6s綠帶培訓基礎篇-圖形分析法

圖形分析法6s綠帶培訓-基礎篇Honeywell

International

Inc.6-

1學習目標了解如何使用以下工具，以圖形化的方式分析數(shù)據(jù)資料：直方圖點狀圖箱形圖移動平均圖統(tǒng)計過程控制散布圖柏拉圖要因分析圖(魚骨圖)使用 Minitab制作圖表了解何處可使用這些工具64

53211091049994DayDBP20

30

40

50

60

70101091049994IndexDBP450350420410400390380370360350340330320400SupplierCustomerSurf

ace

FlawsCondensationMoisture%InspectorsMicroscopesBrakeEngagerAngleSuppliersLubricantsSpeedLathesBitsSocketsOperatorsTrainingSupervisorsMenShiftsMachinesMaterialsAlloysMethodsMeasurementsMicrometersEnvironmentCause-and-Effect

DiagramDeformationColorAir

BubbleWeight

Dev.12012.3100.013213.587.729330.074.243144.244.210005000100806040200DefectCount

Percent

Cum

%PercentCountPareto

ChartforDefects6-

2應用范例6-

3設計：一位超導電磁設計工程師必須了解電阻與溫度間的關聯(lián)性。間斷制造：一位過程工程師正監(jiān)測點火開關裝置的電線直徑。連續(xù)制造：一位過程工程師正試著判斷反應器的溫度與純度等級間是否有關聯(lián)。管理：一位客戶服務經(jīng)理希望了解客戶需求的分布情形，作為其需求價值的函數(shù)。直方圖直方圖可以以顯示數(shù)據(jù)分布的情形。請開啟EWMA315.MTW檔案。產(chǎn)出變數(shù)為DBP(用于炭黑制造)。以下為12天內(nèi)所收集的資料。In

Minitab:

Graph>Histogram,

graph

variable

DBP.

Click

“Options...”and

specify

“Number

ofintervals”

=

8.105094

96

98

100

102

104

106

108DBPFrequencyDBPTimeDay95111002110431105411085199611007110481101911051016-

4(The

First

TenObservations)點狀圖點狀圖也可顯示數(shù)據(jù)分布的情形。Minitab會在階段作業(yè)視窗中顯示點圖。In

Minitab:

Graph>Character

Graphs>Dotplot,

variable

is

DBP.請試作一個以天數(shù)為變數(shù)的點狀圖，可得出何種訊息？:::..:.

:.

:::..

.

::

::

::

::.:

::

:

:

::

::

::

::

:

::6-

5---+---------+---------+---------+---------+---------+---DBP93.0

96.0

99.0

102.0

105.0

108.01091049994DBP箱形圖箱形圖可簡易地顯示數(shù)據(jù)分布的情形，類似直方圖，但只繪制其側(cè)邊。Q1:

25%MedianQ3:

75%Graph>Boxplot,

graph

?variable

Y

is

DBP.Graph>Boxplot,graphvariable

Y

is

DBP,variableX

is

Day.6543211091049994DayDBPLowest

pointwithin

Q1-1.5(Q3-Q1)Highest

pointwithin

Q3+1.5(Q3-Q1)6-

6推移圖推移圖可以以時間函數(shù)的角度觀察數(shù)據(jù)及測趨勢請在EWMA315.MTW中建立DBP變數(shù)的推移圖In

Minitab:

Graph>Time

Series

Plot,

graph

variable

is

DBP.50

60

7020

30

40101091049994IndexDBP6-

7控制圖110100900

10

20

30

40

50

60

70Observation

NumberIndividual

Value控制圖可監(jiān)控隨時間變化的過程平均值和變異，并判定過程是否受控下。外觀類似推移圖，但卻有過程平均值和上、下控制界限。用同樣的數(shù)據(jù):Stat>Control

Charts>Individuals,

graphvariable

is

DBP.I

Chart

for

DBPX=100.83.0SL=109.6-3.0SL=92.046-

8散布圖散布圖分析兩變數(shù)間的關系。Open

‘Scatt39.mtw.’In

Minitab: Graph>Plot,

Y

varable

is

Customer,

Xvariable

is

Supplier.merSupplie336r

Custo325418375355367445385365375455395395395405365346355429385(First

Ten

observations)450350420410400390380370360350340330320400SupplierCustomer6-

9檢查表和控制圖檢查表是所有的質(zhì)量工具中，最有價值的診斷裝置之一。請看Memory

Jogger手冊中檢查表的說明。1236711.610.810.012.413.214.04

5Individuals

byDay%

PCurrent

Data

Week

16-

10M

U=12.70UCL=13.38LCL=12.02Reason1234567Change

in

Variable

A

header

pressure?Inconsistent

labresults?TemperatureT/H2OTemp/H2O

flow?Variable

A

valves

in

manual

and

wide

openRate

changesLong

lag

before

lab

results

returnPressure

controller/nent

stack

problems?Valves

sticking????柏拉圖柏拉圖是被用于確認改善目標優(yōu)先順序的重要工具，使我們能著重于造成

80%不良結(jié)果的

20%問題。Open

“PARETO64.MTW.”文件In

Minitab:

Stat>Quality

Tools>Pareto

Chart,

Chart

Defects

Table,Labels

in

‘Defects,’

Frequencies

in

“Freqs.’Defects

FreqsAirBubble

93AirBubble

81AirBubble

62AirBubble

57Weight

Dev.

120Weight

Dev.

132Weight

Dev.

91Weight

Dev.

88Deformation

18Deformation

29Deformation

31Deformation

42Week123412341234Color241Color422Color393Color274DeformationColorAir

BubbleWeight

Dev.10005000100806040200DefectCount431293132120Percent44.230.013.512.3Cum

%44.274.287.7100.0PercentCountPareto

Chart

for

Defects6-

11第二層柏拉圖第二層柏拉圖可用采更深入鉆研資料.Open

‘EXH_QC.MTW.’In

Minitab:Stat>Quality

Tools>Pareto

Chart,

chart

defect

datain

‘Flaws’中,BYvariable

in

‘Period’FlawsScratchScratchPeelPeelSmudgeScratchOtherOtherPeelPeelPeelPeelScratchScratchPeelScratchSmudgeScratchPeelPeelPeelPeelOtherOtherScratchScratchPeelScratchSmudgeScratchOtherScratchScratchPeelPeelPeelSmudgeSmudgeSmudgeOtherPeriodDay

Day

Day

Day

Day

Day

DayEveningEveningEveningEveningEveningEveningEveningNightNightNightNightNightNightNightNightNightNightNightNightNightNightNightNightNightNightNightWeekendWeekendWeekendWeekendWeekendWeekendWeekend151050DayCount151050EveningCount151050NightCount151050WeekendCountScratchPeelOtherOthersPareto

Chart

for

Flaws您應反復練習第三層、第四層等柏拉圖，直到可合理解決您的問題。柏拉圖是排列應努力項目的重要工具。6-

12因果圖因果圖(又名魚骨圖或

Ishikawa)可顯示特定瑕疪的可能因素。In

Minitab:

Stat>Quality

Tools>Cause-and-Effect,

put

each

of

the

causesinto

the

corresponding

places.ManMachineMaterialMethodMeasureEnviroShiftsSocketsAlloysAngleMicrometersMoisture%SupervisorsBitsLubricantsEngagerMicroscopesCondensationTrainingLathesSuppliersBrakeInspectorsOperatorsSpeedCondensationBrakeEngagerSurf

ace

FlawsSpeedLathesBitsTrainingOperatorsSupervisorsMenShiftsMeasurements

MaterialsMicrometers

AlloysMicroscopes

LubricantsInspector