantsafeenoughtorun?

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ImprovementsofConBnuousProducBonPlants

•  ControlperformanceThecontrolperformanceisovenregulatory,e.g.holdingameasuredand/orcomputedquanBtyatitsdesiredvalue.

•  ProcessperformanceTheprocessperformanceisameasureofhowwelltheprocessmeetsitsobjecBves.ThiscouldforexamplebeproducBonrate.

•  EconomicperformanceTheeconomicperformanceismeasuredinfinancialterms,e.g.,financialproducBonratewhichisexpressedasMoney(Euros/dollars/SEK)perproducBonBme.

ControlImprovement

TheplantimprovesthecontrolofconcentraBoninthereactor.ThevariaBonintheconcentraBonisreducedby40%(controlimprovement)

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ProcessImprovement

TheplantimprovesthecontrolofconcentraBoninthereactor.ThevariaBonintheconcentraBonisreducedby40%(controlimprovement).ThecontrolimprovementsallowtheeliminaBonofdelaysforproductanalysis,sotheplantcannowdeliver10%moreproductperday(processimprovement).

ProcessImprovementCommonprocessimprovementfactors:• Higheroutput• LoweruBlitycost• BeZeryield• Fewerunwantedbyproducts• Lesslabor• BeZerquality

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EconomicImprovement

IfthereismarketfortheaddiBonalproduct,therewillbeaneconomicalimprovement.IfthereisnomarketfortheaddiBonalproduct,therewillbeaneconomicalnetlosssincetheadiBonalproductwillrequireaddiBonalrawmaterial.

income

income

Cost Cost

Contents•  CourseFormalia•  ProducBonSystems–  ConBnuous/Discrete/BatchSystems–  ProducBonStrategies


•  OpBmizaBoninProducBonSystems•  ConBnuousProducBonSystems•  Summary

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PhysicalModelofanEnterprise

ENTERPRISE

SITE

AREA

PROCESSCELL

UNIT

PRODUCTION UNIT

PRODUCTION LINE

WORKCELL

Lowerlevelequipmentused

inbatchoperations

Lowerlevelequipmentusedinrepetitiveordiscreteoperations

Lowerlevelequipmentusedincontinuousoperations

STORAGEZONE

STORAGEUNIT

Lowerlevelequipmentusedininventoryoperations

UNIT

Workcenters

Workunits

ConBnuousProducBonProcesses

FuncBonalModelofanEnterprise

Level4

Level1

Level2

Level3

BusinessPlanning&LogisBcsPlant Production Scheduling, Operational Management, etc

ManufacturingOperaBonsManagementDispatching Production, Detailed Production Scheduling, Reliability Assurance, ...

ConBnuousControl

1- SensingtheproducBonprocess,manipulaBngtheproducBonprocess

2- Monitoring,supervisorycontrolandautomatedcontroloftheproducBonprocess

3- Workflow/recipecontroltoproducethedesiredendproducts.MaintainingrecordsandopBmizingtheproducBonprocess.

TimeFrame

Shivs,hours,minutes,seconds

4- Establishingthebasicplantschedule-producBon,materialuse,delivery,andshipping.Determininginventorylevels.

TimeFrame

Months,weeks,days,shivs

Level0 0- ThephysicalproducBonprocess

DiscreteControl

BatchControl

Level5CompanyManagement

5- Receivesalesorders,assureshippingandcustomerrelaBons.

TimeFrameYears,Months

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Thankyoufortoday

Market-Driven Systemsarchive.control.lth.se/media/Education/Engineering...– Matemacal Models –...

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