质量管理课件1

质量管理

QualityManagement

一、14个要点:

Point1CreateConsistencyofPurposePlanDoStudyAct

TheShewhart-DemingCycle FocusonConstantImprovementPoints2and3Point2.AdoptNewPhilosophy

Bettertobeproactiveandchangebeforecrisisoccurs.Point3.CeaseDependenceonMass InspectiontoAchieveQuality

AnyInspectionwhosepurposeisto improvequality istoolate.Points4and5Point4.EndthePracticeofAwardingBusinessonthe BasisofPriceTagAlone

Developlongtermrelationshipbetweenpurchaser andsupplier.Point5.ImproveConstantlyandForever.

Reinforcetheimportanceofthe continuousfocusoftheShewhart cycle.Points6and7Point6.InstituteTraining.

EspeciallyimportantforManagerstounderstandthedifferencebetweenspecialcausesandcommoncauses.Point7.AdoptandInstituteLeadership

Differentiatebetweenleadershipand supervision.Leadershipistoimprovethesystemandachievegreaterconsistencyofperformance.Points8to12Points8-12.

DriveoutFearBreakDownBarriersBetweenStaffAreas EliminateSlogans EliminateNumericalQuotasforWorkforce EliminateNumericalGoalsforManagement RemoveBarrierstoPrideof Workmanship300QualityisimportantPoints13and14Point13.EncourageEducationandSelf-Improvement forEveryone

Improveknowledgeofpeople willimproveassetsof organization.Point14.TakeActiontoAccomplishTransformation

Continuallystrivetowardimprovement.ControlCharts

控制图MonitorsVariationinDataExhibitsTrend-MakeCorrectionBeforeProcessisOutofcontrolShowWhenChangesinDataAreDuetoSpecialorAssignableCausesFluctuationsNotInherenttoaProcessRepresentsProblemstobeCorrectedDataOutsideControlLimitsorTrendChanceorCommonCausesInherentRandomVariations

GraphofsampledataplottedovertimeAssignableCauseVariationRandomVariationProcessAverage

MeanProcessControlChart过程控制图UCLLCLControlLimits

控制限UCL=

ProcessAverage+3StandardDeviationsLCL=ProcessAverage-3StandardDeviationsProcessAverageUCLLCLX+3

-3

TIMETypesofError

误差类型FirstType:BeliefthatObservedValueRepresentsSpecialCauseWheninFactitisDuetoCommonCauseSecondType:TreatingSpecialCauseVariationasifitisCommonCauseVariationComparingControlChartPatterns

控制图模式比较XXXCommonCauseVariation:NoPointsOutsideControlLimitSpecialCauseVariation:2PointsOutsideControlLimitDownwardPattern:NoPointsOutsideControlLimitWhentoTakeCorrectiveAction

何时采用校正措施1.EightConsecutivePointsAbovetheCenterLine(orEightBelow)2.EightConsecutivePointsthatareIncreasing(Decreasing)CorrectiveActionshouldbeTakenWhenObservingPointsOutsidetheControlLimitsorWhenaTrendHasBeenDetected:pChart（概率图）ControlChartforProportionsShowsProportionofNonconformingItemse.g.,Count#defectivechairs÷by

totalchairsinspectedChairiseitherdefectiveornotdefectiveUsedWithEqualorUnequalSampleSizesOverTimeUnequalsizesshouldnotdifferbymorethan 25%fromaveragesamplesizepChart

ControlLimitsAverageGroupSizeAverageProportionofNonconformingItems#DefectiveItemsinSampleiSizeofSamplei#ofSamplesLCLp=UCLp=p_pChart

ExampleYouaremanagerofa500-roomhotel.Youwanttoachievethehighestlevelofservice.For7days,youcollectdataonthereadinessof200rooms.Istheprocessincontrol?pChart

HotelData #Not

Day #Rooms

Ready

Proportion

1 200 16 0.080

2 200 7 0.035

3 200 21 0.105

4 200 17 0.085

5 200 25 0.125

6 200 19 0.095

7 200 16 0.080nnkpXnpiikiikiik

111140072001211400086430864308641086420008640596.1460......

or,

.0268pChart

ControlLimitsSolution16+7+...+16

()()_pChart

ControlChartSolutionUCLLCL0.000.050.100.151234567PDayMeanp_ProcessVariability:

RedBeadExampleFourWorkers(A,B,C,D)spent3daystocollectbeads,at50beadsperday.Theexpectednumberofredbeadtobecollectedperdayperworkeris10or20%.Worker Day1 Day2 Day3 AllDays

A

9(18%) 11(12%)6(12%)26(17.33%)

B 12(24%) 12(24%) 8(16%)32(21.33%)

C

13(26%) 6(12%)12(24%)31(20.67%)

D

7(14%) 9(18%) 8(16%)24(16.0%)Totals

41 3834113 ProcessVariability

ExampleCalculationsAverage Day1 Day2 Day3 AllDays

X 10.25 9.5 8.5 9.42

p 20.5% 19% 17% 18.83% LCL=.1883-.1659=.0224UCL=.1883+.1659=.3542_ProcessVariability

ExampleControlChart0A1B1C1D1A2B2C2D2A3B3C3D3

.30.20.10pUCLLCL_MoralsoftheExample1.Variationisaninherentpartof anyprocess.2.Thesystemisprimarily responsibleforworker performance.3.Onlymanagementcanchangethesystem.4.Someworkerswillalwaysbeaboveaverage, andsomewillbebelow.VariableControlCharts:RChart(极差图)MonitorsVariabilityinProcess Characteristicofinterestismeasuredonintervalor ratioscale.ShowsSampleRangeOverTimeDifferencebetweensmallest&largestvaluesin inspectionsamplee.g.,Amountoftimerequiredforluggagetobe deliveredtohotelroomUCLDRLCLDRRRkRRiik

431RChart

ControlLimitsSampleRangeatTimei#SamplesFromTableRChart

ExampleYouaremanagerofa500-roomhotel.Youwanttoanalyzethetimeittakestodeliverluggagetotheroom.For7days,youcollectdataon5deliveriesperday.Istheprocessincontrol?RChart&MeanChartHotelData

Sample Sample

Day

Average

Range 1 5.32 3.85

2 6.59 4.27

3 4.88 3.28

4 5.70 2.99

5 4.07 3.61

6 7.34 5.04

7 6.79 4.22RRkUCLDRLCLDRiikRR

14338542742273894211438948232038940........

RChart

ControlLimitsSolutionFromTableE.9(n=5)

_RChart

ControlChartSolutionUCL024681234567MinutesDayLCLR_MeanChart(TheXChart)ShowsSampleMeansOverTimeComputemeanofinspectionsampleovertimee.g.,AverageluggagedeliverytimeinhotelMonitorsProcessAverageUCLXARLCLXARXXkRRkXXiikiik

2211and

MeanChartSampleRangeatTimei#SamplesSampleMeanatTimeiComputedFromTable____________MeanChart

ExampleYouaremanagerofa500-roomhotel.Youwanttoanalyzethetimeittakestodeliverluggagetotheroom.For7days,youcollectdataon5deliveriesperday.Istheprocessincontrol?RChart&MeanChart

HotelData

Sample

Sample

Day

Average

Range 1 5.32 3.85

2 6.59 4.27

3 4.88 3.28

4 5.70 2.99

5 4.07