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TheBasicSeven(B7)ToolsofQualityAPowerPointTrainingPresentationByKeithH.Cooper"Asmuchas95%ofqualityrelatedproblemsinthefactorycanbesolvedwithsevenfundamentalquantitativetools."-KaoruIshikawa
WhataretheBasicSevenToolsofQuality?FishboneDiagramsHistogramsParetoAnalysisFlowchartsScatterPlotsRunChartsControlChartsWheredidtheBasicSevencomefrom?KaoruIshikawaKnownfor“DemocratizingStatistics”TheBasicSevenToolsmadestatisticalanalysislesscomplicatedfortheaveragepersonGoodVisualAidsmakestatisticalandqualitycontrolmorecomprehendible.TheBasicSeven(B7)ToolsofQualityFishboneDiagramsNostatisticsinvolvedMapsoutaprocess/problemMakesimprovementeasierLookslikea“FishSkeleton”ConstructingaFishboneDiagramStep1-IdentifytheProblemStep2-Draw“spine”and“bones”Example:HighInventoryShrinkageatlocalDrugStoreShrinkageConstructingaFishboneDiagramStep3-IdentifydifferentareaswhereproblemsmayarisefromEx.:HighInventoryShrinkageatlocalDrugStoreShrinkageemployeesshopliftersConstructingaFishboneDiagramStep4-IdentifywhatthesespecificcausescouldbeEx.:HighInventoryShrinkageatlocalDrugStoreShrinkageshopliftersAnti-thefttagspoorlydesignedExpensivemerchandiseoutintheopenNosecurity/surveillanceConstructingaFishboneDiagramEx.:HighInventoryShrinkageatlocalDrugStoreShrinkageshopliftersAnti-thefttagspoorlydesignedExpensivemerchandiseoutintheopenNosecurity/surveillanceemployeesattitudenewtraineetrainingbenefitspracticesConstructingaFishboneDiagramStep5–Usethefinisheddiagramtobrainstormsolutionstothemainproblems.TheBasicSeven(B7)ToolsofQualityHistogramsBarchartUsedtographicallyrepresentgroupsofdataConstructingaHistogramFromasetofdatacomputesummean(x)MaxMinRange(max-min)ConstructingaHistogramUserangetoestimatebeginningandendCalculatethewidthofeachcolumnbydividingtherangebythenumberofcolumnsRange#ofColumns=WidthAcmePizzaExampleLet’ssaytheownerwantsadistributionofAcme’sThursdayNightSalesDataSetfromlastThursday(slices)0212241312122434143223212212214221212212121212121222121211222314223222123224224412223221224212421721223121121222122121222424AcmePizzaExampleMean=2.032258Max=7 Min=0Range=7QuestionFor7columnswhatwouldthewidthbe?Range/Columns=7/7=1sliceAcmePizzaExampleSlicesofPizza#timesorderedHistogramConstructingaHistogramHowisthishelpfultoAcme?2slicesofpizzamostcommonorderplacedDistributionofsalesusefulforforecastingnextThursday’slatenightdemand IfyouwereanAcmemanagerhowcouldyouapplythisinformation?TheBasicSeven(B7)ToolsofQualityParetoAnalysisVerysimilartoHistogramsUseofthe80/20ruleUseofpercentagestoshowimportanceAcmePizza(part2)Slices
Frequency
%0 1 .3
1 33 13.09
2 65 25.79 3 8 3.17
4 12 4.76 5 0 0 6 0 0 7 1 .3AcmePizza(part2)ThecompletedParetoAnalysisresultsinthefollowinggraph:SlicesofPizza#timesordered2143756AcmePizza(part2)CriticalThinkingHowdoestheParetoAnalysisdifferfromtheHistogram?HowcanthisbeausefultooltotheAcmeboss?The咽Basi樸cSe車ven敲(B7)殿Too卷lso趣fQu態(tài)alit診yFlow注char褲tsAgr血aphi融cal選pict膠ure筆ofa餅PRO思CESSProc環(huán)essDeci鎮(zhèn)sionThe販proc阻ess助flowFlow衫char塔tsDon螺’t壁For茅get喬to花:Defi屢nes貸ymbo洋lsb妻efor昆ebe著ginn蕉ingStay級con必sist稼entChec步kth皆atp腔roce誰ssi恒sac騙cura濁t(yī)eAcm急eP艷izz儀aE隸xam腰ple悉(Fl錢owc友har患t)Win坑dow旁T蘿ake竊Cu輸sto狠merMone換y?(sta究rt)姨Orde淹rGet辯Pi江zzaLock加upPut京More賀inOve雙n補(bǔ)2P禮iesAva陡ila趴ble繞?Tim喂etoc幣lose炭?Tak迫et丸oC性ust蘆ome漿rnoyesnoyesnoyesHow瓜ca籠nw富eu忘se仍the借fl汽owc撞har赴tt鬧oa驅(qū)nal課yze留im服pro襲vem俗ent歡id刃eas很fr旱om捉the刪Hi施sto孔gra駁m?Win招dow能T因ake俘Cu雞sto魯merMone皺y?(st僑art嘆)瓣Or仿derGet倘Pizz銷aLoc隨kupPut倒Mo紅re廚inOven季2P但iesAvai你labl悉e?Timetoc糞lose胳?Take貧to診Cust村omernoyesnoyesnoyesWan聽ts肢ome單pr角act饑ice掠?Mak株ea斧fl榨owc地har終tf仁or:Taki呈nga嶄sho邪werCoo戶kin淘gd秤inn扛erDri蜓vin勤ga蹄ca鋪rHav勁ing薪a住par鞋tyCre惡ati搭ng閘aF迎low筍cha運(yùn)rtAny海othe惜rpr容oces茂ses偶you境can腰thin掙kof怨?The擁Ba偏sic消Se護(hù)ven眠(B倡7)嚼To齊ols薯of及Qu場ali撒tySca躬tte樸rP棗lot畏s2Di按mens釣iona球lX/生Ypl筒otsUse亦dt拾os撞how怪re把lat璃ion芒shi灣pb語etw費(fèi)een如in捧dep唇end謝ent炮(x)挖an調(diào)dd默epe磨nde肉nt(毯y)弦var什iab雷lesAcme咽Piz皂za積(Sc雅atte百rDi寄agra虧m)Min鈔ute徹sC鎖ook草ing柏De色fec周tiv強(qiáng)eP郊ies10脆145青830吸575落2060觸1420鉤425融6In搏thi尿ss萬imp歷le寫exa翼mpl錦e,曠you父ca濱nf誤ind死th傍ee磚xis棟tin踐gr枯ela仇tio肯nsh咸ip段wit畢hou論tm絨uch塘di缺ffi屑cul揉ty叛but雀…Sca見tte漢rD明iag鎮(zhèn)ram倉sEas挪ier辦to盛se托ed樣ire偽ct性rel組ati懷ons起hipTim頓eC刃ook經(jīng)ing嶺(m宿inu嚷tes好)Def煎e(cuò)ct謠ive棒Pi悟zza桌sSca片tte以rD旁iag押ram匙sAs恥aq解ual伴ity仁to頌olWha囑td跌oes孟th漂is勞tel掙lA勾cme嚷ma湊nag降eme抽nt橫abo瘋ut倒the潛ir燒pro崖ces矮ses足?Imp敞rov迎eme睬nts皺?Time誘Coo帥king儉(mi即nute芽s)Defe歸ctiv尤ePi曉zzasThe師Ba罪sic壯Se慕ven坦(B覆7)捎To很ols童of叔Qu侵ali升tyRun勞char另tsTime辰-bas朗ed(雄x-ax腦is)Cycl您icalLook瘋for痕pat邁tern斷sRun胡Char尋ts89畢10奴11彼12采1復(fù)23撒489堡101暮112旺12開3489永101塔112薯12移34PM-蔑AMPM-鋼AMPM-泊AMThur文sdayWee拘k1Thu王rsd濱ayWee動(dòng)k2Thu界rsd商ayWeek枕3510雷15括202懷530蠶35暖404篇550庸55粉606境570撿75島808悶590棵95樸100Sli池ces遠(yuǎn)/ho崇urTimeThe稠Ba喬sic揮Se慘ven膛(B輔7)懇To凍ols傲of所Qu袖ali吧tyCon礦tro斤lC辦har語tsDev敲iat錢ion樣fr俊om免Mea焦nUppe曬ran墻dLo斜wer霸Spec趕’sRan內(nèi)geCont府rol帶Char姜tsUppe拖rLi愛mitLowe丑rLi漠mitUna累cce婚pta典ble紡de堪via府tio配nXCont怠rol寇Char席tsAcm抽eP隆izz羽aM砌ana愈gem眾ent秒wa旅nts懇to膝ge露ti膝no仿nt捕he騰con賽tro炭lc們har療ta顏cti醒onAver眠age變Diam哭eter悅=1慕6in肥chesUppe角rLi津mit易=17獎(jiǎng)inc乏hesLow濁er椒Lim題it慚=1脈5i數(shù)nch越esAcme準(zhǔn)exa花mpleCont癥rol律Char騾tsUppe完rLi錯(cuò)mit17i
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