Raw Mix Prep 3bhs 211545 Reva Lr

8/3/2019 Raw Mix Prep 3bhs 211545 Reva Lr

1/8

Raw Mix Preparation

IdustrilIT

Solutios or the Cemet Idustry


2/8

OptimizeIT Rw Mix Preprtio

OptimizeIT Raw

Mix Preparation

is ABBs answer to

feed quality pro-

blems. Our whole

experience and

know-in the field

of cement produc-

tion and advanced

process control

has been merged

to create real solu-

tions for our cus-

tomers.

Icresed proits (5%10%)

Icresed productio (3%10%)

Eergy svigs (3%7%)

More stable product quality (10%20%)

BEnEfITS

OPTIMIZED PROCESSOPTIMIZED PROCESS

Application Support

Training

Product Support

OptimizeIT

Raw Mix

Preparation

Pre-blending Optimization

Knowledge Based

Solutions Technology

Application

Commissioning

Configured

Strategy

Package

Raw Mix

Preparation

Raw Mix Optimization

Raw Mill Optimization

Wht is OptimizeIT Rw Mix Preprtio?

Theconsequencesofpoorlypreparedrawmeal

arewellknown.Highlimecausesmealtobe

burnedharderandrefractorylifedrops.High

alkalinesmaycausecycloneblockageandrestrict

theuseofthecementproduced.Moisturecontent

risesandsodoesenergyconsumption.Andof

course,oversizemealbringslowreactivityand

burnability.

Asleadersinkilncontrolandoptimizationusing

OptimizeITExpertOptimizer,ABBunderstands

thewoesofill-preparedrawmealenteringthe

kilnandthejoysofwell-preparedmeal.Fluctu-

ationsinthechemicalcompositionofexcavated

rawmaterialsareunavoidableatthestartofthe

manufacturingprocess.However,ifundetected

orleftuncorrected,stablekilnoperationbecomes

difficult.

ThatiswhyABBhasdevelopedOptimizeIT Raw

Mix Preparation (RMP):toofferrawmixquality

assurancetotheleadersofthecementindustry.

OptimizeITRawMixPreparation(RMP)depictsa

comprehensivesetofsoftwaresolutionsthatcover

allstagesoftherawmixblending,fromthequar-

rytoitsgrinding,makingsurethatyourquality

targetsarereachedatthelowestpossiblecost.

RMPisafullyintegratedsolutioninABBsCPM

cementportfolio,consistingofKnowledge

ManagementSystems,LaboratoryInformation

ManagementSystems,AutoLabandofcourseour

solutionsforkilnandmilloptimization.ThusRMP

iscreatingthebasisforthemodulargrowthand

developmentofyoursystem,adaptedtoyour

plantsneeds.


3/8

Three optimizati-

on modules work

in concert to help

the cement plants

to achieve their

desired quality,

cost and safety

targets.

OnlineMeasurement

Composition Control

Limestone/Clay

Composition Control

OnlineMeasurement

RawMill

HomogenizingSilo

Kiln FeedPre-blending

Optimization ModuleRaw Mix

Optimization ModuleRaw Mill

Optimization Module

Sampler

OfflineXRF

How does OptimizeIT Rw Mix Preprtio

work?

RMPachievesthegoalofminimizationoffeed

chemistryfluctuationsatthelowestpossiblecost

byconcatenatingthreestrongfunctionalmodules.

Thesemodulesproducevaluetoourcustomers

asstandalonesolutions,butthemaximumbene-

fitsandsynergiesarereachedwhendeployed

together.Theyconformauniquesolutioninits

strength,performanceandcompleteness.

Pre-bledig Optimiztio

Thequarryfluctuationsaresmoothedearlyin

therawmealpreparationprocess,namelyatthe

pre-blendingbeds.Optimumproportioningof

thedifferentrawmaterialsonthecombinedpre-

blendingbedisachievedwiththeABBPre-blen-

dingOptimizationModule.ModelBasedControl

technologyisusedtoitsfullstrengthinorderto

copewiththechallengesposedbythematerial

propertiesvariabilityandthetimedelaysinherent

tothesystem.

Rw Mix Optimiztio

TheRawMixOptimizationModulereduces

andcontrolsshort-termfluctuationstothetarget

valuesbyoptimizingandcontrollingtherawmeal

materialproportionsintherawmillfeed.Asin

theformermodule,ModelBasedControltechno-

logyplayshereacrucialroletoattainthedesired

qualitytargets.Withthehelpofmathematical

modelsthismoduleisabletoforeseecomingqua-

litydeviationsinthemillorsilos,orforinstance

findremedytofeedersmalfunctions.Thispermits

implementationofpredictiveactionsratherthan

reactiveones.

Rw Mill OptimiztioTheRawMillOptimizationModuleachievesstable

milloperationatthemaximumeconomicproduc-

tionrateforthefineness,moisture,andchemical

compositionrequired.Short-termfluctuationsare

dampened.Theoptimizationthereforesupports

boththeoperatorsandthoseresponsiblefor

qualityalike..

Tirelessly supervises desired

process prmeters

Uchlleged rectio speed

Cosistetly tkes the best decisio

Executes my smll chges s

opposed to ew lrge chges

Immeditely recogizes

borml coditios d cts

ccordigly

BEnEfITS


4/8

Pre-bledig Optimiztio Module

ThePre-blendingProportioningModulebalan-

cestheanalysisvalueswiththecorresponding

quantityvaluesofthecombinedpre-blending

bed.TargetvaluesareusuallyCaOand/orAI 2O3.

Thecrushedmaterialsareanalyzedusinganon-

lineanalyzer,oralternatively,samplesregularly

taken,automaticallyprocessedandanalyzed.In

automaticmodethefeedersreceivecalculatedset-

pointsvalues.

ThePre-blendingModellingModuletracksthe

rawmaterialflow.Amathematicalmodelisbuilt

usingthechemicalcompositionandthelocation

oftherawmaterialinthepre-homogenization

bed.Duringthereclaimingprocess,themodule

deliversthechemicalcompositionofthereclai-

medrawmaterialtorefinetheperformanceofthe

RawMealProportioningModule.

Thecontrolalgorithmsaredesignedtodealwith

longtermdisturbancesmakingsurethatmostof

theproblemscanbecorrectedattheirorigin.On

theotherhand,thesolutionissuchthatamaxi-

mumofrobustnessandreliabilityisguaranteed

atalltimes.

Thismoduleisthefirststeptowardshomogeniza-

tionofthematerialchemistry.Itsaimistoreduce

mediumtermfluctuationsofthematerialproper-

tiesandtopreparethegroundforfurtherimpro-

vementsusingthesubsequentmodulesavailable

inthesystem.

Erly smoothig o log- d

medium-term compositios

Mthemticl modellig o

pre-bleded structures

Correltio with modellig whe

reclimig

BEnEfITS

The Pre-blending

Optimization

Module tackles

quality problems

very early at the

root cause by hel-

ping to achieve

the best possible

bed of raw mate-

rials.


5/8

TheRawMixOptimizationModuleaimsforthe

lowestpossibledeviationsfromthequalitytargets

attheconveyorbelts,themillandhomogenizati-

onsilos.Thisisachievedviaonlinecontrolofthe

weighfeederratesactiveattheplant.

Theoptimizationisadaptedtoproducestable

rawmealcharacteristicsenteringthekiln,using

regularlytakensamplesfromlaboratoryoronline

analysers,feedingadigitalcontrolalgorithm.

Therawmixchemicalcompositioncorresponds

tothequalityrequirementsexpressedeitherby

thespecificlimestandard(LS),silicamodule(SM)

andaluminamodule(AM),orbythepotential

clinkerphasesC2S,C3S,C4AF,C3A.Bothgroups

ofmagnitudescanbederivedfromthemainraw

mixoxidesCaO,SiO2,AI2O3andFe2O3.

Rw Mix Optimiztio Module

Thecontrolalgorithmisbasedonthelatest

controltechnologieslikeModelPredictiveControl

(MPC)usingMixedLogicalDynamic(MLD)

processingandgraphicalmodelbuilding.This

allowsexplicitconsiderationoftimedelays,

actuatordynamics,planttopology,etc.Theresult

isthebesteversolutioninthemarketplace.

Theoptimizationallowstheprioritizationand

tuningofdifferentgoalslikerawmaterialcost

optimizationandachievementofdesiredquality

targets.Italsoallowsyoutoreducethesensitivity

tomeasurementnoise,specifyfeedervariability,etc.

Optimiztio o rw mix chemicl

compositios

Miimize rw mteril costs

Reduce mucturig costs

dowstrem

Itertiolly recogized qulity

stdrds

BEnEfITS

The Raw Mix

Optimization

Module executes

online control of

the weigh feeders

in order to gua-

rantee the optimal

trade-off between

deviations from

quality targets and

material costs.

Based on state-

of-the-art control

technology, it

offers optimal

results and high-

est robustness.


6/8

Rw Mill Optimiztio Module

TheRawMillOptimizationoptioncontrolsboth

thetemperature,thefeedratetothemillandthe

separatorspeedinordertoachievetherequired

throughputforkiln.Wherestartingthemill

requiresdamperstobemoved,tochangegas

flowpaths,themodulewillalsorespondtothese

effectstokeepthesystemstable.

TheRawMillOptimizationModulestabilizesmill

operationandthencontinuouslyoptimizesits

mainprocessvariablesofthroughput,particle

sizeandenergyconsumedrelievingoperators

oftediouscorrectiveactions.Stabilitycontroluses

afeedcontrolstrategytoobtainastablegrinding

process.Freshfeedoptimizationdeterminesthe

millpowerconsumptionsetpointthatgivesthe

highestfreshfeedrate.Finenessandmoisture

controlareincluded.

Theprinciplebywhichthismoduleprovides

benefitsisasfollows.First,stabilizationofthe

keyprocessparametersisachieved.Notethat

themoduleimplementssmallactionsfrequently,as

opposedtotheinfrequentlargeactionstypicalof

humanoperator,theresultisamoresmoothope-

ration,largerproductivity,lesswearandtear,etc.

Inasecondstep,theMillOptimizationModule

movestheprocesstowardsitsconstraints,seeking

optimalsetpointsintheeconomicsensewhilestill

meetingalltheconstraintsoftheprocess.

Processsafetyissuesaretakenintoaccountauto-

maticallymakingsurethattheplanttechnicaland

humanassetsarenotjeopardizedatanypointin

time.

Stble opertio o rw mills

Mximum ecoomic productio rtes

fie tuig o prticle size d mois-

ture cotet

Opertor Support d Triig

BEnEfITS

Rely on the Raw

Mill Optimization

Module in order

to obtain maxi-

mum operational

stability, highest

throughput and

safety.


7/8

RMP Cotrol Techology

Pre-blendingbed

Feeders Raw mill Homogenizationsilo

Quarry

Long termfluctuations

Kiln

Quality

Middle termfluctuations

Short termfluctuations

ZeroShort termfluctuations

Pre-blendingOptimization

Module

Raw MixOptimization

Module

Raw MillOptimization

Module

RMPisbasedonthemostmoderncontroltechno-

logiesavailable.Thesystem

Usesamathematicalmodelsoffeeders,con-

veyorbelts,mills,andsilos,etctopredictinto

thefuturetheeffectofdifferentcontrolmoves

pickstheoptimalonesforapplicationinthe

plant.

Forcreationofthemathematicalmodelalibrary

ofcomponents(feeders,conveyorbelts,silos,

mills)isavailabletoconfigurethecustomerappli-

cation.Thisisdoneusinghighlyefficientgraphi-

caltoolsthatviadraganddropoperationscreate

theoverallplantlayout.Generationoftheoverall

processmodel,optimizationproblemsolvingand

simulationofresultsistakenoverbythesoftware!

RMP sotwre key cts

RMPisbasedonthemostmodernsoftware

technologiesavailable:webservers,thinclients,

graphicalmodelbuilding,OPC,latestWindows

version,etc.Thisensuresmaximumperformance

andlowestpossibleownershipcosts.

DataacquisitionandStorage

Standardinterafacestoprocessandonline

analyzers

IndustryspecificOracledatabasestructure

Databackupandrestorefunctions

Control

Rawmillcontrol

Closedloopcontroloffeedersetpoints

Costminimization

Constraintsatisfaction

HumanMachineInterface

Latestwebtechnology:server-thinclient

architecture

Basicsetofstandardreports,processdis-plays,trendsandmenus

OptimizeIT is

an outstanding

robust solution for

quality issues at the

cement plant. It puts

the most modern

software and control

technology at the

service of our

customers.

Ehced process stbility

Better respose to disturbces

Compestio or delys i

coveyor belts

Hdlig o delys i smplig,

X-Ry lysis, etc.

Recogitio d correctio o weigh

eeder errors

Predictio o moduli vlues i the

mill d the silos

fEaTURES


8/8

3B

HS211545ZAB

E01/Rev

A(07

.06500Pomca

ny

s)

stablecoatinginthekilnwithstablerawmealfedtothekiln

formationoffavourableclinkerphasesgrownfromraw

mealwithconsistentproperties

kilnoptimizationhasfewerfluctuationstocopewith

cementisgroundtohighqualityfromconsistentclinker

qualitywithwell-balancedphases

ABBassuresqualitywithacomprehensivesetofsolutions

fortheautomationandoptimizationofrawmealpreparation.

OptimizeIT Raw Mix Preparation

Rawmixpreparationisthequalitykeycontrolparameter

upstreamforstable,continuousmanufactureofhighqua-

lityclinkerandcement.Downstreamqualityandupto5%

productionincreasesorsavingsoriginatefromABBsqua-

lityassurancesystemOptimizeITRawMixPreparation.The

reasonsareclear:

ConsultABBonhowtooptimizeyourupstreamoperations.

aBB Switzerld LtdCH-0 Baden DttwilSwitzerlandPhone: +1 (0)8 8 8 Fax: +1 (0)8 8 [email protected]

www.abb.com/cement

Documents

Raw Mix Prep 3bhs 211545 Reva Lr