Little-Field--simulation-Strategy-and-report

B6016ManagingBusinessOperationsReportonLittlefieldTechnologiesSimulationExerciseByGroup4:AniseTanQingYeAneelGautamChuKarHwa,LeonardTanKokWeiRankingReflectingonthesimulationexercise,wehavemadebothcorrectandincorrectdecisions.Nevertheless,althoughweranked4th(Exhibit1:OVERALLTEAMSTANDING),webelievewegainedadeeperunderstandingofqueuingtheoryandhaveobtainedinvaluableexperiencefromthisexercise.RankTeamCashBalance($)1bigmoney11,346,3202techwizard1,312,3683makebigmoney1,141,6864beaters123895,4055donothing588,0546mas001472,296Exhibit1:OVERALLTEAMSTANDINGDecisionsMadeAsummaryoftherationalebehindthekeydecisionsmadewouldperhapsbestexplaintheresultsweachieved..Decision1DayParameterValue54station1machinecount2Whentheexercisestarted,wedecidedthatwhentheleadtimehit1day,wewouldbuyonestation1machinebasedonouranalysisthatstation1takesthelongesttimewhichis0.221hrssimulationtimeperbatch.(Exhibit2:Averagetimeperbatchofeachstation).Asday7andday8have0jobarrivals,weusedday1-6figurestocalculatetheaveragetimeforeachstationtoprocess1batchofjobarrivals.Baseontheaveragetimetakentoprocess1batchofjobarrivals,wewereabletofigureouthowmanybatcheseachmachinecanhandle.daynumberofjobsarrivingeachdayutilizationofstation1,averagedovereachdayutilizationofstation2,averagedovereachdayutilizationofstation3,averagedovereachday120.4330.0790.019220.2720.1580.108310.3980.1060.1654000.0520520.330.0790.06610.3320.1580.013Averageprocesstimeperbatch0.2210.0790.046Maximumbatchprocessedaday4.5212.6621.74Exhibit2:AveragetimeperbatchofeachstationWedidnotpaymuchattentiontothestation3machineatthisstageeventhoughthereappearstobesignificantvariationinprocessingtime,astheusageappearstobeverylow.Decision2DayParameterValue56station2machinecount2Thisturnedouttobeanincorrectdecisionaswehaveyettofigureout“howthesystemworks”.Weboughtanadditionalmachineatstation2,eventhoughthequeueaccumulationwasnotthatsignificant,aswewantedtoeliminatethequeueto0.(SeeExhibit4).Lateron,wefiguredthatweshouldlookattheutilizationofthemachineasopposedtothequeuenotbeing0.Exhibit4Wedidafurtherprojectionbyusingregressionanalysisconsolidatingthejobarrivalsfromday1-60tofigureoutwhetherweshouldhaveboughtmachine2atstation2,andrealizedourmistake.(Exhibit5:RegressionAnalysisofday1-60)Exhibit5:RegressionAnalysisofday1-60Basedontheformulay=0.0559x+1.1753(y=12.66-themaximummachine2canhandle,wecanfigureoutx=day205.Thismeansweshouldhaveboughtmachine2onlyafterjobarrivalsexceed12batches,andthatwillbeatday205basedontheregressionanalysis.Weboughtittooearlyandthuslosttheopportunitytoearnmoreinterestoncash.Decision3:DayParameterValue132station1machinecount3134station1machinecount4135station2schedulingrulepri4142station2schedulingrulepri2OnDay132,wenoticedthatjobsarrivalshadincreasedsignificantlyandourleadtimehadalreadyhit5days.Machineutilizationhadalsoreached100%andourrankinghaddropped.PleaseseeExhibit6.Weimmediatelyboughtonemoremachineatstation1.Lateron,wefiguredoutweneedanothermachineatstation1asourleadtimewasalready5days,andthequeuewillnotbereducedwithouttheadditionalmachine.Soonthefollowingday,weboughtanothermachineatStation1.AsregardsStation3,basedonourformercalculation,thereseemstobenoneedtobuyanothermachine,becauseamachinecanprocess21.74batchesaday.Ifthatisthecase,whyisthereaqueueatstation3?Wethenrecalculatedhowmanybatchesy=0.0559x+1.1753R²=0.2004-202468100204060numberofjobsarrivingeachdaynumberofjobsarrivingeachday线性(numberofjobsarrivingeachday)onemachineatStation3canhandleusingthefiguresfromday1today134,andtheaveragetimetoprocess1batchforonemachineatStation3is0.09hrssimulationtimeandthemostitcanhandleis11.11batchesaday.Onday135,wedecidedtobuyanothermachineatStation3.Also,wesettheprioritytostage4asnowourpriorityistomeettheleadtime.Exhibit6:Decision4:DayParameterValue152station2machinecount1152station3machinecount1152station1machinecount3Thisisawrongdecision.Thesimulationbriefingmaterialsindicatedthatfromday150-180,thejobarrivalswillbefixed.Wedidcloselymonitorthisandthusdidnottakeactiononday150.Theaveragearrivalsforday150–152arearound10batches,andconcludedthatday150-180willbearound10batches.Inthatcase,twomachinesatStation1,onemachineatStation2,andonemachineatStation3shouldbeabletohandle10batchesaday.Wemadeadecisiontosellthe“extramachines”inhopeofearningextrainterest.Also,wesetprioritytostage2asweneededtofullyutilizestage3whenthejobarrivalsfluctuate.Decision5:DayParameterValue157station2schedulingrulepri4157station2schedulingrulefifo158station2schedulingrulepri4166station3machinecount2168station2schedulingrulefifo169station2schedulingrulepri2169station2schedulingrulepri4169station2machinecount2170station1machinecount4Onday157,werealisedthattheleadtimehit1.26daysandalsonoticedthatthejobarrivalsdidnotstaythesame.Instead,theyseemedtocontinuallyincrease.Aswehopedthatjobarrivalswillstarttodrop“lateron”,wescheduledprioritytostage4toshortentheleadtime.Itseemedtoworkastheleadtimedroppedto0.6onday163.However,onDay166,theleadtimeshotupto2.5days(Exhibit7).Wequicklyboughtbackallthemachineswhichwesoldaswestillhavesometime