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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
• ProducBonSystemsModels– MatemaBcalModels–Topology– EnterpriseModels
• OpBmizaBoninProducBonSystems• ConBnuousProducBonSystems
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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
• CourseFormalia• ProducBonSystems– ConBnuous/Discrete/BatchSystems– ProducBonStrategies
• Produc4onSystemsModels– MatemaBcalModels–Topology– EnterpriseModels
• OpBmizaBoninProducBonSystems• ConBnuousProducBonSystems
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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
• CourseFormalia• ProducBonSystems– ConBnuous/Discrete/BatchSystems– ProducBonStrategies
• ProducBonSystemsModels– MatemaBcalModels–Topology– EnterpriseModels
• 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
• CourseFormalia• ProducBonSystems– ConBnuous/Discrete/BatchSystems– ProducBonStrategies
• ProducBonSystemsModels– MatemaBcalModels–Topology– EnterpriseModels
• 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
Step1:SelecBonofControlParameters
ControlParameter
Whattomeassure
ProducBon
Inventoryvariables
Surroundingvariables
Quality
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Step1:SelecBonofControlParameters
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
Step3:Controlstructure
Mightrequireprocessredesign:• Replacesensorsand/oractuatorsinordertomodifythedynamics.
•Movetheplacementofsensorsand/oractuatorsinordertoavoidBmedelays.
•Addsensorsinordertomeasureclosertoimportantdisturbances.
•
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Step3:Controlstructure
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
• ProducBonSystemsModels– MatemaBcalModels–Topology– EnterpriseModels
• 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