利用minitab做蒙特卡洛模擬_第1頁(yè)
已閱讀1頁(yè)，還剩4頁(yè)未讀， 繼續(xù)免費(fèi)閱讀

下載本文檔

版權(quán)說(shuō)明：本文檔由用戶提供并上傳，收益歸屬內(nèi)容提供方，若內(nèi)容存在侵權(quán)，請(qǐng)進(jìn)行舉報(bào)或認(rèn)領(lǐng)

文檔簡(jiǎn)介

1、1DoingMonteCarloSimulationinMinitabStatisticalSoftwareDoingMonteCarlosimulationsinMinitabStatisticalSoftwareisveryeasy.ThisarticleillustrateshowtouseMinitabfMonteCarlosimulationsusingbothaknownengineeringfmulaaDOEequatio

2、n.byPaulSheehyEstonMartzMonteCarlosimulationusesrepeatedromsamplingtosimulatedatafagivenmathematicalmodelevaluatetheoutcome.Thismethodwasinitiallyappliedbackinthe1940swhenscientistswkingontheatomicbombusedittocalculateth

3、eprobabilitiesofonefissioninguraniumatomcausingafissionreactioninanother.Withuraniuminshtsupplytherewaslittleroomfexperimentaltrialerr.Thescientistsdiscoveredthataslongastheycreatedenoughsimulateddatatheycouldcomputereli

4、ableprobabilities—reducetheamountofuraniumneededftesting.Todaysimulateddataisroutinelyusedinsituationswhereresourcesarelimitedgatheringrealdatawouldbetooexpensiveimpractical.ByusingMinitab’sabilitytoeasilycreateromdatayo

5、ucanuseMonteCarlosimulationto:?Simulatetherangeofpossibleoutcomestoaidindecisionmaking?Fecastfinancialresultsestimateprojecttimelines?Understthevariabilityinaprocesssystem?Findproblemswithinaprocesssystem?Manageriskbyund

6、erstingcostbenefitrelationshipsStepsintheMonteCarloApproachDependingonthenumberoffactsinvolvedsimulationscanbeverycomplex.ButatabasiclevelallMonteCarlosimulationshavefoursimplesteps:1.IdentifytheTransferEquationTodoaMont

7、eCarlosimulationyouneedaquantitativemodelofthebusinessactivityplanprocessyouwishtoexple.Themathematicalexpressionofyourprocessiscalledthe“transferequation.”Thismaybeaknownengineeringbusinessfmulaitmaybebasedonamodelcreat

8、edfromadesignedexperiment(DOE)regressionanalysis.2.DefinetheInputParametersFeachfactinyourtransferequationdeterminehowitsdataaredistributed.Someinputsmayfollowthenmaldistributionwhileothersfollowatriangularunifmdistribut

9、ion.Youthenneedtodeterminedistributionparametersfeachinput.Finstanceyouwouldneedtospecifythemeanstarddeviationfinputsthatfollowanmaldistribution.3.CreateRomDataTodovalidsimulationyoumustcreateaverylargeromdatasetfeachinp

10、ut—somethingontheder100000instances.Theseromdatapointssimulatethevaluesthatwouldbeseenoveralongperiodfeachinput.Minitabcaneasilycreateromdatathatfollowalmostanydistributionyouarelikelytoencounter.4.SimulateAnalyzeProcess

11、OutputWiththesimulateddatainplaceyoucanuseyourtransferequationtocalculatesimulatedoutcomes.Runningalargeenoughquantityofsimulatedinputdatathroughyourmodelwillgiveyouareliableindicationofwhattheprocesswilloutputovertimegi

12、ventheanticipatedvariationintheinputs.ThosearethestepsanyMonteCarlosimulationneedstofollow.Here’showtoapplytheminMinitab.MonteCarloUsingaKnownEngineeringFmulaAmanufacturingcompanyneedstoevaluatethedesignofaproposedproduc

13、t:asmallpistonpumpthatmustpump12mloffluidperminute.Youwanttoestimatetheprobableperfmanceoverthoussofpumpsgivennaturalvariationinpistondiameter(D)strokelength(L)strokesperminute(RPM).Ideallythepumpflowacrossthoussofpumpsw

14、illhaveastarddeviationnogreaterthan0.2ml.3Minitabwillquicklycalculatetheoutputfeachrowofsimulateddata.Nowyou’rereadytolookattheresults.StatBasicStatisticsGraphicalSummarytheFlowcolumn.Minitabwillgenerateagraphicalsummary

15、thatincludesfourgraphs:ahistogramofdatawithanoverlaidnmalcurveboxplotconfidenceintervalsfthemeanthemedian.ThegraphicalsummaryalsodisplaysersonDarlingNmalityTestresultsdeivestatisticsconfidenceintervalsfthemeanmedianstard

16、deviation.ThegraphicalsummaryofyourMonteCarlosimulationoutputwilllooklikethis:Ftheromdatageneratedtowritethisarticlethemeanflowrateis12.004basedon100000samples.Onaverageweareontargetbutthesmallestvaluewas8.882thelargestw

17、as15.594.That’squitearange.Thetransmittedvariation(ofallcomponents)resultsinastarddeviationof0.757mlfarexceedingthe0.2mltarget.Alsoweseethatthe0.2mltargetfallsoutsideoftheconfidenceintervalfthestarddeviation.Itlooksliket

18、hispumpdesignexhibitstoomuchvariationneedstobefurtherrefinedbefeitgoesintoproductionMonteCarlosimulationwithMinitabletusfindthatoutwithoutincurringtheexpenseofmanufacturingtestingthoussofprototypes.Lestyouwonderwhetherth

19、esesimulatedresultsholduptryityourself!Creatingdifferentsetsofsimulatedromdatawillresultinminvariationsbuttheendresult—anunacceptableamountofvariationintheflowrate—willbeconsistenteverytime.That’sthepoweroftheMonteCarlom

溫馨提示

  • 1. 本站所有資源如無(wú)特殊說(shuō)明，都需要本地電腦安裝OFFICE2007和PDF閱讀器。圖紙軟件為CAD,CAXA,PROE,UG,SolidWorks等.壓縮文件請(qǐng)下載最新的WinRAR軟件解壓。
  • 2. 本站的文檔不包含任何第三方提供的附件圖紙等，如果需要附件，請(qǐng)聯(lián)系上傳者。文件的所有權(quán)益歸上傳用戶所有。
  • 3. 本站RAR壓縮包中若帶圖紙，網(wǎng)頁(yè)內(nèi)容里面會(huì)有圖紙預(yù)覽，若沒(méi)有圖紙預(yù)覽就沒(méi)有圖紙。
  • 4. 未經(jīng)權(quán)益所有人同意不得將文件中的內(nèi)容挪作商業(yè)或盈利用途。
  • 5. 眾賞文庫(kù)僅提供信息存儲(chǔ)空間，僅對(duì)用戶上傳內(nèi)容的表現(xiàn)方式做保護(hù)處理，對(duì)用戶上傳分享的文檔內(nèi)容本身不做任何修改或編輯，并不能對(duì)任何下載內(nèi)容負(fù)責(zé)。
  • 6. 下載文件中如有侵權(quán)或不適當(dāng)內(nèi)容，請(qǐng)與我們聯(lián)系，我們立即糾正。
  • 7. 本站不保證下載資源的準(zhǔn)確性、安全性和完整性, 同時(shí)也不承擔(dān)用戶因使用這些下載資源對(duì)自己和他人造成任何形式的傷害或損失。

評(píng)論

0/150

提交評(píng)論