Closed-Loop Measurement of Equipment Efficiency and Equipment Capacity

Transcription

1 Closed-Loop Measuremet of Equpmet Effcecy ad Equpmet Capacty Robert C. Leachma Dept. of Idustral Egeerg ad Operatos Research Uversty of Calfora at Berkeley Berkeley, CA Jauary, Itroducto Abstract Formal deftos for the compoets of effcecy ad capacty, mathematcal formulas for computg overall effcecy, ad data collecto strateges are proposed for rgorous measuremet of equpmet effcecy ad equpmet capacty. Measuremet of overall equpmet effectveess (OEE) uder the TPM paradgm s revsed to become a true quattatve measure of effcecy that we term overall equpmet effcecy. The measuremet also s exteded to support the mateace of capacty parameters for producto plag. The weakesses of equpmet aalyses based o utlzato ad aggregate UPH (uts per hour) fgures are cotrasted agast the robustess of the proposed approach. Applcatos semcoductor factores are dscussed. As a successor to the Total Qualty Maagemet (TQM) paradgm, Total Productve Mateace (TPM) s ow a promet paradgm drvg maufacturg mprovemets a umber of Japaese dustres, partcularly the semcoductor dustry. TPM also has gaed a foothold some Amerca compaes. Whle TQM's mmedate focus s o efforts to perfect product qualty, TPM's mmedate focus s o efforts to perfect equpmet productvty. Strateges uder the TPM paradgm clude creasg equpmet kowledge wth the maufacturg workforce, mprovg mateace procedures, chagg procedures to reduce or elmate setups, test procedures ad dle tme, makg modfcatos to crease mache speed or reduce scrap ad rework, etc. Successful TPM s facltated by rgorous defto ad measuremet of mache effcecy. Overall effcecy s expressed as a fucto of a umber of mutually exclusve compoets order to quatfy the varous kds of productvty losses that are occurrg, whereupo the most approprate mprovemet tatves may be formulated. A umber of authors have wrtte about the defto ad measuremet of overall equpmet effcecy (OEE) uder the TPM paradgm [], [2], [3], [4]. A uremarked potetal by-product of rgorous ad routzed measuremet of OEE s the opportuty to realze routzed ad rgorous mateace of capacty data for the purposes of plag ad schedulg. The eeds of equpmet assessmet ad equpmet mprovemet ad

2 the eeds of plag ad schedulg lead to dfferet deftos ad parttos of effcecy data, as wll be dscussed. Oe goal of ths paper s to propose a commo data collecto methodology ad a complete set of formulae for effcecy factors that ca support both OEE ad capacty aalyses. May compaes ackowledge the potetal value of OEE ad capacty data, but they have bee dauted by the effort requred to rgorously collect ad mata the requred data. The secod goal of ths paper s to dscuss practcal meas of data collecto ad data mateace. Data acqusto strateges ragg from very maual to very automated that have bee successfully mplemeted are dscussed. Oe mght expect that tradtoal Idustral Egeerg methodologes would offer rgorous meas of measurg equpmet effcecy ad capacty. But t must be recogzed that tradtoal IE methods are oreted to measurg ad maagg work that s performed maually. It s a gve that dfferet people are capable of workg at dfferet speeds. Oe could hardly hold all workers up to a stadard defed by the worker wth the greatest physcal stregth or the best had-eye coordato. Thus tradtoal IE stadard processg tmes for operatos are of ecessty statstcal averages, wth staces of operatos performed both slower ad faster tha the stadard. Some degree of ucertaty processg tmes for maual work s uavodable, ad thus some degree of ucertaty overall effcecy measuremet s uavodable as well. I semcoductor maufacturg, vrtually every processg operato s performed by maches. It s perfectly reasoable to hold all maches of a partcular kd up to a stadard of performace defed by a mache perfect workg order. The dstrbuto of actual mache processg tmes for a partcular operato s thus oe-sded,.e., there s a theoretcal or deal mache speed f the mache s perfect workg order, but speed degrades whe the mache s out-of-tue, malfuctog, jammg, etc. From a TPM pot of vew, all such degradatos are effcecy losses that potetally ca be elmated. Thus we are terested mache effcecy calculated based o the (determstc) theoretcal or deal mache speeds, ot based o the statstcal average mache speeds. 2. Metrcs of Equpmet Effcecy. Measuremet of equpmet performace most Amerca semcoductor maufacturers tradtoally emphaszes use of two basc metrcs, equpmet avalablty ad equpmet utlzato. Equpmet avalablty measures the fracto of total operatg tme a observato perod such as a week or a moth that a mache asset was capable of performg or actually performg processg work. Avalable tme excludes tme the mache was ot operatoal because of mateace or repars or watg for repars, ad t excludes tme the mache was udergog prevetve mateace, cleag, calbrato, re-qualfcato after mateace, or used egeerg efforts. Tme the mache was actually processg ad tme the mache was smply dle are cluded avalable tme. Uavalable tme (the complemet of avalable tme) s termed mache "dow" tme. 2

3 Equpmet utlzato measures the fracto of total operatg tme a observato perod that the mache asset was actually egaged processg actvty. Precse deftos ad measuremets of utlzato vary from compay to compay; for practcal reasos, tme credted to utlzato may clude ot oly actual processg tme but also short perods of tme the mache s dle whle operators perform hadlg, recpe dowload ad metrology tasks that are requred betwee cosecutve mache cycles. From the TPM pot of vew, losses of equpmet avalablty ad equpmet utlzato are of course causes for maagemet cocer, but they are ot the oly types of effcecy losses that occur. Clearly, avalablty s ot a overall effcecy score sce t does ot accout for dle tme losses. Whle utlzato accouts for dle tme losses, t s ot a overall effcecy score, ether. Ths s because the mache speed may vary dfferet staces of the same processg operato, perhaps because of dffereces operator hadlg ad preparato tme, or because of bref mache jams or stoppages ot reported as "dow" tme, or because of bref dle perods ot broke out from reported producto tme, or smply because the mache s out-of-tue ad uable to operate at full speed. Thus a mache asset may be reported as beg fully utlzed but stll ot provde 00% of ts theoretcal productvty. Eve wth o varatos mache speed, there s a subtle but very serous ad practcal cocer wth use of the utlzato metrc. Typcally, tme a mache actually speds producto s ot measured drectly, but rather t s calculated as the total operatg tme less the reported dow tme ad the reported dle tme. Uder such a strategy, oe s depedet upo the maufacturg orgazato to fathfully report all dow tme ad all dle tme order to correctly determe utlzato. Geerally, t s mpractcal for the orgazato to record umerous, short dle perods betwee cosecutve mache rus the reported dle tme, ad t s mpractcal for the orgazato to record short-term mache jams or aborts the reported dow tme. Wthout comparg the producto tme agast some stadard "should-take" tme for the work actually performed, there s o way to check f all lost tme actually was reported,.e., oe ca ever be sure that utlzato s ot overstated. True mache effcecy must be measured terms of "eared" utlzato, computed usg "should-take" or "theoretcal" processg tmes. Let S deote the should-take tme for the processg work completed by a mache asset durg some observato perod, computed accordg to the specfed theoretcal mache rates appled to the actual quattes of the mache's varous operatos that were successfully completed. S wll almost always be sgfcatly smaller tha the producto tme deduced from the reported dow tme ad the reported dle tme. Let T deote the total legth of the observato perod. We defe the overall equpmet effcecy (OEE) for the observato perod as the followg rato: S OEE =. () T Equato () demostrates that a determato of overall equpmet effcecy s achevable wthout precse measuremet of ether equpmet avalablty or equpmet utlzato; rather, 3

4 oe oly eeds to kow how much work was successfully performed, ad what s the theoretcal tme requred to perform such work. Whle most factores the semcoductor dustry do ot udertake a careful ad rgorous measuremet of OEE of ther maches, t s estmated that OEE scores would be geerally the rage of percet, yet these factores do ot have capacty to capture all of ther potetal market demads. Thus there s cosderable proft potetal assocated wth creasg OEE ths dustry. Of course, just kowg the overall effcecy score s ot very helpful for detfyg the uderlyg mprovemets eeded to crease OEE. A breakdow of the overall effcecy to ts may compoets s requred to focus ad prortze mprovemet efforts. As wll be dscussed, a breakdow s also requred for precse capacty aalyss. We ow tur to defg such a breakdow. For coveece, a glossary of the otato used here s provded Table. 3. Data Collecto Requremets For a formal presetato of equpmet effcecy aalyss, we make the followg deftos ad assumptos, geerally followg the characterstcs of semcoductor wafer fabrcato. Products of a factory are assumed to be maufactured accordg to a process flow,.e., a fxed seres of maufacturg operatos. Each such operato s termed a process step. For each process step, the process specfcato s the set of structos to the maufacturg operators dcatg whch equpmet assets are sutable ad what settgs of the equpmet cotrols are requred to correctly perform the step. Uts of products move through the factory from equpmet to equpmet a group termed a lot. There s a fxed startg sze for lots; however, as a lot moves from process step to process step, there ca be some loss of uts or eve loss of the etre lot as scrap. Uts wth each lot are wafers frot-ed factores ad packaged devces or chps back-ed factores. As a practcal matter, the strategy for computg overall effcecy must be devsed wth cosderato of the factory's capabltes data collecto. Relevat data sources avalable most semcoductor factores clude the followg: () Equpmet trackg databases, to whch producto operators key observed chages equpmet state.. (2) Work--process (WIP) trackg databases, to whch producto operators key uts ad lots actually processed. (I semcoductor maufacturg, uts tracked though frot-ed factores are wafers, whle uts tracked through back-ed factores are chps or packaged devces.) (3) Mache-geerated evet logs, documetg the mache recpes performed, the umber of uts processed, the elapsed tme varous stages of the processg cycle, etc. May but ot all types of fabrcato equpmet provde such logs. 4

5 (4) A aalog sgal ca be captured from most processg maches dcatg whether or ot t s egaged processg actvty. A trackg applcato motorg these sgals could be devsed to record the mache's actual operatg tme. At a mmum, we shall assume here that the factory s able to perform the followg data collecto for each equpmet asset of terest: () Total dow tme, total producto tme, ad total dle tme are recorded durg each observato perod for the asset. More detaled breakdows of dow tme ad dle tme losses to varous subcategores are carred out ay practcal applcato, order to facltate a aalyss of losses by uderlyg reasos. Cosderg the purposes of ths paper, oly a lmted breakdow of the dle tme category wll be dscussed here. (2) The factory tracks all work--process (WIP), recordg the total umber of lots ad the umber of uts each lot started to processg, ad the total umber of lots ad uts successfully completg each process step performed by the equpmet asset. Such WIP-trackg fgures eed to be tabulated for each observato perod. (3) The factory also records the sequece of lots processed through each mache, thereby eablg the calculato of batch szes betwee chages equpmet setup. (These data are ot ecessary for computg OEE, but are requred for computg capacty, as wll be dscussed secto 5.) I addto to such WIP ad equpmet trackg data, the calculato of OEE requres data cocerg the process specfcatos for all process steps performed by the equpmet asset, as well as the theoretcal tmes to complete each specfcato. We shall defer dscusso of these more statc data to Secto 4. We develop the computato of OEE for the case of equpmet types that perform operatos sequetally,.e., oly oe product udergog oe operato s egaged by the equpmet at a tme. Most semcoductor fabrcato equpmet fts ths descrpto; however, mult-chamber cluster tools smultaeously processg several lots of several products requre a more volved methodology makg use of evet logs. Wth these prelmares asde, we ow proceed to a formal defto of equpmet states. For the purposes of ths paper, we use a smplfcato of the states set forth the SEMI E0 gudeles [5] famlar to most semcoductor maufacturers. Uder E0, a equpmet asset of terest at ay stat of tme s classfed to to exactly oe of fve mutually exclusve states: oscheduled tme, dow tme, stadby tme, producto tme, or egeerg tme. Total tme durg a observato perod each of these fve states sums to the total legth of the observato perod. I ths paper, we use three more aggregate states: dow tme (cludg the E0 egeerg ad dow tme states), dle tme (the E0 stadby tme), ad producto tme. Our three states also are mutually exclusve, ad they sum to the total operatg tme (total tme less ay oscheduled tme). They are dscussed more detal as follows. 5

6 Producto tme cludes all tme the mache s egaged processg actvty. Accordg to E0 gudeles, mache chageovers ad setups requred to swtch processg to a dfferet operato or a dfferet lot are to be cluded the dow tme state. However, whe mache chageovers, setups ad recpe loads are relatvely bref ature, t ca be mpractcal to report such tme as mache dow tme. As a practcal matter, a fab followg the E0 gudeles s typcally oly able to record major setups dow tme, leavg mor setups as part of producto tme. For the purposes of ths paper, chageovers ad setups are vewed as compoets of processg actvty, ad therefore cluded producto tme. We shall assume such mache chageover tme (.e., tme to recofgure the mache to process a dfferet product, sometmes called "setup tme" operatos research lterature) s cluded producto tme. Tme to "set up" or "requal" the mache for operato after mateace, source materal repleshmet, or egeerg work s cosdered part of dow tme, as wll be dscussed below. Idle tme cludes all perods the mache s physcally prepared to egage processg actvty (.e., chageover or processg), but o such actvty s takg place. Causes of dle tme clude lack of product ready for processg, lack of operators preset to perform processg, or producto cotrol rules such as Kaba lmts that may block processg actvty because of dowstream WIP accumulato. For some types of equpmet, bref dle perods may be ecessary betwee the completo of processg of oe mache load ad the tato of processg of the ext load. As a practcal matter, there s probably some mmum legth for dle evets whch the factory s capable of routely trackg ad recordg; dle duratos less tha ths legth ed up reported producto tme. Thus the dle tme state cludes all "reportable" dle tme. Dow tme cludes all tme the mache s operatve because of mache falures ad cosequet repars, delays watg for repar materals ad/or repar labor, ad all follow-o calbratos, qualfcatos ad tests performed to restore the mache to a productve state. It also cludes all tme the mache s operatve because of prevetve mateace, source materal repleshmets, scheduled equpmet cleas, calbratos, egeerg work, ad all follow-o actvty requred to restore the mache to a productve state. As wth dle tme, ay factory there s some mmum durato whch s practcal to track ad record as dow tme; evets shorter tha ths, e.g., short-term mache jams ad aborts, evtably wll be cluded the reported producto tme. 4. Calculato of Equpmet Effcecy Data s assumed to be tabulated for observato perods such as weeks, for whch effcecy scores wll be calculated. The compoets of overall equpmet effcecy calculated for a equpmet asset are defed as follows. 4.. Reported Dow Tme ad Idle Tme Losses 6

7 Frst, we have two compoets that accout for dow tme ad dle tme losses: () DT s the fracto of operatg tme that the asset s reported as the dow tme state. (2) IT s the fracto of operatg tme that the asset s reported as the dle tme state. I addto to dow tme ad dle tme losses, OEE must accout for losses due to feror mache speed, ad losses assocated wth feror qualty resultg scrap or rework. These two categores are accouted for by the metrcs rate effcecy ad qualty effcecy, respectvely, whch we ow defe. 4.2 Rate Effcecy The basc purpose of rate effcecy s to express the rato of the observed mache processg rate to the theoretcally achevable mache rate. Expressed dfferet uts, t s the rato of the theoretcal tme to complete the reported work dvded by the reported producto tme. To calculate rate effcecy, oe eeds theoretcal processg tmes for the equpmet asset. Most processg maches perform a varety of processg operatos volvg a varety of equpmet settgs ad a cosequet varety of processg duratos. Some presetatos of OEE (e.g., [3]) set forth oly a sgle parameter for theoretcal mache speed. The author also has observed that some compaes edeavorg to measure mache effcecy smply report the total umber of uts processed per mache per ut tme, aggregatg over the varous operatos o varous products that are performed. Ths aggregate fgure s compared agast a sgle theoretcal mache speed to gauge effcecy, ad/or aggregate fgures for several maches of the same type are compared to ascerta relatve effcecy. Whle the sgle-parameter approach s easy to mplemet, t has a drawback that effcecy measuremet gets clouded by chages product mx. Cosder oe mache performg mostly operatos wth a short theoretcal processg tme oe observato perod whle performg mostly operatos wth a log theoretcal processg tme the followg observato perod. For example, a photolthography stepper mght be exposg a mplat layer oe shft ad a metal layer the ext. Ths dfferece should ot be costrued as a dcato that the rate effcecy of the mache has decled. We assume here that theoretcal processg tmes are establshed ad mataed for every process specfcato that the equpmet asset s called upo to perform. Typcally, most processg cycles cosst of a fxed compoet for materal hadlg, plus a varable compoet depedg upo the process specfcato. Ofte ths varable compoet may be expressed as a mathematcal formula or as a table look-up of the parameters of the specfcato. Rather tha mata processg tmes for each operato as elemetal data, t s proposed to mata such formulae ad referece tables, alog wth matag the database of process specfcatos a computer-readable form. Theoretcal processg tmes ca the be calculated from the uderlyg data whe t s desred to compute effcecy scores. I the author's 7

8 experece, t s much less troublesome to mata the processg tme formulas ad look-up tables tha t s to mata a database of UPH (uts per hour) fgures as elemetal data. Chages process specfcatos are frequet semcoductor maufacturg, ad a separate IE effort to mata UPHs evtably eds up as a paper chase, wth the UPH database always laggg the latest chages to process specfcatos made by the process egeers. Matag the process specfcatos a computer-readable form allows them to serve as the elemetal data for effcecy ad capacty aalyss. I Secto 6.2 we shall descrbe a actual applcato llustratg ths strategy. Some types of maches process a sgle ut of product at a tme. Others accommodate several uts the processg chamber ad process them smultaeously. Most processg steps volve the operator tederg a lot of product uts to the mache, whereupo the mache selects oe or several uts from the lot ad places them the processg chamber for tato of a processg cycle. I geeral, the theoretcal processg tme of a mache performg a partcular operato has up to three compoets: () Tme_per_ut (TPU) - maches processg a sgle ut at a tme have ths compoet. There ca be both a true processg compoet as well as a separate materal hadlg compoet (measurg the tme to exchage a ut the chamber wth aother uprocessed ut from the lot). Ths latter compoet s usually depedet of the process specfcato. (2) Tme_per_lot (TPL) - the case the operator teders a lot to the mache, ad/or there s some tal pump-dow or other evrometal preparato, ad/or there s some tal materal hadlg actvty to load the mache for the frst processg cycle, there s a tme per lot compoet of overall processg tme. Ths compoet s typcally depedet of the processg specfcato. I a few wet bech operatos, processg may cosst of the etre lot beg dpped a bath or a seres of baths, whch case the tme per lot may be the sole compoet of processg tme. (3) Tme_per_mache load (TPML) - the case the mache smultaeously processes multple uts a sgle processg cycle, the (chamber) processg tme s appled to a mache load rather tha to a dvdual ut. The theoretcal processg tme ThPT s calculated by aggregatg the three compoets, expressg the result as a tme per ut. To covert tme per lot ad tme per mache load to a tme per ut, these fgures are dvded by the sze of a full lot FLS ad the sze of a full mache load FML, respectvely. TPL TPML ThPT = ( TPU ) + + (2) FLS FML Usg equato (2), rate effcecy s calculated as follows. Suppose the varous processg steps performed by the mache asset are umbered =, 2,...,. Let WS deote the umber of uts that were started to step durg the observato perod. Let ThPT deote the theoretcal processg tme for step, ad let PT deote the reported total producto tme durg the 8

9 observato perod. (We remark that.0 DT IT = PT / T,.e., producto tme, dow tme ad dle tme sum to total tme.) The we defe the rate effcecy RE of the mache as ( WS )( ThPT ) = RE = PT. (3) 4.3 Qualty Effcecy Ths factor accouts for effcecy losses resultg from the output of product that does ot meet qualty requremets. I practce, some qualty problems are detectable mmedately, resultg mmedate scrappg of the product or mmedate rework of the product (where rework s techcally ad ecoomcally feasble). I other cases -- for example, the udesred deposto of partcles o semcoductor wafers -- t caot be determed utl after dowstream processg ad testg f a qualty problem has bee geerated. We shall restrct our measuremet of qualty losses here to qualty losses that are mmedately recorded. If rework s explctly ad rgorously measured, oe could accout for t the qualty effcecy factor. I practce, may factores do ot accout for "local" rework,.e., rework loops that fall betwee cosecutve WIP-trackg log pots a process flow. To cope wth a lack of rework data, we may vew rework as ot a qualty loss but rather as a rate effcecy loss. As log as reported producto tme cludes the tme spet performg rework ad the WIP-trackg fgures exclude rework, effcecy losses due to the performace of rework wll be fully captured the rate effcecy factor. Let WS deote the total umber of uts started to process step durg the observato perod, ad let WF deote the total umber of good uts completg process step, cosderg all process steps =, 2,..., performed by the mache asset. Sce processg tmes vary amog process steps, we shall weght ut producto couts by such tmes order to properly gauge the mpact o the mache asset from processg uts that ed up as scrap or eed to be reworked. As before, let ThPT deote the theoretcal processg tme for step. The qualty effcecy QE for the equpmet asset durg the observato perod s defed by QE = ( WF )( ThPT ) = ( WS )( ThPT ) =. (4) The qualty effcecy for a equpmet asset s ot to be cofused wth the rate of qualty for a process flow, ofte termed the le yeld of the process. The le yeld of a process flow s the As a alteratve approach, Nagub [4] suggests a strategy for estmatg drect qualty losses based o the process cotrollablty factor C pk. 9

10 product of the scrap rates of the process steps the flow. (If rework uts are excluded from WS, the the scrap rate of step durg the observato perod s calculated as WF /WS.) Factores also defe le yeld up to a gve process step, equal to the product of the scrap rates for precedg steps the process flow. Such le yelds are useful capacty aalyss for producto plag, as wll be dscussed below. 4.5 OEE Formula Combg the expressos for avalablty ad utlzato losses wth the expressos for mache rate effcecy ad qualty effcecy, we obta the followg expresso for overall equpmet effcecy: { DT IT}( RE)( QE). OEE =.0 (5) The term curly brackets equato (5) s the reported mache utlzato, expressed as a fracto of total tme. The last two terms reduce reported utlzato to "eared" utlzato, cosderg the rato of "should-take" producto tme to reported producto tme, ad the porto of should-take producto tme that was geeratg output of acceptable qualty. It s structve to substtute detaled expressos for the terms (5) ad observe the resultg cacellato of terms: OEE = ( WS )( ThPT ) ( WF ) ( ThPT ) PT = = = = T PT ( WS )( ThPT ) = ( WF )( ThPT ) T = S T. (6) That s, the expaded formula for OEE reduces to true mache effcecy,.e., to the should-take tme for the good output actually completed dvded by the total elapsed tme. 4.4 Comparso to Prevous Formulatos Earler formulatos of OEE do ot express the true measure of effcecy. We meto two accuraces here commo to most formulatos of overall equpmet effectveess. Some authors (e.g., [], [5]) have proposed usg a rate-of-qualty (RQ) metrc leu of QE, where RQ s defed as 0

11 RQ = WF = WS =. (7) Whle smple to compute, RQ assgs the same amout of effcecy loss to all uts of feror qualty, regardless of how much mache tme s requred to produce those uts. Uless theoretcal process tme s costat across all steps performed by the mache, the corporato of RQ to OEE meas OEE does ot express true effcecy. Most OEE authors propose to measure rate effcecy terms of actual vs. theoretcal mache rate. May formulatos (e.g., [], [2], [3], [4]]) assume there exsts a sgle, deal mache rate, depedet of product mx; as dscussed earler, ths s accurate the case of heterogeeous process steps performed by the mache. Others (e.g., [5]) propose use of a weghted-average theoretcal mache rate. Let UPH deote the theoretcal uts per hour that the mache ca acheve whe performg step. Note that UPH = /ThPT. Thus RE may be properly expressed as RE = = WS UPH PT (8) Some practtoers have proposed a dfferet formula (e.g., [5]). Frst, a weghted-average theoretcal mache rate s computed,.e., AUPH = WS ( ) UPH. = WS j = j (9) Next, RE s defed as RE = WS = ( AUPH )( PT ). (0) Equato (0) s ot correct because the logc behd equato (9) s faulty (for the same reaso t s ot correct to say that f you drve oe mle at 0 mph followed by oe mle at 20 mph, the your average speed s 5 mph). If equato (9) s replaced by computato of the harmoc mea,.e.,

12 AUPH = = = WS WS UPH, () the (0) reduces to (9) ad the expresso for RE s oce aga redered exact. 4.5 Exteso for Demad Effcecy I some factores, producto cotrol s so weak (or facal cetves are so skewed) that sgfcat tme s spet processg products that are ot demaded or desred by marketg. Whle facal metrcs may dcate such producto "reduces" factory costs (by provdg more volume over whch to "spread" factory costs), such actvty does ot apply equpmet assets to geerate reveue for the compay, ad therefore s waste from the pot of vew of TPM. From the pot of vew of ecoomc effcecy, the should-take tme for good uts ought to be reduced to the fracto that s spet processg products actually demad. Let PP deote the umber of uts that were plaed (demaded) to be processed through process step durg the observato perod. We defe demad effcecy DE as { WF, PP }( ThPT ) M = DE. (2) = = ( WF )( ThPT ) The mmum the umerator s employed so that the metrc oly credts producto wth the pla. If we revse the defto of OEE to accout for DE,.e., OEE = { DT IT}( RE)( QE)( DE) 2 = M { WF, PP }( ThPT ).0 =, (3) T we see that the OEE formulato expresses true effcecy,.e., the should-take tme for the completo of good uts that were demaded, dvded by the total observato tme. We shall assume the remader of the paper that OEE s defed by (5),.e., we shall assume there are o demad effceces. 5. Capacty Data

13 A key purpose of capacty data s to determe factory producto schedules that are feasble, whle turg away or delayg as lttle busess as possble ad matag acceptable factory cycle tmes. As the mx of products demad vares, t s desred to adjust producto schedules to respod as much as possble to the ew mx wthout overloadg the processg equpmet. Capacty data cludes processg tmes for the varous process steps performed o each of the products produced, a detfcato of the equpmet assets sutable to perform each process step, ad the total hours per plag perod each mache asset ca be egaged processg actvty (.e., the "capacty" of each asset). Mache capacty per perod ca be vewed as a overall effcecy factor tmes the operatg tme the perod, whereby the mache-hour capacty parameters descrbed above are equvalet to approprately-defed mache effcecy parameters. Thus capacty aalyss appears to use the same kd of parameters (processg tmes ad overall effcecy factors) that would be geerated from measuremet of OEE. If all effcecy losses were depedet of producto schedule, oe could smply use the theoretcal processg tmes ad the OEE fgures as the processg tme ad equpmet effcecy parameters of a capacty model. Ufortuately, certa kds of effcecy loss are mx-depedet. Obvously, dle tme losses deped o the producto volume (ad, tur, whch equpmet type s the fully-loaded bottleeck may deped o product mx); moreover, the amout of lost tme for chageovers (accouted for the rate effcecy factor) depeds o the mx of producto, especally f chageover tmes are qute varable from product to product. Smlarly, lost effcecy resultg from less-tha-maxmum mache loads also depeds o producto volume ad mx. Rework rates for certa products also may be hgher tha for others. As a result, OEE scores ca fluctuate purely as a result of chages the producto schedule. Capacty aalyss s usually performed terms of ut quattes to be released to the factory or terms of ut quattes to be completed by the factory varous plag perods. Le yelds from the tal release pot up to each process step ad from each process step to factory output are thus requred parameters for such calculatos. Gve the use of le yelds producto plag calculatos, equpmet effcecy parameters used capacty aalyss also eed to exclude the qualty effcecy term. I vew of these ssues, capacty aalyss requres a set of processg tmes ad overall mache effcecy factors that are dstct from the parameters used to defe OEE. Nevertheless, these factors ca be computed from a commo set of compoet parameters wth a commo data collecto ad data mateace strategy, descrbed as follows. 5. Effectve Processg Tmes To capture the effect of chageovers, load szes ad rework rates that vary by product ad process step, we suppose that statstcs are collected for each process step cocerg - the average lot sze ALS of lots passg through the process step; 3

14 - the average mache load sze AML (f the mache processes more tha oe ut of product at oce); - the average umber of uts processed after a chageover or setup for the process step s made, utl chagg the mache to perform a dfferet process step (hereafter ths statstc s called the "average batch sze" ABS for the process step); - the average fracto of uts passg through ths process step that are reworked (hereafter ths statstc s called the "average rework factor" ARF for the process step). Statstcs cocerg lot sze ad batch sze typcally ca be deduced from WIP-trackg data, whle developmet of rework ad load sze statstcs may requre measuremet actvty addtoal to that proposed Secto 3. We also suppose measuremet s made to establsh a stadard tme TPS to perform a mache setup or chageover for the process step. Usg these data, we defe the effectve processg tme of a process step performed by a mache asset of terest as follows: TPL TPML TPS EPT = TPU ( + ARF ). ALS AML ABS.0 (4) Example. To llustrate the defto ad computato of effectve ad theoretcal processg tmes, cosder a projecto alger mache used to perform photolthography operatos semcoductor maufacturg. Process specfcatos for such operatos wll dcate the exposure settg to use ad whether wafers ca be auto-alged or must be maually-alged for reasos of process cotrol. Assume ths case the lot sze s a sgle cassette of wafers. Measuremets should be made of a mache perfect workg order to establsh the followg parameters: - tme requred for exposure uder each exposure settg ("exposure tme"); - tme to cycle ad auto-alg a wafer ("cycle & alg tme"); ad - tme to flush the last wafer out of the mache ad back to the cassette ("flush tme"); The values for such parameters should be statc utl fudametal egeerg chages are made to the equpmet. Measuremets also should be made of processg actvty performed by a profcet operator to establsh the followg parameters: 4

15 - addtoal tme to maually alg a wafer ("maual alg tme"); - tme to exchage cassettes ("exchage cassettes tme"); ad - the tme to sert a retcle ad ru a test wafer ("retcle chage tme" + "test wafer tme"). The tme to ru a test wafer may deped o the process step (e.g., some steps may ot requre a test wafer to be processed). Usg these parameters, the compoets of effectve ad theoretcal processg tmes are calculated as follows: ad TPU = ( cycle_&_alg_tme ) + ( maual_alg_tme ) + ( exposure_tme ); TPL = ( flush_tme ) + ( exchage_cassettes_tme ) ; TPS = ( retcle_chage_tme ) + ( test_wafer_tme ). To calculate theoretcal processg tme, the expressos above for tme per wafer ad for tme per lot, together wth the capacty of a cassette (whch ths example s the maxmum lot sze), should be plugged to equato (2). To calculate effectve processg tme, all three expressos above should be plugged to equato (4), together wth statstcs for average lot sze, average batch sze ad for average rework rate. 5.2 Equpmet Effcecy for Capacty Aalyss As dscussed above, to perform proper capacty aalyss, the equpmet effcecy formula eeds to be modfed for use capacty aalyss. Frst, the equpmet effcecy measure used capacty aalyss should omt the qualty effcecy factor (sce such losses are corporated to the le yeld parameters). Secod, ts rate effcecy factor should be computed usg effectve processg tmes. A thrd adjustmet to the equpmet effcecy formula s requred wth respect to dle tme. Depedg o product mx ad volume, oe or more equpmet assets the factory wll have maxmal utlzato of avalable tme relatve to other assets, thereby defg the factory bottleeck(s). Equvaletly, the bottleeck assets wll have mmum dle tme; all other equpmet types the factory wll of ecessty have larger dle tmes. For such equpmet types, the observed performace wll be below capablty, as the workloads tedered to them are costraed by the performace of other assets. We shall term the dfferece betwee the actual dle tme for a asset ad a asset's mmum dle tme f t were the bottleeck as the scheduled dle tme SIT. The ssue s that scheduled dle tme, whle deed represetg overall effcecy loss, should ot be costrued as uavalable capacty. O the other had, mmum dle tme does represet uattaable capacty from a producto plag pot of vew. 5

16 As recogzed by may researchers, there s a trade-off curve betwee allowed WIP level (or, equvaletly, allowed factory cycle tme) ad the utlzato of equpmet assets, as depcted Fgure. The partcular shape ad posto of the curve depeds o varous factors descrbg the varablty the factory; less varablty affords a more favorable trade-off curve. Depedg o busess eeds, a maufacturer may target to operate at dfferet pots o ths trade-off curve. For example, a memory producer may target 00% utlzato of bottleeck equpmet avalablty, wth a cosequet log cycle tme, whle a ASIC producer may target oly 90% utlzato of bottleeck avalablty order to mata a lower cycle tme. Thus the mmum dle tme of a equpmet asset depeds o the allowed cycle tme or WIP level the factory. Gve a certa target cycle tme or WIP level, the mmum dle tme of the bottleeck asset depeds o a host of factors that cause varato processg rate or lot arrvals: schedulg methods, the level of operator staffg, relablty of equpmet ad processes, etc. For the purposes of capacty aalyss, the equpmet effcecy score eeds to accout for mmum dle tme, but t should ot clude allowaces for scheduled dle tme. Suppose for the momet that the mmum dle tme s specfed for each equpmet asset. (Updatg these parameters s dscussed Secto 5.3 below.) We may the defe a equpmet effcecy for use capacty aalyss as follows. Frst, we defe the capacty rate effcecy of a equpmet asset. Let EPT deote the effectve processg tme for process step, =, 2,..., performed by the mache. Let PT deote the total reported producto tme for the mache durg a observato perod, ad let WS deote the total uts upo whch process step was tated,, =, 2,...,. The capacty rate effcecy CRE of the equpmet asset durg the observato perod s defed as CRE = ( WS )( EPT ) = PT. (5) Next, let MIT deote the fracto of operatg tme equal to the mmum dle tme for the asset. The we defe the capacty equpmet effcecy (CEE) of the asset durg the observato perod as { DT MIT}( CRE). CEE =.0 (6) CEE s smlar to OEE, except that t excludes losses for scheduled dle tme ad t excludes losses already bult to the processg tme parameters EPT of the capacty model. The CEE of a equpmet asset s greater tha ts OEE, but stll well below a score of.0. CEE accouts for dow tme the same as does OEE, but t oly accouts for rate effcecy losses compared to effectve processg tmes. The dffereces betwee theoretcal ad effectve processg tmes (reflectg setups, small batch szes, etc.) are accouted for the processg tme parameters themselves. Idle tme losses at bottleeck assets are smlar CEE ad OEE, but dle tme losses at o-bottleeck assets are less CEE tha OEE, reflectg the scheduled dle tmes for such assets. 6

17 5.3. Computato of Capacty Equpmet Effcecy The measuremet of OEE observato perods s bascally a trackg exercse performed order to ppot the most mportat opportutes to crease equpmet effcecy. O the other had, producto plag volves the predcto of equpmet effcecy future plag perods order to pla a approprate producto volume. The hstorcal data o equpmet performace collected the observato perods must be traslated to forecasts for equpmet performace. For ths purpose, for each of the compoets of effcecy loss (DT, IT, ad CRE), assume there s a "actual" or reported fgure for the latest revew perod, ad there s a "stadard" fgure to be used plag calculatos made before results of the ext revew perod are avalable. For example, let Actual_DT deote the value of DT the latest revew perod, ad let Std_DT deote the forecast for DT to be used plag calculatos. Typcally there s statstcal fluctuato dow tme from revew perod to revew perod. A practcal way of forecastg such a parameter s to compute a expoetally-weghted movg average of the actuals. As s well-kow, ths s equvalet to updatg the forecast as a weghted average of the curret forecast ad the latest actual,.e., Std _ DT ( Actual _ DT ) + ( α )( Std _ DT ), α.0 where α s a smoothg costat wth value betwee 0 ad, typcally 0. or less for osy data. Ths strategy may be employed a straghtforward fasho to develop stadard values (.e., forecasts) for all parameters except MIT. Observatos ad cosequet updatg of ths parameter are oly possble for bottleeck equpmet assets, as all other assets are ot stressed suffcetly to experece mmum dle tmes. Gve a bottleeck asset, let Std_MIT deote our prevous forecast for MIT. We suppose a target cycle tme or WIP level has bee establshed for the factory. We develop a updatg scheme for Std_MIT as follows. As before, let PP deote the umber of uts that were plaed or demaded to be started to process step durg the observato perod, ad let EPT deote the effectve processg tme for step, cosderg all process steps =, 2,..., performed by a equpmet asset of terest. Let T deote the operatg tme the observato perod. The plaed load PL o the equpmet asset the observato perod, expressg the fracto of operatg tme that the asset s plaed to be egaged producto actvty, s computed as PL = ( PP )( EPT ) = ( T )( Std _ CRE). (7) 7

18 The ablty to update Std_MIT depeds o the lot release methodology for the factory. We ca classfy ay release methodology to oe of two types: utlzato-preservg, or WIPpreservg. Utlzato-preservg release methods costra releases to acheve a target utlzato,.e., a target value of PL. O the other had, WIP-preservg release rules schedule releases to mata a costat level of WIP or WIP workload o bottleeck equpmet assets. Examples of WIP-preservg release methods clude Workload Regulato [7], Starvato Avodace [8], Queue Maagemet [9], or Lear Programmg models corporatg Dyamc Producto Fuctos [0]. A example of a utlzato-preservg method s the uform release rule, whereby release quattes for a plag perod are calculated to acheve some target plaed load PL, ad lot releases of each product durg the perod are spread uformly through the plag perod ad released wthout regard for curret WIP level or curret bottleeck workload. A chage the amout of varablty the factory mafests tself dfferet ways, depedg o the type of release method. If a utlzato-preservg rule s employed, dle tme of the bottleeck assets wll be fxed, ad the chage wll mafest tself as a reducto the WIP level ad a reducto the average factory cycle tme. Ths s a dcato that a hgher utlzato ca be acheved for the target cycle tme. The factory ca therefore reduce MIT to a smaller value ad attempt a hgher utlzato. The maxmum reducto that ca be made MIT s ukow; the factory wll have to expermetally reduce MIT utl the cycle tme lmt s reached. O the other had, the WIP-preservg release rules preserve WIP levels at the bottleeck or e route to the bottleeck; a reducto varablty wll mafest tself as a crease utlzato for the same WIP level, ad thus a lower value of dle tme wll be observed. We shall assume here that a WIP-preservg release methodology s used. Due to fluctuatos varablty, some smoothg of actual dle tmes s approprate to make a forecast. Let Actual_IT deote the observed dle tme o the bottleeck asset. The we ca update our stadard for MIT a smlar maer as for the other effcecy parameters,.e., Std _ MIT ( Actual _ IT ) + ( α )( Std _ MIT ), α.0 (8) Gve the above updatg procedures for the stadard effcecy factors, we may defe the stadard for capacty equpmet effcecy of a equpmet asset as { Std _ DT Std _ MIT}( Std _ CRE). Std _ CEE =.0 (9) 5.4. Formal Defto of Equpmet Capacty To perform capacty aalyss, t s desred to express the capacty of a bak of detcal maches terchagably performg a partcular set of processg steps. Let Q deote the quatty of maches servce, ad let W deote the hours the bak wll be operated the plag perod. We assume the compoets of CEE are computed for each mache ad the averaged over the bak of equpmet. From these averages, a average CEE score s computed for the equpmet 8

19 type. (Sce the allocato of dle tme amog maches the bak s arbtrary, the effcecy score for the bak of maches may be more meagful tha the effcecy scores of dvdual maches the bak.) As dscussed earler, equpmet capacty should be expressed mache hours per plag perod. The capacty CAPY of the equpmet bak s the ( Std _ CEE)( Q)( W ). CAPY = (20) The result of (20) s the "rght had sde" of a capacty costrat a producto plag model. The coeffcets o producto varables to use a such plag model are the effectve processg tmes multpled by the le yelds from release or dvded by the le yelds to out, depedg o whether the varables represet producto starts or outs. I certa equpmet bays of may semcoductor fabrcato plats, there ca be several varetes of the same basc type of equpmet, e.g., several geeratos of the same type of mache. The dfferet types are able to perform overlappg but dssmlar sets of process specfcatos. For ths case of alteratve mache types, capacty s more complex to express. We omt detals here, but capacty costrats for sets of mache types may be formulated to qute accurately model the stuato for the purposes of producto plag. The terested reader s referred to []. 6. Data Acqusto Strateges We ow revew successful data collecto techques supportg equpmet effcecy ad capacty aalyses. 6.. Low-Tech Approach: Paper Forms Systematc reportg of dow tme ad dle tme for equpmet assets of terest has bee mplemeted may compaes usg paper forms flled out by producto operators. Fgures 2 ad 3 llustrate two dfferet approaches to form desg. Fgure 2 provdes a copy of the form developed for use at a offshore semcoductor test faclty operated by Harrs Corporato. Usg ths form, operators record the start tme ad completo tme of each (reportable) dow tme or dle tme evet, fllg the durato ( mutes) of the evet the approprate colum that dcates the reaso for the lost tme. At the ed of the producto shft, the form s tured over to a keypuch operator who totals the tme each of the reaso colums ad eters the results to a database. Total producto tme for the mache durg the shft s computed the database by subtractg the varous dow ad dle tmes from the shft durato. WIP-trackg ths factory s computerzed. Note that the form does ot requre the operator to record processg evets, sce rate effcecy ca be calculated from the WIP-trackg data. The form does make provso for the operator to wrte commets cocerg mache jams ad stoppages ad other remarks, whch ca facltate the research efforts of egeers vestgatg poor rate effcecy scores. Fgure 3 provdes a copy of the form use at a U.S.-based wafer fabrcato faclty operated by NEC Electrocs, Ic. O the form, the twety-four hour workday has bee parttoed to a 9

20 grd of fftee mute tervals. Producto operators assg a sgle code to each terval that best descrbes mache actvty durg the terval. The codes are lsted o the bottom rght; LR for "lot rug" s the code for producto tme. The same form s also used to record all producto lots processed by the mache. The umber of wafers s also recorded, from whch ay scraps may be deduced by comparg records for the same lot across dfferet equpmet. I the NEC factory, the durato of a process step for a sgle lot ad reportable dow tme evets are typcally thrty mutes or loger; thus the fftee-mute grd s felt to be accurate eough for estmatg total producto tme ad dow tme. Whle the form does ot facltate precse measuremet of dle tme, as log as rate effcecy s calculated, ay ureported dle tme wll stll be captured as effcecy loss. The form Fgure 3 s extremely easy to fll out; oce every fftee mutes, a sgle code s marked o the form by the operator. At the ed of a work day, the form s tedered to a keypuch operator so that data ca be recorded a computerzed database. Note that the total tme each category s smply computed as 5 mutes tmes the umber of etres. Usg ether type of form, assumg the database to whch the data s loaded also cludes theoretcal processg tmes ad the producto schedule for the mache, computato of rate effceces, OEE ad CEE as proposed ths paper ca be made from the formato o the form (supplemeted by WIP-trackg data the case of Fgure 2) Hgh-Tech Approach: Mache Sesg The low-tech paper form approach descrbed above reles o the dscple of the producto operators ad keypuch operators to properly record the ecessary data. I equpmet bays where each operator s resposble for a umber of processg maches, tmely ad accurate data collecto ca be very challegg. A more desrable approach would be realzed f each mache could dcate whe t s experecg dow tme or dle tme, thereby mmzg the operator's data collecto efforts. A aalog sgal ca be take from most major types of processg equpmet used semcoductor fabrcato that dcates whether or ot the mache s egaged a processg cycle. At the o mplat room servg three fabrcato areas Moutatop, Pesylvaa, operated by Harrs Corporato, ths type of sgal, humorously termed the "EKG" of the mache by the mplat process egeer, was used a semautomated equpmet trackg system, descrbed as follows. The "EKG" sgal from each mplater s chaeled to a laptop computer equpped wth a touch scree. Whe a certa threshold tme elapses wthout tato of a ew processg cycle o the mache, the computer souds a alarm to alert the operator, ad dsplays a touch-sestve scree upo whch the operator may select the reaso for mache actvty. The meu dsplays a tableau of reaso codes smlar to those the trackg forms Fgures 2 ad 3. Dsplay of the scree s subject to a "tme-out" mechasm, whereby f after a certa tme allowace o selecto has bee made by the operator, the actvty s automatcally assged to a "No Operator" subcategory of dle tme. Whe a ew processg cycle s tated, the computer records the elapsed tme of the category of actvty ad stores t the database. The trackg system also has aother user scree (called the "overrde scree") whereby the process egeer 20

21 or the mateace techcas ca dcate to the system that ther actvato of the mache s actually part of mache dow tme rather tha tato of a processg cycle. The system thus automatcally tabulates all dow tmes ad dle tmes, wth use of the touchscree meu ad the overrde scree descrbed above servg as the oly huma put requred. Whe ths applcato was developed 99, the Moutatop mplat room, cludg te o mplat maches, was the producto bottleeck for the Power product le of Harrs Corporato's Semcoductor Sector. Thus a cocerted effort was made to measure OEE ad capacty of the o mplat maches. I addto to the automato of equpmet trackg descrbed above, computato of equpmet effcecy was automated the system as well. The database supportg effcecy ad capacty computatos cluded the process specfcatos vewed by the producto operators performg mplat process steps. These specfcatos dcated, for each mplat process step, whch mplaters could be used, the mplat speces to use, ad the dose Kev to be appled. Aother table the database provded a cross-referece betwee relatg beam curret ( mcro-amps) to the speces ad dose appled for each of the te mplaters. A mathematcal formula relatg theoretcal mplat beam tme as a fucto of beam curret ad mplat area (the latter fxed for each mplater) was obtaed from the equpmet vedor ad programmed the database as follows: Beam_tme = (.602E-3) * Dose * (Area / Beam_curret) * (.0 / 60.0), where Beam_tme s expressed mutes, Dose s expressed Kev, Area s expressed square cetmeters, ad Beam_curret s expressed mcro-amps. Usg ths formula ad the crossreferece table, theoretcal mplat beam tmes were automatcally computed for each of the process specfcatos. For the case of very low doses, the results of the formula are ot applcable; to hadle such cases, mmum mplat tmes were establshed the database for hgh curret ad medum curret mplaters to whch the calculated values were compared. The database also cluded a table specfyg stadard tmes for the lag tme from mache start utl beam o for hgh curret maches, ad for the wafer dexg tme for medum curret maches. Stadard tmes also were developed for operator-performed loadg ad uloadg of the maches. I the Moutatop case, speces were dedcated by mplater, so that mache chageover tmes betwee dfferet process steps were eglgble. Usg the foregog data plus WIP-trackg results as put, computer routes the system automatcally computed rate effceces, OEE ad CEE for weekly revew perods. Capacty parameters for use weekly producto plag cycles also were updated automatcally. Note that by meas of the beam tme formula ad the establshmet of stadard tmes as descrbed, mateace of processg tme data was reduced to mateace of the table of process specfcatos used by the producto operators. Chages process specfcatos would automatcally result updated processg tmes calculated by the system at ru tme. I the calculatos performed for oe week early 99, mplater utlzato (as a percetage of total tme) raged from 6% to 76%, whle rate effcecy averaged 72%. Eve assumg 00% demad effcecy ad o scrap losses, overall equpmet effcecy would rage from 2