discrete event simulation analysis of a gearbox manufacturing plant using the software ‘witness’

ENGINEERINGSIMULATIONCOURSEWORK2;PDE4905 May1,2015

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Middlesex University, London

School of Science and Technology

PDE4905

EngineeringSimulation

Coursework

FortheAcademicYear2014-2015

RifatAbdulRahiman

M00514416


:

Content

Abstract……………………………………………………………………………………………….…..03

Introduction……………………………………………………………………………………,……….03

Methods…………………………………………………………………………………………….…….04

Results………………………………………………………………………………………………….….07

Discussion…………………………………………………………………………………………….….14

Conclusion……………………………………………………………………………………………….14

Bibliography…………………………………………………………………………………………….15

Appendix…………………………………………………………………………………………………16


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ADISCRETEEVENTSIMULATIONANALYSISOFAGEARBOXMANUFACTURINGPLANTUSINGTHESOFTWARE‘WITNESS’

Abstract

Simulationtechnologyandoptimizationhasbeencombinedinrecentyearswhichareusedrapidlybyvariousindustries.OnesuchcombinationisthesoftwareWitness.UsingthesoftwareWitness,amodelforthegearboxmanufacturingplantwascreatedandthensimulatedbyconductingittoperformvarioustasks.UsingtheWitness,astochasticdiscreteeventseveralcompanieshaveimprovedtheirfunctionality.Fromthegivenmodel,whenitwassimulatedtheeffectithasonthebreakdownofitsmachines–CNCandconveyorbelt,intheplantanditsperformancefinanciallywascalculated.Herethebreakdowndoneforboththemachinesisdonefor90minutes.Resultsobtainedfromaseriesoftestsdoneonthesystemandmoredetailsaboutthebreakdownareexplainedextensivelyinthereport.

Introduction

Simulationisacosteffectivemethodologywhichiswidelyusedinmanagementscienceandoperationsresearch.Theimplementationofgivenmanufacturingprocessintosimulationmodelisatypicaltechniqueusedtoanalysetheprocessanditscharacteristics.

Simulationisatoolusedtypicallytoanalyseandunderstandthecharacteristicsofanysetofindustrialormanufacturingprocessesinwhichit’sstochasticanddynamicsystemscanbetestedupon.Furthermore,otherparameterslikecostandleadtimecanbeaccuratelyunderstoodwithrapidconfigurationadjustmentscanbemade(Lanner,2008).Ontheotherhandsimulationmodelsareafunctionthatassessesthevalueofanysetofspecifications.Theyareoptimizedtoobserveandconverttheinputparametersintoitspotentialoutputresults.Optimizationcanalsobeusedtocontrolthenumberofoperatorsandmachinesinadditiontothemanagementandmaintenanceofcostsandresourcesrespectively.Alsocycletimescanbeminimizedbasedontheformulationofconstraints(April,Glover,KellyandLaguna,2003).

Whenconsideringdiscreteproblems,themethodologyofstochasticapproximationisusuallyappliedbecauseofitsrelationshipwithgradientsearch.Itisdifferentfromthecontinuouseventsimulationsuchthatinstantaneouschangescantakeplaceinthesystemduringdiscreteeventsimulation,whileitisimpossibletochangeanyparametersduringcontinuouseventsimulation.Moreoverthisapproximationmentionedfocusesmainlyoncontinuousvariableproblems(April,Glover,KellyandLaguna,2003).

OneofthesimulationsoftwareusedtoprocessadiscreteeventsimulationisWITNESS,developedbytheLannerGroupInc.whichismainlyusedtosimulateaproductionormanufacturingprocesstoanalyseandgetproperinformationonit.AgearboxmanufacturingplanthasbeenmodelledusingtheWITNESSsoftwareaccordingtothegivenconditionsandanalysedtocalculatetheprobablerevenueobtainedasperthebudgetgiven.Partslikegearsarrivefromexternalsuppliersafterwhichitpassesthroughtheconveyorbeltafterwhichitisassembledandtheninspectedfollowedbytheshipmentoffinalproducts.CNCmachinesarealsousedintheproductionwhiledefectproductsareledtothedisassemblingarea.


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Thecompletemodelisdesignedandanalysedtofindthedesiredresultswhicharedescribedinthereportalongwithotherbreakdowncharacteristicsofthesystem.Themodeldesignedconsistsofaplantwherethegearssuppliedarrivesexternalsourceandfedintoaconveyorbeltofsize20minlength,whosemaximumcapacityisalways180partswithamaximumspeedof5m/min.Gearspurchasedareofsize80mmx80mmx100mmindimension.Similartogears,bearingsandcastingsarealsoprocuredwhicharefedintotheassemblyandCNCunitsrespectively.Likewisetheconveyorbeltalsoprovidestheassemblyunitwithgearsfromwhichgearboxismanufactured.

Loadingandunloadingofpartstothemachinesaredonecontinuouslybyanoperatorforwhichthereisauniformlydistributedcycletime.Itis0.5–1.0minutesand0.5–0.9minutesrespectively.Themaximumcapacityofabinis50whiletheCNCmachining’scycletimeis2.3minutes.Inspectionisdoneforevery20thgearboxpassedanditscycletimeistriangularlydistributedwithaminimum,maximumandamodeof0.8,2.2and1.1minutesrespectively.Assemblingisdonewithtwogearsandtwobearingsbyanoperatorwhichtakesameanof3minuteswithastandarddeviationof0.7minutes,butnolessthan2.2minutesandnogreaterthan5.Thisisfollowedbytheassemblytobeputattestingthroughbufferandthenthetestbench.Itprocessesfor10minutes.Anoperatorwhodoestheloadingtakesfrom0.2to0.4minutesforloadingandunloadingforeachgearbox.Itisalsotobenotedthatasperthegivendescriptiondisassemblytakesameanof2.3minuteswithstandarddeviation0.4,andbetween1.7and3.5minutes.

Methods

ThebasisuponwhichtheplantwasmodelledisbyusingPetriNetwithastochasticsetup.PetriNetfoundedbyCarlAdamPetriin1962istoolusedtocreatesynchronizedandconcurrentmodelindistributedsystems.Theyarecomprisedof3typesofcomponentswhichincludeplaces,transitionsandarcs.Theseareindicatedascircles,rectanglesandarrowswhichrepresentsstateofthesystem,actionsthatresultinchangeofstateandtheconnectionbetweenplaceandtransitionorviceversarespectively.Itistobenotedthateveryplaceandarchasacapacityandaweightrespectively.Thisallowsseparatetokenstostayinaplacetomodelmorecomplexsystems(Ling,2001).

TherequiredmodelwascreatedusingtheWITNESSsimulationsoftware.Itconsistsofvariouscomponentslikemachines,buffersandparts.Amongthesebuffersusedinthesystemrepresentbinsandtestactionswhilevariablesarealsousedtospecifytheiractions.Initiallythegearsarrivedexternallyissuppliedtotheassemblythroughtheconveyorsetafixedspeed.Simultaneouslyalongwiththegears,bearingsandcastingaresuppliedtotheassemblyandCNCrespectively.


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ATypicalexampleofaPetriNetModelCourtesy:Techfak

Theassemblyhasasequentialinputruleascasting,gearandbearingarepulledinasperthegivensequence.Thefunctionusedtodefinethestructureis

SEQUENCE/WaitCastingoutofBin#(1),

GearoutofConveyor_BeltatFront#(2),

BearingsoutofWORLD#(2)

FurthermorethefinaloutputfromtheassemblyistobedefinedasGearboxwherethefunctionis

CHANGEALLtoGearbox

Moreoveroncetheproducthasreachedtheinspectionstation,asperthedescription78%ofthepartswillbeintheuppertolerancelimit.Thisfunctionforthesystemhasbeenstructuredasgivenbelow.


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IFBinomial(0.78,20)<=N_passed

Clean_CNC=1

N_passed=0

ELSE

N_passed=N_passed+1

ENDIF

Castingswhichareboreddownarethenlettotheinspectionstationfromwhichitproceedtotheassemblyviabinifqualified;elseitisscrapped.ThefinalproductnamelyGearboxisthenledtothetestbenchwhereitistested.Ifthere’sanyerror,itisthendisassembledfromthedisassemblingunitfromwhichgearsproceedtotheconveyorbelttorepeatthecyclewhiletherestisscrapped.Theoperatorhasbeenallocatedshiftsasrequiredtoworkfor8hoursperweek.

TheModelcreatedusingWitnesssimulationsoftwareasperthedescription

RevenueandBudget

TherevenueisdeterminedusingWitnessaswellwhereasthecostisdefinedinthesystem.Meanwhilethemachinerateiscalculatedbyobtainingthetimeneededtorunthemachinetogettheinvestmentonmachineback.Theanalysisisdoneonthebasisofdirectandindirectcosts.Ontheotherhand,thetotalbudgetrequiredhasbeenmentionedasperthedescriptionoftheplant.TheCNCworkstationwaspurchasedforacost£72000whichisneededtoberepaidinthreeyears.Neverthelessabudgetof£15000wasallocatedtosetuptheremainderoftheplantwherethecostsforassemblystations,binsandtestbenches(pergearbox)is£1800,£200and£2200respectively.Inadditionthecostforhiringanoperatoris$1500wherethehourlyrateis£15.60whichincludeson-costs.Thisexpenditureistoberepaidwithinoneyear.Theexpectedincomefromthesaleofeachcompletedgearboxis£80.AccordingtoYang,therevenueforhiskindofsystemisobtainedbyusingtheequation

Return=NShip(Gearbox)*80–[(NQty(Assembly)*0.9+NQty(CNC)*24+NQty(Test_Buffer)*0.1+NQty(Test_Bench)*1.1+NQty(Operator)*16.35)*80]


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Breakdown

Oneofthecommonoccurrencesinthemanufacturingsectoristhebreakdownofequipmentsandunits.MultiplebreakdownsofunitscanbesetinWitnesswhichhastobedonethroughproperdistribution.Accordingtothedescriptiona90minutesbreakdownhastobeconsideredinthesystem,whichindicatesthetimerequiredtorepairthespecifiedunit.ABreakdowncounterhasbeenusedanddefinedtoindicatethenumberofbreakdownsthatoccur.ThetimetakenbetweeneachbreakdownfortheconveyorbeltandtheCNCmachineis8000and4000respectively.Itsfunctionisdefinedas

Breakdown_counter=Breakdown_counter+1

Results

Therequiredmodelwascreatedandsimulationwasdonetoanoptimumlevelmanuallytoobserveandanalysetheperformance.TheRevenuefortheplantwasdeducedbymanuallysettinguptheplantatdifferentconditionswithinthegivenbudgeto£15000.Thiswasdonebyusingseveralvariables,functionsandvariablesalongwiththemanufacturingunitliketheinspectionandassemblybase.Operatorswereassigneduniformshiftswithamaximumof8hoursperday.Thesystemwasrunfor14400minutestoobtaintheresults,andoutof6differentcalculationsasgivenbelow,thecombinationthatgavethemaximumrevenuefortwoweekswas£43964forabudgetof£13700.Oneofthetasksrequiredwastoidentifythecharacteristicsofthesystemafterandbeforeeachofthemachinesorunithasbrokendown.

Number of Shipments

Operator Shift

Quantity

Assembly Quantity

Bin Quantity

Conveyor Belt

Quantity

Test Bench

Quantity

Test Buffer

Quantity

CNC Quantity Budget Revenue

585 1 2 1 1 2 1 2 9700 41324 620 1 3 1 1 2 1 3 11500 42132

585 2 2 1 1 2 1 3 11200 38096 620 1 3 1 1 3 1 2 13700 43964 605 1 3 1 1 3 1 3 13700 40844 555 1 1 1 1 1 1 1 5700 41004

Table1.RevenueandBudgetStatistics

Oneofthetasksrequiredwastoidentifythecharacteristicsofthesystemafterandbeforeeachofthemachinesorunithasbrokendown.Understandingthebreakdowncharacteristicsanditsaftereffectswillassistinmanagingthesystemandreducetheriskassociatedwithit.Thisishighlyhelpfulinmaintainingtheincomeaswell.Itistobenotedthatwhenanyonepartofthesystembreaksdown,itaffectsthewholesetupcompletely.Theconditionsforthebreakdownasmentionedearlieraresetinsystemandtheperformanceforeachunitwasinvestigatedbeforeandafterthebreakdown.Thedataandstatisticsforeachoftheunitsaregivenbelow.


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Table2a.ConveyorBeltStatisticsbeforeBreakdown

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Table2b.ConveyorBeltStatisticsafterBreakdown


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Table3a.CNCStatisticsbeforeBreakdown

Table3b.CNCStatisticsafterBreakdown


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Table4a.InspectionStatisticsbeforeBreakdown

Table4b.InspectionStatisticsafterBreakdown


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Table5a.AssemblyStatisticsbeforeBreakdown

Table5b.AssemblyStatisticsafterBreakdown


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Table6a.DisassemblyStatisticsbeforeBreakdown

Table6b.DisassemblyStatisticsafterBreakdown


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Table7a.TestBenchStatisticsbeforeBreakdown

Table7b.TestBenchStatisticsafterBreakdown

Furtherstatisticsareencompassedintheappendixastheyareinsignificanttothesimulationanalysis.


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Discussion

ThesimulatedresultsobtainedforthesystemmodelledusingWitnesswasanalysedwhichgiveanideaaboutitscharacteristics.Itwasfoundthatthroughmanualcalculationssettingthebudgetwithintherequired15000poundslimit,amaximumrevenueof43964 pounds was achieved when using 3 assemblies and test benches along with 2 CNC machines. In addition a conveyor belt was used. A budget of 13700 pounds was used in this case. Using Witness and through optimization excellent forecasts can be achieved for the revenue and budget which gives a good indication on what business model to use and proceed to improve and maximize the income. Nevertheless it is only a forecast and is liable to change when compared with the performance in the real world as the values can end up being higher or lower than the initial forecast.

Thebreakdownstatisticswasalsoobservedduringtheanalysistounderstanditsimpactonthesystem.TheplantisaffectedhugelywhenanyoneoftheunitsbreakdownespeciallytheconveyorbeltandtheCNCmachinebecausetheyaretheunitsfromwhichthesystemstartstowork.Theplanttendstobecomeidlewhentheybreakdownasshowninthedatagivenearlier.Thisinadditionhasanadverseimpactontherevenueoftheplantaswell.Alsothereducednumberofshippedgearboxescanalsobeseenfromthedataafterthedifferentsectionshaveundergoneabreakdown,whencomparedwiththeirdatapriortobreakdown.

Eventhoughthebreakdownstatisticsforeachmachineisvaluableandhastobeconsidered,liketheoptimizationofthesoftware,itdoesn’tincurtherealtimeaspectsandtendstobedifferentintherealworldcomparedtothesystem.

Conclusion

ThemodelwasdesignedusingthesimulationsoftwareWitnessandthemaximumrevenueobtainedforaperiodoftwoweekswas43964poundsforabudgetof13700pounds.Thisindicatesthattheplantcanincurarevenueof402300poundsperyearbasedontheforecast,whichactuallyisarespectableamountofincomewhenconsideringtherequirementsfortheplant.Moreoverfromthedetailedanalysisofbreakdown,specificallythebreakdowncounteritcanbeseenthatthereisalwaysonebreakdownintheplanteveryweek.Thisshowsthattheaveragenumberofbreakdowntheplantisexpectedtosufferinayearis52.

Whenthemachinesorunitsbreakdown,especiallytheCNCandconveyorbelt,thecompleteplantisaffectedandissubjectedtoidlenessandblockageindifferentmachines.Nonethelesstheseresultsarenotpreciseastheydon’tconsiderthehuman,externalorsupplyanddemandfactorswhichalsoplayahugeroleontheworkingoftheindustriesandfocusingsolelyonthesimulatedforecastcanalsoleadtopoorperformance.


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Bibliography

ChrisLing,2001.ThePetriNetMethod.[Online].Availableon:www.utdallas.edu/~gupta/courses/semath/petri.ppt.[Accessedon29/03/2015].

JayAprilFredGloverJamesP.KellyManuelLaguna,2003.PRACTICALINTRODUCTIONTOSIMULATIONOPTIMIZATION.[online].Availableon:http://www.courses.vcu.edu/MATH-jrm/OPER641/Papers/AprilPracticalSimulationOptimization.pdf.[Accessedon29/03/2015].

Lanner,2008.SimulationandSimulationSoftwareExplained.[Online].Availableon:http://www.lanner.com/en/simulation-explained.cfm.[Accessedon29/03/2015].

MingChen,n.a.PetriNet.[Online].Availableon:http://www.techfak.uni-bielefeld.de/~mchen/BioPNML/Intro/pnfaq.html.[Accessedon29/03/2015].

YangX.S,2014.Discrete-EventSimulation:IntroductiontoWitness.MiddlesexUniversity.London


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Appendix

Table8a.GearStatisticsbeforeBreakdown

Table8b.GearStatisticsafterBreakdown


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Table9a.BearingStatisticsbeforeBreakdown

Table9b.BearingStatisticsafterBreakdown

Table10a.CastingStatisticsbeforeBreakdown


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Table10b.CastingStatisticsafterBreakdown

Table11a.BinStatisticsbeforeBreakdown


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Table11b.BinStatisticsafterBreakdown

Table12a.TestBufferStatisticsbeforeBreakdown


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Table12b.TestBufferStatisticsafterBreakdown

Table13a.GearboxStatisticsbeforeBreakdown

Table13b.GearboxStatisticsafterBreakdown


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Table14a.OperatorShiftStatisticsbeforeBreakdown

Table14b.OperatorShiftStatisticsafterBreakdown