MODEL.BASED OPERATION OPTIMISATIONOF GTASS METTING FURNACES

M. DA GRACA CARVAIHO-, A. p. xEtM*, M. NOGUETM**lnstituto Superior T6cnico - Lisboo (portugol|

plonts is increosing os some moioisocrol, economic, energetic ondenvironmentql consfroins oru mor"ond more offecting the gloss indu-stry. Growing oworeness for sofer,cleoner, checper, lighter, foster onjbetler production hos iurned theinveslment in Reseorch ond Deve-lopment, o strotegic priorify for fhemodern gloss industrv. This DoDeris qimed of discussing the mojel-bosed conrrol technoloiie, fo, gL;,furnoc-e. operotion optimisorioi osport of this R&D efforr.Speciol demonds in refroctories,burning syslems, furnoce or.hit".jfure, preheoting devices, instrumen-fofion -ond control ore good exom-ples of fields where rhe-technoioo,,tronsfer from other industriol orZlcesses is not stroiqhtforword.This, is.nowodoys- hoppening in thetreld of control technologies, whenrecently developed physiJolfboseJmothemoticql models stort lo beport o[ odvonced control ,vrtumond the development of new:."tuo|ond op-erotion stroiegies is one ofthe.solest woys to improve theequrpment efficiency.

he.pressure to improve the ope-rotion efficien.y of gloss moking

' l.S.T. - Mechonicol Engineering Deporr_ment Lisboo, Porluool "" lrMDlARE,'Reseoich & Development inEngineering ond Environm""i, frj. "-2ZB0 Oeiroi, portugol

ler contoiners with increosedstrength ond durobility. ln the soe-ciol glosses sectors, the indusrrv issubjected to o boord rong" of ne*demqnds. All these reqJirementswill impose speciol needs to im-prove the operotion process ond in-troduce new complexities in the pro-duction choin. This is onother reo-son which exploins why control sy-stems in gloss industry ore beco-ming o strotegic R&D topic (3).

2 - GI.ASS FURNACE MATHEMATI.CALMODETTING

ln this chopter o simple ond shortclqssificotion of the modelling roolsused in odvonced control strJteoiesis proposed to help the undersLn-ding of the further'presenrotion ofmodel-bused control olgorithms.

ldentificotion models - ln rhis mo-dels, process doto is freoted tvoi-colly by block box module *hur"stondord functions ore odiusted toreproduce doto identified irom theindustriol system. The flexibiliv rohondle o lorge number of indusiriolsystems ond the proximify to the in-dustriol system oie the roin oduon-toges of these models. Following thesome opprooch, more recendy neu-rol networks beins used to'buildidentificotion mod6ls. Appticorionexomples in gloss industry. simultr:-.neous temperoture ond outlel goscomposition on-line prediction toie i.

I .INTRODUCTION l.l - The need of modern controtsyslems for complex processes

The development of odvonce controlond supervision syslems ore beco-ming on importont focbr in helpinqgloss industry copoble to oclrieulslrotegic developments in the fol-lowing directions (1, 2l: to morketnew gloss.products (ultro-light con-toiners, ultro-thin ponels

"tc.); tomeet environmentol regulotion otlow cost (ovoiding the usi of expen-sive pollution controlling devices); toprotect the workers environment ondsofety (meeting emerging sociol); toreduce the equipment size, com-plexity ond degrodotion (loweringinvesiment cosfs|; to decreose thignergl ond row moteriols consump-tion (lowering operotion costs); ioimprove the product quoliry ([ee-ping low cosrs); to flexibilize theproduction choin (responding to hemorketing demonds).'

1.2 - The need of modern controls.ystems for sophisticoted gloss pro-ducls

Future trends in gloss industry orestrongly reloted wirh the devlloo-ment of new products. ln the flotgloss sector the mqrkets qre moreond more demonding for muhi-functionol glozing. tn .o"ntoine, glorslhe response to,the competitio-n ofmetols ond polymers conloinersseems to be the development of ligh-

INIERNAIONAL GIASS JOURNA|. {1996) . No. 89 3t

used in.the regulotion of fuel iniec-tion ond oir/fuel rqtio.

Single equotion physicolly-bosedmodels - Simple lows ore odiustedto describe the behoviour of indu-striol systems through the correlo-tion of process doto. From o pre-viously known relotion between oprocess poromeler ond o porticulorfeoture of the industriol system, omothemoficql function is sei-up ondodiusted with meosurements. Appli-cotion exomples in gloss indusiry:inslontoneous debrminotion of fuelefficiency using temperolure ondmoss flow roie meosurements.

2.1 - Physicolly-bosed simulotionmodelsThese models ore bqsed on comolexnumericol solvers for the eouotionsthot govern the behoviou, of th" r.e-levont physicol phenomeno occur-ring in the industriql equipment.The procticol use of these models incontrol of industriol gloss meltingfiurnoc-es is presenily giowing os thicost of these models in control of in-dustriql gloss melting furnoces ispresently growing os ihe cost of os-socioted hordwore is becominglower. Howeuer, only very recentlidedicoted control tyrtert'boted onthese modelling tools stort beingovoiloble (4, 8)]Exomples of possible opplicotions moy'be given osfollowst- Optlmal operotion strofegres. The

on-line generotion o[ operotionscenorios to be used in ihe outo-motic seorch of optimol workingconditions.

- Process dalo reconstruction.Dedicoted three-dimensionol nu-mericol models con be used tocolculote, ofFline, non occessibleprocess dolo.

- Experl systems.Soph.isticoted modelling toolsmoy be used to build or-to em-body knowledge-bosed systemsport of expert systems which conbe used to ossist the operotion.

- Tomogrophic modelbosed obser-vation.Dedicoted firee-dimensionol mo-dels con be used to reconstructfields of relevont vorioble using

os input the current stote of thefurnoce operotion.

- On-line operotion optimisoton.Simplified' ond dedicoted muhi-dimensionql models when cou-pled.with optimisofion olgorithmscon be used for the seFup of on-line optimisotion loops.

3 - MODET.BASED PREDICTIVECONTROT OF GTASS.MAKINGSYSTEMS

ln this chopter some exomples ofidentificotion model-bosed predic-tive controllers ond of phvsicollv-bosed model utilisotion' in' oduol-ced control strotegies ore given.tdentifi coti on- roiel bo s"d predi ctivecontrollersTroditionolly, mosl industriol proces-ses were controlled in o orimoryloop by loop bosis where'r"u"rJllocol set-points were regulotedusing odjusted Proportionol, lnte-grotive, Derivotive (PlD) controllers.This wos, mostly, o single-input/sin-gle-output opprooch. However, oc-cordingly to the current demonds ofquolity, flexibiliry, efficiency ond so-fefy imposed to the industriol pro-cess, clos.sicol cgntrol strolegiesproved to be insufficient. luis Ayolo(9) presented o structured logiccontioller for the foreheorth temJe-roture control. ln this *ork, expe-riences on the development of FtObosed controllers ore comporedwith srructured logic bosed control-lers. PID controllers proved to beunoble to odequotely sotisfy oll theconirol requirements without opero-tor intervention due to the eflect oidisturbonces from preceding zones.Feedforword conhol wos piesentedos on ohernotive to occommodolethe upstreom disturbonces. Corefulmodelling of the foreheorth processwos proposed. The use of odoptiveself tuned or, olternoiiuely, on:linetuned model-bosed controllers wosinvestigoted.A similqr problem in the gloss mel-ting production is the regulotion ofthe gloss temperoture in floot olossmelting tqnk outler. The hJouvgloss-melt inertio ploys o decisiverole in the behoviour of the outlettemperoture. Tokofumi lto ond Shoii

lnoboyoshi (10) proposed on odop-tive modei-bosed control strotegy toreduce temperoture instobility in ofloot gloss melting furnoce. A pro-cess computer, networked to oworkstotion, wos used to cqlculotethe eslimoted volues of the identifi-cotion modei. model onolvsis ondcontrollers tuning were done in theworkstotion. Promising resuhs wereobtoined, olthough, siobilising con-trol by simple identificotion modelsdoes not ollow the optimise the ope-rotion os required for such o com-plex process. Artificiol intelligencetechniques were suggested i; (,l0)os o bosis for the development ofoptimol process control.A fully block-box opprooch wos fol-lowed in the development of onodoptive predictive control proce-dure for the gloss melting furnocebottom temperoture by J-F. Simonond V. Wertz (1 l). Historic treot-ment of process doto reportinggloss qroliry levels wos done to finithe correct temperoture set-points,speciolly bottom temperoture set-point, for good product quolity. Acoscoded control strotegy in threel-evels wos proposed. The moior dif-ficulties ore: to hondle the lorgethermol inertio of the melting tonkond to bolonce the big relotive im-portonce of perturbotions. An iden-tificotion model wos developed ondused for conlinuous testing of thebest crown temperoture profile tobe used for the more stoble bottomtemperoture reponse, Afeedforword compensotion of pre-dictoble voriotioni ond o feedbockcompensotion o[ the unpredictobleperturbotions were sel. A modelod[ustment procedure wos used tokeep fte model predictions closer tothe furnoce behoviour. This control-ler wos tested with promising resultsin two cross fired furnoces. A simi-lor opprooch wos olso proposed byToichiro Nokogowo ond Tokio Ki-muro (12) to control the bottomtempe-roture, together with o sugge-sted lusion, in o multi-vorioblehybrid control system, of quolitotiveond quontitotive process doto.Aimed ot overcoming the difficultiesossocioted to the regulotion of fullymu.lti-input/multi-output processesin bosis of conventionql identifico-

32INTERNAIIONAI. GIASS JOURNAT (l 996) - No. 89

lvlo D E L- B As E D o P E RAT I o N o pr t MrsAiloN o f G as s tvlE LT t N G FURNA cEs

tion-model bosed controllers, ShiJing Zou. ond Chen yong yi (13)proposed o Fuzry Logic -ontrolleito regulo-te o gloss tubing process.A single fuztllogic contrj ltop ho,been creqted to regulote the glosstubes outside diom"-te, in o do"nnerprocess.A very interesting first ottempt ofcombining, in o control qnd supervi-sion hierorchicol system, plD 6osedlocol control loops, neurol networkbosed prediclive zonol control ondo fuzrylogic wos presented bv D.K.Pirovolou ond co-ourhors (l{. Thismethodology wos opplied to the op-timol control of o <gos heorth> usedin monulqcturing of outomobiledoor windows, o process where thequolity requirements ore very strict.The so-colled <gos heorth>> in o sortof tunnel kiln which con be devisedinto o number of zones where locolcontrol loops for top ond bottomlemperotures ond pressure wereused. A polynomiol neurol networkwos used os on identificotion modelcopoble to hondle with the processdjmensionolly ond complexiiy. Soti-stoctory results in determining theoveroll process set-points ondlocolcorrections to the PID controllers set-points were roported in (14). Anodditionol importont feoture wqs thecopocity of preventing operotion di-sturbonce propogotion olong thetunnel kiln limiting the impoct ofproduction instobilities ond'uncon-trolled fluctuotions.

dimensionol models mqke it to beo priority tool for the treotment ofstrongly multi-input/multi-outputsituotions"

- the physicolly-bosed models relyon the soluiion of the octuol ohvsi-col phenomeno. Thus, its prejic-tive copobility ollows to evoluotethe system reoctions under opero-ting conditions.

The recenfness of the phvsicollv-bo-sed models use in industriol'oro-blems solution mqy exploin whyonly o very few oppiicotions in conltrol of gloss melting units hove beenpresented yet. Below some pioneerworks in these field ore referied.E.D. Former {15) developed o mo-del-bosed odoptive contiol sirqteovfor the optimol control of the fr"l Ji-ficiency in the gloss melting furnoce.This system wos oimed ot minimi-sing, on-line, the fuel consumption.A physicolly-bosed ollows to visuo-lise the instonloneous enerqv effi-ciency ond estimote the NO>iformo-tion. A conventionol odoptive con-trol technique wos used to moximisethe energy efficiency, nomely tokinoprofit from the use of disiributeiburner control.R. Sims presented ('16) o supervisionsysiem for the foreheorth operotion.Set-poinfs for the loco.l control loopswere corried out by the supervisionsystem. An on-line odiusted phvsi-colly-bosed model is used in'threemoin olgorithms: temperoture stobi-lisotion, temperoture homogenising,;ob chonge operotion ossistoncemodule. Results of the utilisotion offiese three functions were presenledin ('16).

for control, speciolly to improve theproduct quolity. ln thot work, sophi-sficoted modelling tools hove beenused to obtoin operotion rules.Those rules were used to form oknowledge-bose.system port of oninnovotive control strotegy oimed toensure high levels of gloii quolity. Atuzzy logic controller hos beenodopted to supervise the furnoceoperotion. A procticol exomplewhere the response of o gloss-mel-ting furnoce to colour chonges hosbeen optimised through thoicontrolshotegy is presented in (l B).The overoll gloss melting choin is ocomplex ond.sensitive sysfem. ltsreoctions ore broodly zone-fo-zonecorreloted ond strongly non-lineor.These ospectr ore dri"uing the deve-lopment of sophisticoted model-bo-sed control strofegies, nomely usingin neurol networks, fuzzy conlroltheory ond physicolly-bosed mo-dels, os it could be drown from theobove described contributions.

4 - APPTICATION EXAMPTES

Some exomples of model utilisotionfor gloss melting operotion optimi-sotion ore given in this poper. Thefirst two opplicotion exomples con-cern the utilisotion of o ohvsicollv-bosed dynomic model for both ol-line optimisotion ond stobilisotion.An exomple showing the three-di-mensionol model copobilities for on-line ossessment of on ory-fuel mel-ting furnoce performonce'is olso gi-ven.3.1 - Physicolly-bosed model

utilisotion in odvqnced conhol sho-legies

Physicolly-bosed models present th-ree mojor odvontoges for use incontrol:- the physicolly-bosed models ollow

the diognostic of the industriol sy-stem operotion beyond the ovoilo_ble process doto, like the thermqlefficiency, for instonce.

- the shongly coupled systems (hi-ghly multi-input/multi-output sy_stems) ore noi eosily occommodl-ted by identificotion models, evenusing neurol nefworks. The spotiolresolution ond the coupled'cho-rocter of physicolly-boied three-

An other exomple of the phvsicollv-bosed models use in gloss'melti,ig 4.1 - A physicoltv-bosed dynomic.s1stems,

control is sivei pr Ni.olol ,"a"r'iJ*i"."lii"il"LJrriii,Vonondruel (ond co-outhors) (12).ln fhol p,op"t o. conhol function is A physicolly-bosed honsienr model-L:"ff::i 1i b,osis of resutrs of non- tinil root ;"t;J;;h'on-op,iriro-steody,three-dimensionol modelling rioi orgorirh; ;; ;;;;i5'ro^i-ot o gloss melting tonk. This work mise qomo aqcanli^l L,* ^^^_-^^.^of o gloss melting ionk. This mise some essentiol but non-senso-::^"T:1, ot finding the rime re- red ft.,rnoce operotion poromerers.po.nse constonts of temperoture ondvelocity qt severol locotions wheremeosurements in reol conditions 4,2 -Thephysicoily-bcsed dynomicwould not be possible. modelR. Bouer (ond co-outhors) hos : , . ,:,,,,'i.,,,shown.(l8l qs the currenr improve- Due to the slrong interdctionment of the copobiliries of morhem-o- b"r**n rd;;itffi;;iliticolsimulorion models con be useful the gloss furnoce,yrr"r, ilr.v.,;:

IMIRNAIIONA| G|-ASS JOURNAT (1996j _ No. 89 33

Fis, | ' G.lass end'porl furnace considered subsystems for physicotly-bosed time-depen-dent modelling.

Fig.2 - Furnoce pull rote (kg/sl.

peroture deviotion respecting to ogiven torget is considered to clossifythe furnqce operotion stobility. Twodedicqted opiimisotion olgorithruwere developed to find optimol ope-roting conditions for the furnoceoperoiion. These olgorithms ore bo-sed on the so-colled <hill ciimber>opprooch. They ore designed tomoximise the stobility ond perfor-monce index. The modelling tool isused to supply doto to the optimiso-tion olgorithm concerning the clossi-ficotion of neor fuiure operotion sce-norios.

4.4 - Applicotion results - perfor-monce mqximisotion

A model-bosed optimol control strq-tegy wos tesfed for future on-lineopplicotion in the operotion optimi-sotion of o regenerotive end-portfurnoce. The furnoce pull.is given byFig. 2. The operoting conditionswith ond without the optimol contrololgorithm ore shown in Fig. 3 io 5where the profiles of fuel llow rote,glo,ss temperoture ond gloss quolityindex ore shown. The proposedcontrol strotegy is oimed ot em-bodying o supervision system copo-ble to give to the operoior the neorfuture moin operotion porometersqble to ensure gloss optimol produc-tion.

4.5 - Applicotion resuhs - stobiliso-tion

The obove described model-bosedlptimol control strotegy wos testedfor the stobilisotion o[ the some fur-noce operotion.A step-wise chonge in the pull rote isinlroduced to exemplity the olgo-rithm use. The consequ"n.", forih"furnoce operofion of thot suddenchonge were simulqted under oconstonl crown temperoture profile.As shown in Fig. 6, the ouilet glosstemperoture decreoses until o newtemperoture level, eventuolly fortrom on operotion iorget. Using thedeveloped model-bJsed optTmolcontrol strotegy, the gloss outlet tem-peroture-con be stobilised by meonsof feedforword octuotion in th"

specting its dynomic behoviour, thedeveloped model is bosed on thecolculoiion of the heot ond mqsstronsfer between oll the furnoceconsidered subsystems (figure 1).The regenerotive chombers were si-muloted os on one-dimensionol sy-stem olong which energy ond mix-ture froction convective/diffusivetronsport equotions were solved.The gos emissivity is colculoted th-rough the grey goses mixture proce-dure {19). The convective heoi tron-sfer coefficient wqs colculoted usingo stondord correlotion (20).ln the combustion chomber, the moinheot tronsfer process is the rodiotiveexchonge between the hot qosesond the enveloping surfoces. in thepresenl simulotor the rodiotive tron-sfer is solved through the rodiosityequotions (21). The botch flootinoover the gloss-melt, is in the pr"r"n"tmodel, divided in two stoqes. theheoting stoge ond the meltirig stge.

The solution procedure is bosed inthe colculotion of non-steodv heotond moss for eqch one of the'obovereferred componenfs.

4.3 - Th9 on.line operofion optimi-sotion olgorithm

' Two merit functions were colculotedfrom the obove described dvnomicmodel results: 1 ) overoll furnoceperformonce; 2) furnoce output sto-bility.The performonce merit function isconlinuously colculoted from theobove described time-dependentmodel results. An index is computedthrough heuristic relqtions -hi.hmoke possible on on-line clossificq-tion of the furnoce performonce.The relevont porometers were consi-dered in the development of thispertormonces merit function. Thecomputotion of the gloss outlet tem-

34IiITERNATIONAI. GLASS JOURNAT {I 996) - No. 89

MODEL.BASED OPERATION OPTIMISAilON OF GLASS MELTING FURNACES

fig.3 - Fuel inlet rate (kg/s),

Fig. 4 - Auilel glass temperature (=.C)

Fig. 6'crown temperdture, glass meh ouiler remperature predicted ond rorgered,

crown temperoture. The effect of thisoction is illustroted in Fig. 7 wherethe stobilisotion of the outlet olosstemperoture is shown to be oih;e-ved, with the colculoted crown tem-peroture profile. The proposed con-trol strotegy ollows to give to theoperotor ihe neor future profiles ofthe furnoce porometers oble b en-sure stoble gloss production.

4.6 - Three-dimensionol simulotionof on oxy-fuel furnoce operotion

A three-dimensionol mqthemoticolmodelling describing the physicolphenomeno occurring in-o

-gloss

tonk furnoce hos been develooed.This model is bosed on the ,olrtionof conservqtion equotions for moss,momenlum, energy ond combustionreloted chemicol species, ond com-prises three moin coupled sub-mo-dels: the combustion chomber, thebotch melting ond the gloss ronk(23). The three moin sub-modelswere coupled by o cyclicol iferotiveway 1241.Combustion chqmber model incor-porotes physicol modelling for theturbuleni dilfusion flome, sooi for-molion ond oxidotion, NO formo-tion ond dissociotion, porficles en-troinment, formotion ond tronsportond rodiotive heot tronsfer. Thetime-overoge equotions for the con-servotion of momentum were usedos well os the equotion for the con-servolion ol energy 1221.Botch melting model incorporotesphysicol modelling for the heot tron-sfer ond melting down process. Theconduclive heot tronsfer occurs onlyin botch depth direction {23}. Glosstonk model incorporotes physicolmodelling for the flow ond'heottronsfer of the molten gloss {24}.

4.7 - Applicotion results - evoluo.fion of NOx formotion criticolregion

The obove described three dimen-sionol model wos opplied to theevoluotion of o lorge'iize oxy-fuelgloss melting furnoce. ln figure 8, overticol plone cufiing onu oF the ory-fuel burners wos ielected, os on

'i

rl

Fig. 5 - Giass quality index.

IMTERNAIONAI GLASS JOURNAT ( t 996) - No. 89 35

F!e. 7 ".!9wn teypeloture, gloss meh outlet temperoture predicted ond torgeled, usingthe model-based feidforwordcontrol algorithm.

Fig. 8 - Predicled NOx concentration inside o lorge size oxy-Iuel combuslion chamben

lisotion of the obove considered fur-noce is presented to show the spo-tiol distribution of porticles insidethe combustion chomber of o glossmelting furnoce. This copobiliV moybe speciolly useful os it is very diffi-cult to estimote the behoviour of theporticles entroinment, formotion ondtronsport mechonism inside o com-bustion chomber. The octuotion onthe furnoce operoting condiiions forreduction of porticle emissions moybe q difficult tosk without o simulo-tion tool helping the furnoce opero-tion teom. The use of o physicolly-bosed three-dimensionol modellingtool os the one here presenled is qpromising olternotive to the deve-lopment of porticle emission doto-boses which would be exponsiveond evenluolly not opplicoble butfor o short ronge of operoting sce-norios.

5. F]NAL REMARKS

Gloss industry is oimed ot mokinggloss products ot o quolity/cost ro-tio os high os possible. The outhors

exomple, for the visuolisotion of theNOx concentroiion inside the com-bustion chomber. ln this figure thelocoliorr of the high concentrotiongrodients ore well opporent neorthe flome envelope.The ovoilobility of such o result moybe speciolly useful for the under-stonding of the NOx formqtion me-chonisms under octuol operotinoconditions. This moy be specioll|importcrni os it is know thot theoctuol high Mx formqtion rofesmoy present completely differentpotlerns inside on oxy-fuel combu-stion chcrmber when comporing withoir-fuel conventionol combustionsystems. The octuotion on the [ur-noce operoting conditions for reduc-tion of NOx emissions in on oxy-fuel melting furnoce, speciolly'olorge one, moy be o difficult tosk.The ovoilobility of decision oidingtools to the furnoce operotion teommoy be on importont contribution toeosy thol iob. The developed three-dimensionol models is oimed,omong other opplicotions, ot em-

bodying o model-bosed knowledgesystem dedicoted to the help the fur-noce operolion optimisolion.

4.8 - Applicolion resuhs - visuqliso-ton of the porticles distributioninside the combustion chomber

ln Fig. 9, o firee dimensionol visuo-

believe thot odvonced conlrol, su-pervision ond co-ordinotion toolsmoy be in the neor future on impor-tont foctor to help gloss industry toincreose thot rotio.This poper concerns the use ofmothemoticol modelling tools in thedevelopment ond operoiion of od-vonced outomotic systems for con-trol, supervision ond co-ordinotion

Fig.9 - Predicled porticles concentration inside o large size oxy-fuel combuslion chamber.

36 INIERNAIIONAI GIASS JOURNA| ll996J - No 89

lvloDEL-BASED OPERATION OPTIMISATI?N oF GtAss MELTING FURNACES

of the gloss melting process. Severolrecent developments ond opplico-lions were discussed os well ossome _opplicofion exomples weredescribed. From these exomoles. itmoy be concluded thot modellinotools use in control tend to be one o"fthe more octives R&D fields in olossmelting process technology, os' thefollowing proposed ones:- continuous development of odvon-

ced physicolly-bosed multi-dimen-sionol mothemoticol models withhigh levels of performonce to beused in. strongly multi-input/multi-output/multi-tosk outomotic con-trollers ond supervision systems.

- development of fusion jgorithmscombining fhe odvontogeiof phv-sicolly-boied models o"nd oalol-ced identificotion models os neu-rol networks bosed ones.

- deuelopment of odvonced opiimi-sotion olgorithms copoble to usein o economic woy model-genero-ted doto in proclss conttl ondoptimisotion.

- development of interconnectionslrotegies for hierorchicol use ofmodel-bosed olgorithms for thedevelopment of ploni-wideco-ordinolion ond supervision qu-tomotic syslems,

Plont wide ossociotion of sophistico-ted unit conhollers with supervisionexpert systems moy leod the deve-lopment of outomotic co-ordinotionsystems moking possible the futurereqlisotion -of computer integrotedgloss monufocturing.

ACKNOWIEDGEMENTS

The present work is portly finoncedby the (R&D) programme underconfoct proiect N' JOE3 CTSS-0040. The ouihors ocknowledgePRAXAIR, CIVE ONd SANTOS BA-ROSA for the.help ond support gi-ven to this work.

REFERENCES

(1) Borton J.1., <<Present Trends in ln-dustriol Gloss Melting>>, XVll lnf.Congress on Gloss, 1995, Beiiinq.{2} Beerkens R.G.C. ond tvtryin-berg H.P.H., <<Comporotive stujy on

energy-soving technologies for glossfurnocesD, Glostech. Ben 65, 1992,Nr. B, pp. 216-?24.(3) Longfeld R. ond Petzoldt J., <<Fu-ture Trends in lndustriol R&D in theField of Gloss>>, ESG Conf. on Fun-domentols of Gloss Science ond Te-chnology, 1993 - Venice.(4) Vonondruel N. ond Deville M.,<Unsteody numericol simulotion ofcirculqtion ond heot lronsfer in ogloss melting tonk>, ESG Conf. OnFundomentols of Gloss Science ondTechnology, I 993, Venice.{5)Muysenberg H.P.H., Simonis F.

ond Peters E.G.J., (studying timetrqnsienf behoviour of qloss meltinotonks by mothemqtico'i simulotioimodels>r, Semionr on Gloss Model-ling, 1995, Vsetin.(61 H. ltoh, M. lgo, K. Odo ond H.Mose, <<Mothemoiicql model of un-steody molten gloss flow with inho-mogeneity in melt>, XVll lnt. Con-gress on Gloss, 1995, Beiiing.(7) Deming H.C.L., (studies on th-ree-dimensionol mothemoticol mo-del of heoi tronfer in combustionspoce of gloss tonk furnoce>>, XVlllnt. Congress on Gloss, 1995,Beiiing,(8) Corvolho M.G., Nogueiro M.ond Wong J., <<Mothemoticol Mo-delling of the Gloss Melting lndu-striol Process>. XVll lnternotionolCongress on Gloss, 1995, Beiiing.(9)Ayolo l.L. ond Solis 1.J., <Siruitu-red logic control in gloss preporo-tion processes>>, IEEE Tronsoclionson lndusfry Applicotions, vol.27,No I , Jonuo ry/Februory I 991, pp.l0B-l I l.(10) lto T. And lnoboyoshi S., ,.Amodelling onolysis ond temperoturecontrols for floot furnoce>>, ESGConf. On Fundomentols of GlossScience ond Technology, 1g93, Ve-ntce.(l l ) Simon J.F. ond Wertz V.,<Adoptive predictive bottom tempe-roture control for o qloss meltinofurnoce, ESG Conf. O"n FundomenYtols of Gloss Science ond Techno-logy, 1993, Venice.(12) Nokogomo T. ond Kimuro T.,<Multivoriqte control through fusiono[ quontitotive ond quolitoiiue com-plementority 1or fuzry dynomicol>,ESG Conf. On Fundomentols ofGloss Science ond Technology,

1993, Venice.{13) Zuo S.J. ond yi C.y., <<Fvzrycontrol of the outside diometer ofgloss tubes in donner processr>, XVlllnternolionol Congress on Gloss,1995, Beiiing.(14) Pirovolou D.K., VochtsevonosG.J.., Zhong X.J. ond Henry V.1.,<<Gloss monufocturing: Modelingond control of o gos heorth> XVlllnternotionol Congress on Gloss,1995, Beiiing.{15} Former E.D., <Model-bosedcombusfion control of o gloss fur-nocel, lnternol (eport ESPRIT llproiect 2194.(16) Sims R., <<Computer optimiso-tion -of gloss conditioning>, ESGConf. On Fundomentols of GlossScience ond Technology, 1993, Ye-nice.(17) Vonondruel N., deHoos B. ondWertz V., uModelling ond conlrol ofo gloss melting tonk vio numericolsimulolion>, XVll lnternotionol Con-gress on Gloss, 1995, Beijing.(l8J Bouer R.A., Beerkens R., Muii-senberg E. ond Simonis F., <Advon-ced control of gloss tonks by use ofsimulotion models> XVll lnternotio-nol Congress on Glos s, | 99 5 ,Beiiing.(19) Truelove, J.S. <<MothemoticolModelling of Rodiont Heot Tronsferin Furnocesr> Heot T ronsfer & FluidFlow Service, Aere Horwell Rept.,Nr HLZ6I34 48/KE, 1924, Seprem-ber.(20) Beion, A., <<Convection HeoiTronfer>>, Jonh Wiley & Sons, NewYork, (1984).l2ll Groy, W.A., /Vliiller, R. <Engi-neering Colculotions in RodiotiveHeot Trqnsfer> Ed. Pergomon Press,1974,(22) Corvolho, M.G. ond Nogueiro,M., <<Gloss Quolity Evqluotion Vio3-D Mothemoticol Modelling ofGloss Melting Furnoces>, ESG Conf.On Fundomentols of Gloss Scienceond Technology, Sheffield, t l9l .

(23) Corvolho M.G., <<Computer si-mulotion of o gloss fuinoce>,(1983) Ph.D. Thesis, London Univer-sity.(24) Corvolho M,G.M.S., NogueiroM. ond Wong J., <Mothemoticolmodelling of the gloss melting indu-slriol processD, XVll lnt. Congress onGloss, (l 995), Beiiing.

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