Predictive maintenance – thestrategythatpredictswhenmachinerywillrequiremaintenance

Edition04/2016

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“Damage can always be prevented if appropriate steps are taken in due time.” There’s no better way of describing the main benefit of predictive maintenance.The principle is based on three pillars:1. Permanently monitoring the condition of a “healthy”

system to detect wear or variations from the normal condition early on – fluid condition monitoring

2. If a variation is detected, in the simplest case only an alert is issued, but a better option is to determine and output the remaining service life of a component or a subsystem – as per Industry 4.0

3. On the basis of this “condition” of the system, costly downtime can now be reliably avoided and inexpensive maintenance can be scheduled.

This type of “condition-based” strategy creates the conditions for enabling negative changes in hydraulic and lubrication systems to be detected early on and countermeasures to be initiated in due time. Virtually every fluid system comes with a multitude of ways to consistently monitor the condition of the fluid and save on unnecessary costs.

Inhydraulicandlubricationsystems,friction,wear,leaksandexcess temperatures can contribute to the operating fluidbecoming contaminated,with solid particle contaminationorwater, forexample.Thiscontaminationthengoesontocauseerrorsincomponentsandsubsystemsandultimatelyinthesystemasawhole.Furthermore,thenormalageingprocessof thefluidcausesperformance losses thatoftenresult insystemdowntime. Inorder toprevent thesetime-consumingandcostlyconsequences,monitoringtheconditionoftheoperatingfluidisofmajorsignificance.Theconditionoftheoperatingfluidiscomparabletoa“fingerprint”oftheoverall condition of the system.Systems for permanentlymonitoring fluids (online fluid conditionmonitoring) in this

contextbecomeacrucialsystemcomponent.Theysupportbothmachine owners andmanufacturers in their effortsto increasemachine availability, performonly scheduledmaintenancewhen possible, and ultimately reduce theoverall cost of themachines over theirworking life. Fornumerousproductionplantsandinfleetmanagement,thecost-baseddecision-makingcriteriafornewinvestmentsisnolongerjusttheprocurementcostofamachine.Whatisalsoevaluatediswhatisreferredtoasthelifecyclecost(LCC),orthecostoverthemachine’sentireservicelife.Inadditiontoprocurementcosts,thisLCCalsoincludesthecostsforoperationanddisposal.Thisultimatelyreducestheactualoverallcostperunitinordertostaycompetitiveintheglobalmarket.Add to thiscertaincustomer requirementsthathavechangedovertime.Currentcustomerrequirements,usingtheexampleofmobileminingequipment:

zHigherproductivity zGreaterbreakoutforces zHigherefficiency

Tomeet these demands, the industry increasingly reliesontheuseofthefollowing(inadditiontoothermeasures):

zElectro-hydraulics zHighersystempressures zTightertolerances (nowinthesingleanddouble-digitµ-range)

Aninevitableside-effectofthistrendisthefactthatmachinesarebecomingincreasinglysensitivetocontaminationintheoil.Ifthecleanlinesslevelisnotmonitoredandeffortsforimprovementnotmadeearlyenough,wearand tearcangraduallyreducethesystemefficiency.Sometimesthesys-temefficiencycanfallby20%beforethemachineoperatorevennoticesaproblem.

Edition04/2016

Predictive maintenance – the strategy that predictswhenmachinerywillrequiremaintenance

zContinuousmonitoringofthemachineryviatheconditionofthefluidandthefluidconditioningcom-ponents

zIntegralpartofapredictivemaintenanceplan

zMaintenanceintervalscanbeplannedaccordingtoneed

zHelpstorevealdefectsanddevelopingdamageinduetime

zHelpstopreventunplannedmachinestoppages

Fluid Condition Monitoring at a glance:

zIncreasesavailability,safetyandproductivity

zIncreasesefficiency,becausecomponentsnolongerhavetobeover-sized

zAspartoftheLifeCycleManagement,costscanbesaved

This canbepreventedbyusingefficientFluidConditionMonitoring(FCM)sensorsandsubsystems.Thesedetectthedeviationsatanearlystageandenabletheusertotakepredictivecorrectiveactioningoodtime.

Market requirementsThe currentmarket requirements for productionmachinesareshowninFig.1.Theseapplygenerallytobothstationaryandmobilemachines.Twobasicrequirementsare:

z Immediatealarmintheeventofseriouserrors zReductionintheunitcostsofaproduct (where“product”canrefertoamachine-producedpartorahauledtonnageperhour)

In order tomeet these requirements, themachinesmustalwayshavethecharacteristicsinFig.1.

Customer specification Fluid condition sensor

Alarm for (fatal) errors Monitoring of the zplannedfluidoperationproperties(temperature,purity,etc.) z installedfluidconditioningcomponents(cooler,filter,etc.)

Reduced unit costs Reduced life cycle cost zProcurementcosts zOperatingcosts zDisposalcosts

Increases in zAvailability zReliability zEfficiency&productivity

Full utilisation of the service life of critical machine parts

Fig. 1

Fig. 2

Failu

re ra

te

Cause:initialcontamination

Cause:severecontamination ofthefluidduringoperation

Cause: long-termwear

Operating time

Initialstart-upphase Usagephase Fatiguephase

Maintenance timing: Tooearly ToolateOptimum

Preventive Condition-based Reactive

Maintenance management strategy:

Total costs

Costs, planned service

Costs, unplanned service

Reactive maintenancePreventive maintenanceCondition-based maintenance

Investment in Fluid Condition Monitoring

Costs, production

stoppage

100%

80%

60%

40%

20%

0%

Fig. 3

Currentmarketrequirementsforproductionmachines

Typicalservice-lifecurveofafluidsystem Typicalmaintenancecostdistribution ofthethreesystems

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Condition-based, predictive maintenance strategyInordertomeettheabove-mentioneddemands,anappropri-atemaintenancemanagementconceptmustbeestablished.“Reactive”strategies(operationuntilfailure)and“preventive”strategiesareunabletominimisethetotalcostsfordowntime,maintenanceandcomponentexchange(seeFig.3,page3).Thechoicemustbefora“predictive”concept,whichistheonlyonethatallowstheservicelifeofallcriticalmachinepartstobefullyutilised,bydetectinga“rise”inlevels(“optimum”inFig.2,page3)whichindicatesthestartofa(fluid)deviationfromthenormalcondition.Thisisthebasisofasubstantialreduction in operating costs by cutting out orminimisingexpensive and unplannedmaintenance and stoppages.As soonas the beginnings of a variation are detected, itis possible to estimate howmuch service life remains forthecorrespondingparameterorcomponentandtousethisservice life inacontrolledmanner forongoingproduction.Meanwhile,sparepartscanbeprocuredandmaintenancewithminimalcostscanbescheduled.

Toclarifythispointfurther,theadvantagesanddisadvan-tagesofdifferentmaintenancemanagementconceptscanbedifferentiatedasfollows:

z In the reactivemodel, the biggest cost factors areunplannedmaintenanceandproductionstoppage. z In the preventivemodel the biggest cost factor is thehigh proportion of plannedmaintenance.Moreover,componentsarerejectedwhichcouldcontinuetobeused. z Inthepredictivemodel,therearesomesmalladditionalcostsinitiallyfortheFluidConditionMonitoringSystem,butthetotaloperatingcostsandthereforetheLCCarethelowest.

The typical cost distributions of the threemaintenancemanagementstrategiesarecomparedinFigure3.AsuitableFluidConditionMonitoring(FCM)Systemalwaysformsthebasisofpredictivemaintenancemanagement.Inpractice,twotypesofFCMcanbeimplemented,asshowninTable1:

Edition04/2016

Predictive maintenance – the strategy that predictswhenmachinerywillrequiremaintenance

Periodic / offline Continuous / onlineImplementation Servicecrewwithportableequipment IntegrationofsensorsFeatures • Oilsampling,measurementsusingparticlecounters

• Monitoringthemeasurementsoverlongertimeperiods• Variationsresultinspecificmeasures

• Permanentsensorinstallation• Definitionoflimits/alarmthresholds• Remotedatatransmissiontomonitoringcentres orcontrolrooms viaintranet/Internet/GSM/satellite• Variationsresultinimmediate specificservicemeasures

Examples

Table 1

Fig. 4

1. Optical particle counter 1. Inductive particle counter 2., 5. Δp sensor 3. Water sensors 4. Oil ageing sensors

Typicalformsoffluidconditionsensors

FormsofFluidConditionMonitoring(FCM)

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Increase in efficiencyAfurthercostadvantageofFluidConditionMonitoringisob-tainedrightfromthedesignstagebecauseofthepossibilityofimprovingthesizingofthecomponents:

zComponents no longer need to be over-sized andthereforemoreexpensive. zThe risk of components being operated at the limit iseliminated. zThesystemhasahigherefficiencyasaresult.

Online fluid condition sensorsThegreatestbenefitofpermanentlyinstalledfluidconditionsensorsandsubsystemsisthefacilitytomonitorthefluidcondition

zonacontinuousbasis zpracticallyinreal-time.

The key systemcharacteristics to bemonitoredand theappropriate sensors (to complement the conventionalsensorsforpressure,temperature,flowrateetc.)arelistedinorderofpriorityinTable2.

Forimplementationinapredictivemaintenanceconcept,theelectricalsensoroutputsmustbeconfiguredaccordingtothefollowingguidelines:

zEssentially, the output signalsmust enable the systemortheoperatortoestimatetheremainingservicelifeofacomponentoraprocesstocarryoutplannedmaintenance. zSwitch outputs alone are usually adequate for slowprocesses. zAnalogueordigitalbusoutputsshouldideallybeusedforhighlytransientprocesses.

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Table 2

System characteristic Fluid condition sensor

Wear 1.Solidparticlesensor

Fluid cross-contamination after addition of incorrect fluid or leakage

2.Differentialpressuresensorforfilters

Water ingress through condensation or leakage 3.Sensorforfreeordissolvedwater

Fluid ageing condition on basis of hydrolysis or oxidation 4.AN(acidnumber)sensor5.Differentialpressuresensorforfilters

Typicalapplicationsforfluidconditionsensors

Fluid technology, hydraulics, electronics and service. Worldwide.

Withover8,000employees,45overseascompaniesandmorethan500salesandservicepartners,HYDACisyourreliablepartnerworldwide.Oursupplyprogrammeincludes hydraulicaccumulators,fluidfilters,processfilters,coolers,electrohydrauliccontrols,industrialvalves,sensorsystemsforpressure,encodermeasurementandsolenoidtechnology,cylinders,pumps,mountingtechnology,armatures,conditionmonitoringandmuchmore.Wedesignandsupplyready-for-usehydrauliccontrolanddrivesystems,includingelectronicopen-loopandclosed-loopcontrolsformobileandstationarymachinesandplantsforawidearrayofindustries.

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Edition04/2016

Predictive maintenance in practice

Inaviationtheguaranteedservicelifeforhydraulicpumpsisnormally10years.Thisleadstointensivequalitytestsandasaresult,higherwarrantycostsoverthewholelifecycleofthepumps.

Task Toreduceboththecostsofinspection(previouslycarriedoutmanually,withindividualoilsamplingandanalysis) andthewarrantycosts.

Solution Thenumberofwearparticlesproducedduringthefunctiontestisameasureoftheservicelifeofeverypump.Thereforeonlineparticlesensorsweretriedoutonthetestrigsandintroducedasonlinequalitytesting.

Result Inspectionandwarrantycostsreducedby>10%.

Aviation – hydraulic aircraft pumps

Intheminingindustryavailabilityandefficiencyareparamount.

Task Reduceunscheduledmaintenance,extendtheservicelifeofcriticalcomponentsandoils,increaseavailabilityandefficiency.

Solution Useofportableparticlecountersandofflinefiltration,bothperiodicallyandwhenlimitvaluesareexcee-ded.Dependingonthelocalcircumstances,samplebottles,portableparticlecountersandonlinesensorsareusedtodetectexcessivelyhighcontaminationlevels.

Result Unplannedmaintenanceworkwasreduced,availabilityandcomponentservicelifewasincreased (availability+10%,reliability+35%,unplannedrepairs-35%)

Mobile industry – mining vehicle fleets

Task Monitoringoftherequiredoilcleanlinessforwearpreventionandwateringressintothelubricatingoilofthrusterdrivesviaseals

Solution Installationofonlinefluidsensorsintheformofaready-for-connection,application-specificall-in-onesolutionResult zRequiredthrusteravailability

secured zDrydockwaitingtimes reducedby>60%

Marine/offshore industry

ThefollowingpracticalexamplesshowwaysthatFluidConditionMonitoringcanbeusedtoreducecosts:

Task Tomonitorthegearboxlubricationsystemonlineinordertopreventsecondarydamageandalsoproductionstoppages(electricitygeneration).

Solution InstallationofaMetallicContaminationSensor(MCS)forfull-flowmonitoringofthelubricationcircuit.Result zAstheimageshows,aMetallicContaminationSensor

(MCS)wasusedtodetectabearingfailure. z Thecurveshowsthenumberofaccumulatedparticles,i.e.theamountofmetaldetachedfromthedrivinggear.Eachjumpcorrespondstooneormoredetectedmetalparticles. z Thefirstwarningwasconfirmedbyavisualinspectionbecausethemainbearingshowedslightdamagebutthiswasclassedasnon-critical.Consistentwiththis,arepairwasplannedanduntilthenthewindturbinecouldcontinuetobeoperatedat80%capacity(thelowercurveinthegraphshowsthepowergenerated). z Theprogressofthedamagewasmonitoreduntilthebearingrepairwasperformed. zNounplannedmaintenanceordowntimewasrequiredandthecostsforanewgearbox(roughly€360,000)couldbeavoided.

ConclusionTheexampleslistedclearlyshowthatusingFluidConditionMonitoringincombinationwithapredictivecondition-basedmaintenancesystemandappropriatemeasurescanhelptoconsiderablyreducethemaintenanceandthecorrespondinglifecyclecostofproductionmachines.Furtheradditionalbenefitsare:

zRapidnotificationwhenfatalerrorsoccur zOpportunitiesforoptimisingcomponentandsystemservicelife

FluidConditionMonitoringisthereforeanefficientsystemdesignelementforreducingthelifecyclecostofmodernproductionmachines,predestinedforthedesignofpredictivemaintenancestrategies.

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Inrollingmillstheoperatingfluidforcontrollingtherollsisexposedtoveryhighratesofsolid-particleandwateringress. Thisisinherenttotheconditionsofhot/coldrollingprocesses.

Task Toreduceunplannedmaintenanceanddowntimecostsbyinstallingfluidsensors.Solution StandardisationofaFluidConditionMonitoringsubsystemanditsintegrationinthehydrauliccircuit.

Thesubsystemconsistsofavisualparticlesensor,awatersensorandadata-loggingdevicewithdisplay.Result Themaintenanceand

downtimecosts couldbesignificantly reduced.

Wind energy – wind turbine gearbox

Steel industry – rolling mills

Roll adjustment in steel works

Planned maintenance

Unplanned maintenance

Before (no FCM)After (with FCM)

FCM

Production stoppage

20% 20%

30% 10%

0% 2%

50% 30%

100%

80%

60%

40%

20%

0%

2000 35000

30000

25000

20000

15000

100005000

0

18001600140012001000800600400200

008.05.08 08.05.28 08.06.17 08.07.07

Date

Part

icle

cou

nt, a

ccum

ulat

ed

Pow

er p

er d

ay [k

Wh]

08.07.27 08.09.05 08.06.17 08.09.25

Total costs

100% 62%

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