Journal of Materials Processing Technology 209 (2009) 60396047

Contents lists available at ScienceDirect

Journal of Materials Processing Technology

journa l homepage: www.e lsev ier .com/ l

Compu ro

F. KlockeDepartment of any

a r t i c l

Keywords:PolishingProcess monitSilicon nitrideMaterial remo

arche sines inA higancey takeroscot inteing ofeasuondurequitool bole opidatio

2009 Elsevier B.V. All rights reserved.

1. Introdu

Polishinqualities inand high foopticsmaning, e.g. forAnd is one oturing wheplanarisatioducted in obased on tresearcherstic insighto an advanthe polishisteel. In theand stabilitnecessarily

Followinthe procestions for an

Correspomany. Tel.: +4

E-mail add

0924-0136/$doi:10.1016/jction

g is the most frequently used technology if high surfaceterms of low roughness, minimised subsurface damagerm accuracies are demanded. It is an essential step inufacturing andof increasedusage in die andmouldmak-applications inmassive forming and injectionmoulding.f the enabling technologies in semiconductormanufac-re polishing is also referred to as chemicalmechanicaln (CMP), and numerous research activities were con-rder to enhance the understanding of the interactionshe online monitoring of the process. The progress ofin the eld of CMP technology has brought the scien-

t and the on it optimisation of machinery and processced level (Oliver, 2004). Particularly in comparison to

ng technologies used for glass, advanced ceramics andse elds the process can still be described as a black boxy, reproducibility as well as efcient processing is notgiven.g this argumentation it is as well of interest to monitor

sing of glass, advanced ceramics or polishing opera-y othermaterial. The fundamental understanding forms

nding author at: Fraunhofer IPT, Steinbachstr. 17, 52074 Aachen, Ger-9 241 8904 137; fax: +49 241 8904 6137.ress: richard.zunke@ipt.fraunhofer.de (R. Zunke).

a necessary basis for any convenient process optimisation. Reli-able data about the polishing process is needed either for theenhancement of the scientic insight or for improvements of theprocess stability in industrial applications. It is not sufcient togather data manually because of high efforts and inaccuracy aswell as non-uniform timing if periodical data is needed. Addition-ally, the manual monitoring of a high amount of measured processparameters is not feasible. Particularly the monitoring in industrialapplications requires an online data acquisition and processing torealise a standardised monitoring and to ensure the reliability ofthe data. Online gathered data enables the operator or an auto-matic control system to react on recent process disturbances forminimising rejects. The monitoring system also realises an exon-eration of the operator. A computer-based data acquisition allowsthe online calculation and visualisation of various process indica-tors and the identication of failures with implemented warningsignals. Thereby, an assistance of the operator is given so that hecan take immediate action in case of any aberration of the pro-cess. Furthermore, the data is gathered and stored in a standardisedapproach which allows the analysis by the means of statisti-cal methodology, i.e. process analysis by design of experiments(DoE).

2. Published approaches to monitor polishing operations

Several research projectswere already undertaken to enable thescientist to monitor the signicant indicators of the polishing pro-

see front matter 2009 Elsevier B.V. All rights reserved..jmatprotec.2009.08.014ter-based monitoring of the polishing p

, O. Dambon, U. Schneider, R. Zunke , D. WaechterProcess Technology, Fraunhofer Institute for Production Technology IPT, Aachen, Germ

e i n f o

oring

val mechanisms

a b s t r a c t

Despite of an extensive scientic resethe mechanisms and interactions of thorder to facilitate the research activitisition and analysis is recommended.information which can be used to enhvarious inspectionmethodswhichonlferometry and scanning electron micthe removal mechanisms and relevanity and reproducibility is the monitorTherefore, a variety of sensors and mthe process duration (e.g. pH value, cdifferent devices and high data ratescess monitoring. Thus, a monitoringenables the researcher to use the whthe functionality are given for the valocate / jmatprotec

cesses using LabView

regarding the polishing technologies of a variety of materials,gle components in the process are still not fully understood. Inthe eld of polishing the usage of computer-based data acqui-h data rate provides the researcher an appropriate density ofthe evaluation of stated hypothesis. This is normally based onplace after theprocessingof the sample, e.g.white light inter-

py. A solution for further elaborating the scientic insight onractions during the process and enhancing the process stabil-the signicant chemical, mechanical and thermal indicators.

rement devices are installed and used to gather data duringctivity, polishing work, coefcient of friction). The amount ofres a computer-based tool to realise an adequate online pro-ased on the LabView environment was implemented whichportunities of computer-based data processing. Examples ofn of the polishing behaviour of silicon nitride.

6040 F. Klocke et al. / Journal of Materials Processing Technology 209 (2009) 60396047

cess. Especially in CMP many researchers worked on a monitoringsolution which was investigated either to collect important onlinedata for monitoring in real time and analysis of the process con-dition or to enable the detection of the endpoint or even bothobjectives.viewswhictical ones. Tused as a ba

Inorderitoring of Cfollowing. OSlurry Mon2000). ThisHunter (20ture, conduconcentrati(2002) publtorque of th(2004) coveendpointinods. One walready pubresearch reitoring of twas develoacoustic emconditions.cannot be apredictive pfrom researmonitoringthat the traered.

As a magreatly in dinteractionsin CMP areaspects canpolishing pknowledge

First rescomponenthighlightedtion in ordematerial reglass. Klocktigate the pemphasiseddue to the cagent, poliscan result iing on theinvolved mthe integritminimisedcan be indthe workinsive mechaused the spwork in relthe differenhardness. Isteel withas the hardthese obsernear plasti

dominated the processing of the hardened steels (Klocke et al.,2005a,b).

The above mentioned investigations on process interactionsand removal mechanisms where based on manually gathered data

featu, theo invstats theditioon a hed an

xible

his plishinlinetheour oon tnd ts. Itstrianismll knre pcalcan bllowmpumo

hosecan

induove

itionestigantofiing ssuppcdatansisant iingof ometeed datheter-broacpolis

ign aoring

poliFig. 2the

orstiesas

ing ol asy.The indicators where derived from different point ofh couldbemechanical, thermal, chemical or even acous-he knowledge in the eld of CMP monitoring can besis to elaborate a solution for other polishing processes.toprovidea shortoverviewof the stateof theart inmon-MP processes some publications are highlighted in thene example for already available solutions is the CMPitor by Colloidal Dynamics 2000 (Colloidal Dynamics,system as well as the system which was published by01) present the capability of monitoring pH, tempera-ctivity, particle sizes, zeta potential, slurry pressure andon of particles in the polishing slurry. Matsuzaki et al.ished a CMP machine which measures additionally thee spindles and derives the uid lm thickness. Oliverrs the eld of the so called endpointing. The purpose ofg is to detect the nish of the process by various meth-ay is the measurement of motor currents which waslished in a patent by Sandhu et al. (1991). More recentsults by Gitis et al. (2001) are based on the direct mon-he coefcient of friction. Another way of endpointingped by Kojima et al. (2000) and uses the monitoring ofissions to characteristic signals for the different processDue to the advances in CMP research the technologyny more characterised by black arts but is a stable androcess (Oliver, 2004). The progress in the eld of CMPch to industrial usage shows clearly that the processof polishing operations was successful and useful andnsfer to other polishing applications should be consid-

tter of fact the various polishing technologies differetail due to the nano-scale characteristics of processand mechanisms. Therefore, many of the approachesnot applicable for other applications. However, somebe transferred to support the investigations of other

rocesses where stability is still an issue or where theis still insufcient to fully understand the process.ults for the process monitoring of polishing of optics were published by Hambcker (2001). Hambckerthe importanceof several indicators of the slurry condi-r to examine the interactions and specify the accordingmoval mechanisms in chemo-mechanical polishing ofe et al. (2005a,b) used a similar approach to inves-olishing process of silicon and calcium uoride andthe importance of a well chosen polishing system

omplex interactions between polishing pad, polishinghing slurry and workpiece surface. These interactionsn various mechanical and chemical reactions depend-material properties and the chemical reactivity of theaterials. On every important objective of polishing isy of the surface layer which can be characterised bydefects and cracks or even micro dislocations. Theseuced by the mechanical and chemical conditions ing gap of the process. Dambon investigated the abra-nisms of steel polishing using diamond slurries andecic energy derived from the determined polishingation to the amount of removed material to amplifyces in mechanisms of polishing steel with various

n order to remove a similar amount of material thelow hardness tended to consume much more energyened steel. Dambon (2005) was able to prove thatvations were due to micro ploughing and a surfacecation of the soft steel instead of micro cutting which

whichthelessorder tcan beenableits conbasedacquir

3. Fle

In tthe poand ontors ofbehaviinsighteters aprocesin indumechathe wesoftwaonlinement cdoes aand coonhighwere cery andalso in

Theacquiscal invimporttion offollowdata isholisticess coimportmachinresultsof paracollectallowscompuan appof the

4. Desmonit

Theeters (effortsindicatpropersideredconsistas welvelocitred the disadvantages mentioned in Section 1. Never-results showed the importance of several indicators inestigate the process at the highest stage. In summary ited that the computer-based monitoring of the processscientist to gain insights on the running process and

n. Additionally, it allows a convenient process analysisigh data density and comparability of the standardisedd stored data.

and mobile monitoring of the polishing process

aper, an approach to a computer-based monitoring ofg process is described. The objective is the monitoringcalculation of mechanical, chemical, thermal indica-

process which allows the examination of the polishingf variousmaterials. The approach can be used to gain anheprocess interactions anddifferent inuencingparam-o monitor the stability of any conventional polishingis intended to be used in research activities as well asl environments where specic questions on removals are to be claried. The approach was implemented inown programming environment called LabView. Thisrovides powerful capabilities of data acquisition andulations as well as online data analysis. The environ-e congured to read data from any sensor or bus andthe online calculation and visualisation of the acquiredted data. The concept of the monitoring system is basedbility andexibility. Therefore, allmeasurementdevicesn to allow the adaption on different polishing machin-easily be used not only in laboratory environments butstrial ones.rall objective is the elaboration of standardised dataand storage toprovide abroaddata basis for technologi-ations. Fig. 1 explains the approachwhich includes threesteps: online data acquisition and visualisation, inser-ne gathered data and data analysis based on principalstatistical methodology. Thus, the continuously acquiredlementedbydiscontinuously acquireddata to provide abasis of thepolishingprocess and todocument thepro-

tently. The discontinuously gathered data does includendicators such as weight loss of the workpiece after theoperation toderive the amount of removedmaterial andptical surface measurements to evaluate the inuencesrs on the resulting surface quality. The total amount ofta can easily be imported in a software solution whichanalysis by statistical means. The consistent usage ofaseddataacquisition, calculationandanalysis isusedas

h to support the investigations of technological aspectshing process.

nd implementation of the computer-basedsystem

shing process is inuenced by a great variety of param-). In order to establish a monitoring with reasonablemain inuencing parameters and most signicant

have to be ascertained. In this context, the materialof the workpiece and the polishing machine are con-xed. The main parameters are the polishing systemf polishing tool, polishing agent and polishing slurry,

the machining parameters, e.g. pressure and relative

F. Klocke et al. / Journal of Materials Processing Technology 209 (2009) 60396047 6041

analy

4.1. Measurcondition

Fig. 3 prdevices. Onon the descant inuenadditionallytion about

onitoFig. 1. Approach to a computer-based data acquisition and

ed and derived indicators for monitoring the slurry The movides an overview about the installed measurementthe one hand, the proposed monitoring system focusescription of the slurry condition, due to the signi-ce on the performance of the polishing process and,, because the reow of used slurry can carry informa-the mechanisms and interactions in the working gap.

ical properand zeta-poafter the pring gap beother handacteristics oby the monand the ene

Fig. 2. Overview of the great variety of inuencing parameters insis of the polishing processes.

ring system measures important physical and chem-

ties of the slurry, such as pH, electrical conductivity,tential. The slurry temperature is measured before andocess as the slurry is constantly pumped into the work-tween polishing tool and workpiece surface. On the, in order to gather an insight in the energetic char-f the process the power of the spindles is measureditoring system. It is used to derive the process workrgy in relation to the amount of material removal in a

polishing (Hambcker, 2001).

6042 F. Klocke et al. / Journal of Materials Processing Technology 209 (2009) 60396047

Fig. 3. Overvimeasurement

qualitativethe coefcieof the triboprocess.

4.1.1. SlurrThe slurr

reowwithmeasuringtemperaturthe working

4.1.2. pH vaThe pH v

tration of hof a liquid.the formatiamong otheface chargepolishing sltion a glassis used.

4.1.3. ElectrThe elec

to conductthe movemdepends onGiven no chin conducticoncentrati

4.1.4. CalcuThe zeta

ries. Stabilichange durand sedimea slurry.

Particulasizes are usable for micof slurry pa

The zetaculated. Thamplitude.

in LabView, using Eq. (1) (Delgado et al., 2005), where ESA repre-sents the measured electro-kinetic sonic amplitude, the volumefracture of particle, the difference of density between particlematerial and polishing liquid, c the velocity of sound and the

ncy:

= E

easung pr

maiqualiworky anl amorkinmecrkpiion.ocessivatinitolishinlar,

wer igicalhe prof toing t

Deter

polis of ttact

ol + pinteworking sconv

p d

pew of the monitored indicators and the placement of the accordingdevices.

manner. The data also allows the online calculation ofnt of friction and herewith a qualitative considerationlogical condition in the working gap of the polishing

y temperaturey temperature ismeasuredboth in the inowand in theconventional thermo couples. This enables not only theof the absolute temperature but the calculation of thee difference, which indicates the heat development ingap.

lue of the slurryalue is dened as the negative logarithm of the concen-ydrogen ions and describes the acid or alkaline effectA change of the pH indicates chemical reactions withon of hydronium or hydroxide ions. The pH inuencesrs chemical reactions, solution processes and the sur-of particles and forms a widely discussed property ofurries for chemo-mechanical polishing. In this applica-membrane based pH electrode with liquid electrolyte

ical conductivity of the slurrytrical conductivity describes the ability of a materialelectricity. The conductivity of solutions is based onent of electrical charged particles, such as ions andthe type of the solved ions and its relevant amount.

freque

d(w)

4.2. Mpolishi

Thegain ain thelated boveralthe wofor thethe woformatthe prfor actthe mothe poparticuing potribolo

In tdrivescaptur

4.2.1.energy

Thepowerout con

p = ptoThe

ishingfollowrstly

W =

W =ange in the existing type of ions in a solution, a changevity can be taken as indicator for changes of the ionson.

lation of the zeta potential of the particles in the slurrypotential characterises the physical stability of slur-

ty means that the particle size distribution does noting a specied time interval. Therefore, agglomerationntation form two driving mechanisms of instability of

rly in CMPwhere slurrieswith preferably small particleed, large particles in the slurry are frequently account-roscratches (Aytes et al., 2003). Park stated aggregationrticles as a source of large particles (Park et al., 1998).potential cannot bemeasured directly, butmust be cal-e integrated device measures the electro-kinetic sonicThe calculation of the zeta potential was programmed

A normavolumeof rregarding tmentionedenergy.

4.2.2. CalcuThe elem

piece and pregarded anassumptionwhich descthe polishinquotient ofthat frictioning power.the relativeSAc

(1)

red and derived indicators for the monitoring of theocess as a tribological system

n objective of the integrated power measurement is totative view inside the energetic processes taking placeing gap. The employed polishing work can be calcu-integration of the polishing power over the time. Theunt of energy can be employed in different actions ing gap. On the one hand, some of the energy is usedhanical interactions between the polishing agent and

ece surface, for example for plastic deformation or chipOn the other hand, the energy which is brought intocould be transferred to heat and as well be needed

ng chemical reactions. These considerations show thatring of the power of the spindles and the derivation ofg power contributes to the process understanding. In

the relationship between material removal and polish-s of interest for the process analysis to characterise thecondition in the working gap of the polishing process.oposed monitoring system the performance of electricol and workpiece spindle are measured separately byhe currents and voltages at the frequency converters.

mining the polishing power and deriving the specic

shing power is calculated by adding the two measuredhe spindles minus the both idle powers measured with-between workpiece and tool (Eq. (2)).

workpiece pidle (2)gration of the polishing power is resulting in the pol-using Eq. (3). The integration is approximated by the

ummation, because the analogue measured power iserted to a digital signal.

t (ideal relation),

t (approximated formula) (3)

lisation of the polishing work by dividing through theemovedmaterial allows to compare polishing processeshe different energetic efforts and efciency. As alreadyin Section 2, the normalised value is called specic

lating the coefcient of frictionents of the polishing system, e.g. polishing pad, work-olishing slurry, and the resulting interactions can bealogically as a tribological system (Dambon, 2005). Thissuggests the calculation of the coefcient of friction

ribes the tribological condition in the working gap ofg process. The coefcient of friction is dened as thefriction force (Fr) and normal force (Fn). It is assumedal interactions cause the complete measured polish-

In Eq. (4) ppolishing represents the polishing power, vrelvelocity which is the velocity between workpiece and

F. Klocke et al. / Journal of Materials Processing Technology 209 (2009) 60396047 6043

em ba

tool, p the lworking ga

Fr =ppolishi

vrel

This resucoefcient o

= ppolishp Af v

Additionmonitoringeach run. Thas well as m

4.3. Implem

Thecomon a niteinput, initiatrol of deviand data redata), stopsheet writinthe operatimenu appethe rst tabname of exprocess parloads all rethe workpieIf necessaryuser interfaperature difand powerthe reprodu

erimoring

pracolishrse ess, cockg comicatioms oandFig. 4. Graphical user interface of the monitoring syst

oad (pressure) and Af the area carrying the load in thep.

ng and Fn = p Af (4)

lts in Eq. (5) which is used for the calculation of thef friction in the proposed monitoring system.

ing

rel(5)

ally to the measured and calculated parameters, the

5. Expmonit

Theof the pin advehardnemal shbearinor replthe terqualitysystem calculates online several statistical values foris includes the average values and standard deviationsinima and maxima of the indicators.

entation of the system and graphical user interface

plete implementationof themonitoring systemisbasedstate machine with the following main states: userlising of the system and the measurement devices, con-ces, measurement (including visualisation, calculationcording), end of measurement (input of discontinuous(after last measurement, further calculation and resultg). A complex graphical user interface (GUI) facilitates

on by users. At the start of the programme a pop-upars for the input of all required data by the user. Onof this menu the user has to enter general data (user,

periment), specications of the polishing system andameter. Based on these data the monitoring systemsquired data, such as idle power of spindles, density ofce material, viscosity of the slurry etc, from a database., the user can edit the data. Fig. 4 shows the graphicalce. The graphs reveal the online development of tem-ference, pHvalue, electrical conductivity, zeta potentialand the graphs of the last two runs in order to examinecibility of the process.

tions. Besidmechanismstand. Theris used to ginteractiontions is ancontrolledformed geoKlocke et al

5.1. Machinsystem

The inveSL120polisnar and sphprecision opsirable inubecause it iishing slurrof 5 l and th

The invsurfaces binterferomemicroscopysed on LabView (excerpt).

ental setup for the evaluation of the proposedsystem

ticability of the approach is validated by investigationsing behaviour of silicon nitride which is primarily usednvironments and applications, due to its extraordinaryorrosion resistance, low thermal expansion, high ther-resistance and low weight. Example applications areponents and moulds and dies for sheet metal formingn of optics. To ensure a high quality of the products inf tribological and optical functionality a high surfaceintegrity has to be maintained by polishing opera-e of its numerous applications the material removals in polishing of silicon nitride is still not fully under-efore, the computer-based data acquisition and analysisain scientic insight on the relevant mechanisms ands. The important ambition of the ongoing investiga-efcient design of polishing strategies for a computerpolishing process which allows the processing of freemetries of complex ceramics geometries as shown by. (2008).

e tool used for the implementation of the monitoring

stigations were carried out on a Satisloh Synchrospeedhingmachine. Thismachine is suitable for polishingpla-erical lenses and is widely used in the manufacturing oftics. The use of this equipment ensures that any unde-ences arising from kinematic instabilities are avoided

s state-of-the-art and featuring a high stability. The pol-y circulates ina closed loop. The slurry tankhasavolumee temperature is controlled by a heating/cooling device.estigations include the inspection of the polishedy optical measurement systems, i.e. white lightter and laser interferometer, and scanning electron. The material removal rate is quantied by weight

6044 F. Klocke et al. / Journal of Materials Processing Technology 209 (2009) 60396047

measurements. The special synchrospeed kinematic allows theassumption of a homogeneous material removal on the completesurface. Therefore, the amount of removed material can also beexpressed in a height difference, calculated on the basis of theweight loss

5.2. Materi

In ordermonitoringisostatically

The objecess interacmaterial recan be realithe silicon-imen weregrinding kinbased poliswater (conc

5.3. Experim

For the pters on the rrate and suEach sampof 5, 5, andrial remova20min the sThepolyurefollowing ptotal in ordeorder to extterm experto a total po

The shorences of inpof polishingthe basis toslurry and t

5.4. Hypoth

In generishing rangand fatiguesuch as oxidParticularlypolishing wtechnique (

Formerresults usinsilicon nitriwere achievsurface quaslurry tendethe one witresults withwith diamocosts for th

Followinthe high efis based onmechanismthe silicon

as a catalyst under the inuence of high pressure and tribologi-cal interactions in the working gap and the combination with theso called chemical tooth ability of ceria (Hu et al., 1998) Whereas,the removalmechanisms inpolishing advanced ceramics usingdia-

slurr

ults

s sectpliednism

ort-t

verifrideringf siors ding te ofingingthe ttherties,al prothe

P p

shorst sithestatso chichThechinal rerevenearden. Th

in theaph)e accts.6 shality(righTheng Ramoster oalysichievshoweas

Besilting

ual vdueandishinre anafter each process step.

als and polishing systems

to illustrate the capabilities of the computer-basedit is used to investigate the polishing behaviour of hotpressed silicon nitride.

ctive is to elaborate scientic understanding of the pro-tions. Based on this knowledge, the optimisation of themoval rate, the surface quality and the form accuracysed. Therefore, fundamental investigations of polishingbased ceramics are undertaken andevaluated. The spec-ground by using diamond grinding wheels with a cupematic. The polishing system consists of polyurethane-hing foils as tools and ceria slurry based on deionisedentration 60g/l).

ental procedure

urpose of investigating the inuences of input parame-esponse of the output parameters, i.e.material removalrface quality, short-term experiments were conducted.le was polished for 20min divided into three steps10min. After each single step, the amount of mate-

l was measured by determining the weight loss. Afterurfacequality and formaccuracywasmeasured aswell.thane foamwasdressed toprovidea fresh surface to therocess step. Every specimen was polished for 60min inr to proof stability and reproducibility of the process. Inend the knowledge about the polishing behaviour long-iments are realised with several steps (20min each) uplishing time of 8h.t-term experiments are conducted to identify the inu-ut parameters, e.g. pressure, velocity and concentrationagents in the slurry. The long-termexperiments deliverelaborate an understanding of, e.g. the life time of thehe stability of the process.

esis for material removal mechanisms

al, the material removal mechanism in lapping and pol-e from pure mechanical character, e.g. abrasion, erosion, and pure chemical character, e.g. chemical reactionsation or dissolution of the material (Evans et al., 2003).due to the hardness of advanced ceramics, abrasiveith diamonds represents a widely applied polishingChinn, 2002).investigations (Klocke et al., 2007) revealed satisfyingg ceria and diamond based slurries for the nishing ofde samples. Material removal rates of up 0.3m/mined. Both polishing slurries realised highly reproduciblelities in the range of several nanometers. However, ceriad to result in a more efcient polishing operation than

h diamond slurry due to less machining efforts. The bestceria slurry were achieved with the same pressure as

nd slurry but with less revolutions, and certainly lesse polishing agent.g the argumentation by Jiang and Komanduri (1998)ciency of polishing silicon nitride with ceria slurryan interaction of chemical and mechanical removal

s. The mechanism can be explained by hydrolysis ofnitride surface in aqueous solutions where ceria acts

mond

6. Res

Thiwas apmecha

6.1. Sh

Tocon nitmonitoence oindicat

Takincreasincreasmachinand dtious opropermateriwell as

dzdt

= K

Thethe molowingfor theof thedata wgrams.the mamatericlearlytures lithe tensamplefound(left grand thdata se

Fig.face quand Rteters.featurivaluescharacThe anwereawhichand a mresult.all resuthe uster RtFigs. 5for polpressuy is assumed to be an abrasive process.

and discussion

ion provides examples, inwhich themonitoring systemto enhance the scientic insight on material removal

s in polishing of advanced ceramics.

erm experiments of polishing silicon nitride with ceria

y the stated hypothesis, experiments of polishing sili-with ceria slurry were conducted. The computer-basedsystem was used to gain information about the inu-

gnicant input parameters on the response of theened in Section 4.he Preston Hypothesis (Preston, 1927) for granted anthe material removal rate should easily be realised bythe pressure p and the relative velocity vr as the mainparameters. In Eq. (6) dz represents the removed heightime interval. The Preston coefcient KP stands for var-inuences on the process which include the materialthe surface quality of the prior machining operation,operties of the polishing agent and the polishing pad asr inuencing parameters as indicated in Fig. 2.

vr (6)

t-term experiments revealed that the pressure featuresgnicant inuence on the material removal rate. Fol-DoE methodology, one of the rst diagrams of interestistical analysis of experimental results is the diagramalled main effects. The left graph in Fig. 5 shows theis the basis for the highly aggregated main effect dia-right graph of Fig. 5 shows the main effect diagram ofing parameters pressure and relative velocity on themoval. The signicance of the parameter pressure isaled by the high slope of the curve which nearly fea-ity. However, the increase of the relative velocity showscy to inuence the surface quality of the silicon nitridee pattern of the main effect diagram can be logicallydetailed data given in the left graph. Additionally, Fig. 5points out the usual slide variations of polishing resultsording standard deviations of the single experimental

ows two graphs to emphasise the average resulting sur-in terms of the roughness parameters Ra (left graph)t graph) in dependence of the main machining param-surface quality of the polished samples is very high,values lower than 5nm for all resulting surfaces and Rt

tly around 50nm. This is due to the chemo-mechanicalf the material removal mechanism (Klocke et al., 2007).s of the Ra graph shows that the lowest, i.e. best, valuesedbyhighpressureand lowrelative speed. TheRtgraphs the maximum distance between a measured depth

ured height of the surface roughness leads to the samede of two values which have to be labelled as outliersRt values follow an anticipated pattern and stay within

ariation which is common for the roughness parame-to its high sensitivity. The combined interpretation of6 arises that high removal rates and low roughnessg of silicon nitride with ceria can be achieved by highd low relative speeds. Therefore, this combination of

F. Klocke et al. / Journal of Materials Processing Technology 209 (2009) 60396047 6045

Fig. 5. Detaile ations (left graph), main effect diagrams for the material removal rate toevaluate the d

Fig. 6. Inuen rithmroughness Rt (

parametersin the follow

6.2. Long-te

Due todependentresearcherbetter undean overall p20min to dloss. The prpH and theslurry condAny changementionedconclusionscess stabilitof slurry inresearcherinow has dcess and ren

6.2.1. MoniAn indic

anism in Sevalue (Fig. 7chiometricon theenvirtively ammof the pH vvalidity of

icallyeasud showing all measured material removal rates and the according standard deviependency on the machining parameters (right graph).

ce of the machining parameters on the resulting surface roughness in terms of aright graph).

was chosen for the long-term experiments discusseding section.

periodples mrm experiments of polishing silicon nitride with ceria

circulation of the slurry the monitoring of time-changes of chemical andphysical properties enables theto draw conclusions on the removal mechanisms. For arstanding a long-term experiment was conducted witholishing time of 8h. The process was stopped everyetermine the removal rate by measuring the weightoposed monitoring system facilitates the survey of, e.g.electrical conductivity as important indicators of theition and its inuence on the material removal rate.s of the slurry condition are observed by the beforeindicators and enable the researcher to draw onlineon mechanisms and interactions as well as the pro-

y. The monitoring difference between the temperatureow and outow should show constant values. If not thewill be alerted that, e.g. the volume ow rate of slurryecreased which causes instabilities of the running pro-ders the results that are not useful.

toring the time-dependent evolution of the pH valueator of the hydrolysis of silicon nitride stated as a mech-ction 5.4 is given by the observed increase of the pH). Jiang and Komanduri (2001) discussed several stoi-

calculations of possible chemical reactions. Dependentonmental conditions it is assumed thatnitrogen respec-onia is a reaction product which leads to the increasealue. In order to determine a second indicator for thethe hypothesis, samples of the slurry were extracted

were underan increase0.1mg/l at13mg/l aftetion 5.4 waa slide decrthese timea while. Fodecrease oide concentthe equilibFig. 7 showinterrupts.increases qments. Afte

Fig. 7. Time-dlated hydroxidetic average of the roughness prole Ra (left graph) and maximum

during the long-term experiments. With these sam-rements of the concentration of ammonium hydroxide

takenusingphotometric detection. The results revealedof the concentration of ammonium hydroxide fromthe beginning of the long-term experiments up tor 8h. Thus the validity of the hypothesis stated in Sec-s afrmed. The pH graph in Fig. 7 shows three timesease, i.e. at the duration of 120, 200, and 380min. Atsteps the long-term experiments had to be stopped forr the determination of the reasons for the describedngoing research is needed. Additionally, the hydrox-ration was calculated based on the monitored pH withrium constant of water (Eq. (7)). The second graph ins the anticipated linear trend with three clearly visibleIt can be recognised that the hydroxide concentrationuite rapidly in the rst 300min of the long-term experi-r that point, a slide transition of the increase can be seen

ependent evolution of the pH value and correlation with the calcu-e concentration in the long-term experiments.

6046 F. Klocke et al. / Journal of Materials Processing Technology 209 (2009) 60396047

Fig. 8. pH sensitivity of the material removal rate in polishing silicon nitride withceria slurry.

and it decelerates because thehydroxide concentration approachesthe saturation of hydroxide in ceria slurry. These ndings could nothave been detected in such a distinct way by solely analysing thepH graph.

c(OH) =1

Furthermof the mateparametersto alkalinerate decreaThese resuinvestigatiovalue range

6.2.2. Moniconductivity

A furtheelectrical coformation oshows the wincrease ofport the hychemical reesis on theSection 5.4.

6.2.3. Monipolishing po

In Fig. 1rate and thea correlatiocan achievethe runningcoefcient oaccounts fotions in the

Fig. 9. Time-dremoved mate

Fig. 10. Correlationof thematerial removal rateand theonlinecalculatedcoefcientof friction.

thusmissing stability. By analysing thedata of the long-termexper-iments in Fig. 10 the researcher learns that the height of the graphof the coefcient of friction already gives an impression of the trend

mateibleentsativeonclhicha ofpareecaured tdditalsog ga

en thal fond t

e (Haear cantcom

nablof dier ex12 itnt inhelef douhigheaphferend thaf thefcioveddecrKw

0pH, Kw equilibriumconstant ofwater (7)

ore, the investigations conrmed the pH sensitivityrial removal rate. Experiments with identical processbut avariationof thepHvalue fromacidic (pHaround3)(pH around 12) demonstrate that the material removalses in acidic as well as in alkaline environment (Fig. 8).lts correlate with the results of the above describedns where high removal rates were realised with a pHfrom 5.5 to 8.5.

toring the time-dependent evolution of the electrical

r clue on the hydrolysis is given by the increase of thenductivity, shown in Fig. 9. The increase indicates thef ions, e.g. ammonium hydroxide. The second grapheight loss of the sample. The correlation between the

conductivity and the amount of removed material sup-pothesis that the material removal is partly driven byactions. The results argue for the validity of the hypoth-chemo-mechanical mechanisms which was stated in

toring the process based on coefcient of friction andwer0 the time-related evolution of the material removalcoefcient of friction is given. The graphs clearly show

nwhich allows to draw the conclusion that the operatora rst impression on the material removal rate duringprocessbyobserving the resultsof theonlinecalculatedf friction. During a single polishing step a stable processr a stable value of the coefcient of friction. Any aberra-graphs indicate aberrations of the running process and

of theis posssuremAlternsame ction wthe areto comtries bcompa

In atem isworkinbetwemateritypes aduciblthe linsignic

Thework eciencyNo othof Fig.ing ageNevertgain omuchThe grthe difin minprice oasnoteof remishingependent evolution of the electrical conductivity and amount ofrial in the long-term experiments. Figrial removal rate in the currently running step. Thus itto preview the process results before any weight mea-were taken to quantify the amount of removedmaterial.ly, observing the monitored polishing power allows theusions. The sole difference is that the coefcient of fric-is calculated as shown in Eq. (5) also takes into accountcontact between tool and workpiece. Thus it is possibleseveral investigationswith differentworkpiece geome-se the value of the coefcient of friction is normalisedo the value of the polishing power.ion to the monitoring of the slurry condition the sys-applied to investigate the energetic coherences in thep. Hambcker already mentioned a linear correlatione employed polishing work and the amount of removedr the chemicalmechanical polishing of different glasshereby concluded that the process is generally repro-mbcker, 2001). The long-term experiment conrmsorrelation, as shown in Fig. 11. This indicates, that nochange in the energetic coherences took place.parison of different data sets regarding the polishinges further conclusions. As an example the energetic ef-fferent concentrations of ceria slurries is given in Fig. 12.perimental conditions were changed. In the left graphis shown that increasing the concentration of polish-duces an increase of the amount of removed material.

ss, the increase does not feature a linear behaviour. Thebling the concentration of ceria from 30 to 60g/l isr than the gain of 60120 and to 180g/l, respectively.

on the right in Fig. 12 analyses the specic energy oft concentrations. A low value is favourable but keepingt doubling the concentration also means doubling theslurry, the concentration of 120 and 180g/l is regardedent. Thecostsof the slurryaredoubledbutas theamountof material is increased by half the time needed for pol-eases by one third. The drawn conclusion is that 60g/l. 11. Evolution of the polishing work and specic energy.

F. Klocke et al. / Journal of Materials Processing Technology 209 (2009) 60396047 6047

Fig. 12. Using ing agderiving the p

does lead toremoval rat

7. Conclus

In orderinteractionsanalysis waknown Labtem integrain order tostability aning powertemperaturcient of frmonitoredgation leveprocess stabvention of r

The functigations ofmajority of

The monrials. Futureadjustmentregarding msensitive prin industriamachinery.sented apprsupport thein serial pro

Acknowled

We sincfor nancia(RWTHAacUniversity a

References

Aytes, S.D., Armental inv

ersity5th B.E., 20l Dyna, O., 2is. RW, A.V.,surem753.J., PauullanAnn.Vinogerialsrnatioety, Saker, ShrospGutmg meR.J., 20Surf.

., Komr 215,., Kopolis.., Damum uF., Damon th180F., Zude. Iny, pp.F., Brel polisems aufactuT., Miyn of C932ki, S.,ta logess co.R. (Edthe monitored polishing work to describe the inuence of concentration of polishrocess efciency by analysis of the specic polishing energy (right graph).

an overall acceptable performance regarding materiale and costs for the slurry.

ion

to elaborate a scientic insight regarding the processin polishing a computer-based data acquisition and

s realised. The application is programmed in the wellView programming environment. The monitoring sys-tes numerous measurement devices and calculationsfacilitate the investigations and to indicate the processd reproducibility. The monitored indicators are polish-resp. work, pH value, conductivity, zeta potential ande of the slurry. The online calculated indicators are coef-iction, the specic energy, and average values of theindicators for statistical analyses on a higher aggre-l. This monitoring system can detect disturbances ofility, which allows early identication or even the pre-ejects in an industrial production.tionality of the presented system was veried by inves-the polishing behaviour of silicon nitride. Therefore, theindicators were exemplary discussed in the paper.itoring system can be used for a great variety of mate-work will implement a process control, e.g. for onlineof the pH value in order to ensure the best performanceaterial removal rate and resulting surface quality in pHocesses. Due to themobility of the system it can be usedl environments and easily adapted to various polishingBeside the usage in ongoing research activities, the pre-oach has already been used in industrial applications tounderstanding of specic questions on the interactionsduction.

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Univthe 1

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thesDelgado

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Computer-based monitoring of the polishing processes using LabViewIntroductionPublished approaches to monitor polishing operationsFlexible and mobile monitoring of the polishing processDesign and implementation of the computer-based monitoring systemMeasured and derived indicators for monitoring the slurry conditionSlurry temperaturepH value of the slurryElectrical conductivity of the slurryCalculation of the zeta potential of the particles in the slurry

Measured and derived indicators for the monitoring of the polishing process as a tribological systemDetermining the polishing power and deriving the specific energyCalculating the coefficient of friction

Implementation of the system and graphical user interface

Experimental setup for the evaluation of the proposed monitoring systemMachine tool used for the implementation of the monitoring systemMaterials and polishing systemsExperimental procedureHypothesis for material removal mechanisms

Results and discussionShort-term experiments of polishing silicon nitride with ceriaLong-term experiments of polishing silicon nitride with ceriaMonitoring the time-dependent evolution of the pH valueMonitoring the time-dependent evolution of the electrical conductivityMonitoring the process based on coefficient of friction and polishing power

ConclusionAcknowledgementsReferences