0606-02 Quality Improvement Procedure Rev7-2

8/3/2019 0606-02 Quality Improvement Procedure Rev7-2

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Quality ImprovementProcedure

March 2008

Quality Management Department

Quality Management Group

Sumitomo Wiring Systems, Ltd.


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1. Two Types of Quality Control

Measures assuming

defects will occur

y Implementation of close inspections

y Free replacement of defective products

Measures to prevent

defect occurrence

(1) Quality of design

y QFD (Quality Functional Development)

y FMEA/FTA

y Design review

(2) Quality of manufacturingy Standardization

y Factor management

(3) Quality of sales and services

y Improvement of service system

y Feedback of repair and complaint information


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To simply prevent defective products from flowing to later processes, (1)To simply prevent defective products from flowing to later processes, (1)

will suffice, but to produce quality products at low cost, (2) is necessary.will suffice, but to produce quality products at low cost, (2) is necessary.

(1)(1) Quality assurance throughQuality assurance through

inspectionsinspections(Defective products are rejected(Defective products are rejected

in inspections)in inspections)

(2)(2) Quality building in processesQuality building in processes

(No defective products are(No defective products aremanufactured)manufactured)

Inspection

NonconformingNonconformingproductsproducts

ProductionProductionprocessesprocesses

Shipping

ConformingConformingproductsproducts

DiscardDiscard

FeedbackFeedbackof causesof causes

Processes areProcesses aremaintained andmaintained and

controlled.controlled.

Take measures forTake measures forcauses of defects incauses of defects in

each process.each process.X

ProductionProductionprocessesprocesses

ConformingConformingproductsproducts

Shipping

The basics of quality control are to improve, maintain, and control

the conditions of production processes and minimize inspections.

1. Two Types of Quality Control1. Two Types of Quality Control

Point!Point!

Man-hours

Cost


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Try to find

defects as if you

are a final

inspector.

From the SWS WAY, We

are a Professional

Manufacturing Group

y Assume that the Japanesecharacter is a defect.

y Circle as you find itand count the number of

.

Limitations of InspectionLimitations of Inspection--Based Quality AssuranceBased Quality Assurance


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Total

13 + 15 + 19 + 13 +

14+8 = 82 pcs.

Try to find defects

as if you are a final

inspector of W/H

assemblies.

From the SWS WAY1-1,

We are a Professional

Manufacturing Group

y Assume that the Japanesecharacter is a defect.

y Count the number of or defects that you found.

?


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Scientific Approach

QC story

Common Approach of Problem-Solving

Set a target Collect all the necessary facts and opinions

Analyze, summarize, and plan (P) Do (D) Check the results (C) and return to (A)

1. Select a theme2. Comprehend the current situation3. Set a target4. Plan activities

5. Analyze the cause6. Consider measures7. Implement measures8. Check the effects9. Maintain the control,

standardize the rule

10.Review the activitiesand future goals

List the problemsEvaluate and narrow down (Q.C.D viewpoint)Decide a theme

Collect dataSort the data for solution finding

List the causes Investigate the causesExtract the root cause

Plan the measures; evaluate and narrow downMake an implementation plan (define 5W1H)

Collect data and check the performance

Evaluate the intangible effect

PDCA


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What Are the QC 7 Tools?

1. Paretto graphs2. Cause-and-effect

diagrams3. Graphs4. Check sheets5. Histograms6. Scatter diagrams

7. Control charts

QC 7 tools -- the statistical analysis tools

using graphs

Variance in quality

Cause of variance(production 5Ms)ManMaterialMachine

MethodMeasurement

Manufacturing process

Datasampling

It is important to select the adequate tool(s) for the purpose

Analysis

7 QC tools


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Approach to Quality Improvement

STEP 2Condition/Status

analysis

STEP 4Permanent solution

(maintenance and

control)

Narrow down target

items using Pareto

diagrams.

(1) Understand the

facts based on the

principles of actual

work site, actual

object, and reality.

(2)Analysis using

histograms and time

series graphs

Develop 5-why

analysis based on

the facts and plan

and implement

measures.

(1) Standardization

and observance of

standards

(2) Daily control

based on control

charts

STEP 3Cause analysis and

measure planning

Identify critical factors related to defects

among many different factors.

Control critical

factors.

Find defect items

from which the

largest effect can

be expected.

STEP 1Determining defect

items subject to

activities


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3. STEP 1: Determining Defect Items Subject to Activities

STEP 1Determining defect

items subject to

activities

STEP 4Permanent solution

(maintenance and

control)

Narrow down target

items using Pareto

diagrams.

(1)Understand the

facts based on theprinciples of actual

work site, actual


(2)Analysis using

histograms and time

series graphs

Develop 5-why

analysis based on

the facts and plan

and implement

measures.

(1) Standardization

and observance of

standards

(2) Daily control

based on control

charts


measure planning



Control critical

factors.

Find defect items

from which the

largest effect can

be expected.


analysis


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What is priority basis?

This principle is to select serious problems from multiple

problems and work on them by preference to produce the

maximum results by using limited resources (people, objects,

money, time, etc.) effectively.

Is priority basis necessary?

It is necessary to make good use of limited resources and

proceed with measures effectively to avoid a mountain in

labor situation.

For this purpose, those items and causes that affect the

results greatly should be identified and dealt with first.

STEP 1Determining Defect Items Subject to

Activities

Priority basisSelecting serious problems from multiple problems and

solving them by priority


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The top 20% makes up 80% of the whole.

The priority of truly serious

problems becomes clear.

Background to Concept of Priority Basis

bParetto lawb

Numberofdefects(cases)

Cumulative

rate(%)

y Significance: The extent and degree of the influence are considerable.

y Trend of expansion: If left unresolved, the influence and degree of theproblem would expand.

y Degree of urgency: A serious outcome will result unless immediate

measures are taken.

Guideline for selecting serious problems

Q7: Pareto diagram

Unprocessed Interfusion Flaws Others


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What is a "Pareto Diagram"?

ProcessA

ProcessD

ProcessC

ProcessE

ProcessB

100

80

60

40

20

00

110

220

330

440

550

[Time(second)]

N = 20 (average)

Defe

ctA

Defe

ctB

Defe

ctC

100

80

60

40

20

00

24

48

72

96

120

[Numberofoccurrence

s]

N = 120

Defe

ctD

Defe

ctE

Defe

ctF

Others

Before improvement

After improvement

(1)Indicates what is the most important problem and what should become the focus.(2)Used to confirm the effectiveness of measures.

[%]

[%]


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Defect A

Defect B

Defect C

0 24

48

72

96

120

Number of occurrences (cases)

N=

70

Defect D

After

impro

Defect A

Defect B

Defect C

100

80

60

40

20

0

0 24

48

72

96

120

Number of occurrences (cases)

N=

120

Defect D

Defect E

Defect F

Others

Be

foreimprov

ement

Comparisono

fbeforeanda

fterimprovem

entacti

Cumulative rate (%)


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DefectA

DefectB

DefectC

100

80

60

40

20

00

24

48

72

96

120

[%]

[Numberofo

ccurrences]

N = 120

April 2002

DefectD

DefectE

DefectF

Others

Step 3 Draw the Pareto Diagram.

Points to note

y Use the right axis forthe ratios of the

accumulated totals.

y Clearly draw dots.These dots should be

placed above the right

edges of the bars.

y Do not forget to

enter "0."

y Locate "Others" on thefar right, regardless of

the value.

y Enter the total number ofsets of data(N).

For time data, enter the

number of sampled pieces

of data.

y Do not forget toenter "0."

y Draw the line of theratios of accumulated

totals from the "0" point.

Points to note

y Locate the pointindicating the numberof sets of data(N) and

the point

indicating"100%" on

the same level.

y Enter the period thisdata was obtained.

Step 4 Determine items to be considered as problems.

Points to note y Even when many classified items are presented, only two tothree items have an enough impact to require attention.


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()

100

80

60

40

20

00

24

48

72

96

120

N = 120April 2002

100

80

60

40

20

00

24

48

72

96

120

N = 120April 2002

Data are all alike and thus important

items are not visible.

This can be caused by inappropriateitem setting or there being a problem

in data collection conditions.

Defe

ctA-A

Defe

ctA-B

Defe

ctA-C

100

75

50

25

00

23

47

70

94

Defe

ctA-D

Othe

rs

When the same measures are

not appropriate for each priority

item, create a breakdown of this

item to indicate more specificpriority items (secondary

classification).

For example, when

classifying "Defect A (part

missing)" into secondary

categories: grommet missing,

clip missing, tube missing,

etc., it becomes easier to

examine specific measures.

Points to note

[%]

[Numberofoccurrences

]

[%]

[Numberofoccurrences

]

[%]

DefectA

DefectB

DefectC

DefectD

DefectE

DefectF

Oth

ers

DefectA

DefectB

DefectC

DefectD

DefectE

DefectF

Oth

ers


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Step 5 Compare Pareto diagrams before and after measures are taken.

0

24

48

72

96

120

Defect A Defect B Defect C Defect D Defect E Defect F Others

0%

20%

40%

60%

80%

100%

0

12

24

36

48

Defect C Defect D Defect A Defect E Defect F Defect B Others

0%

20%

40%

60%

80%

100%

Before improvement

After improvement

Overall effectiveness

Effectiveness ofmeasures for B

Use the same color for the

same item bar.

N = 120

N = 48

Effectiveness ofmeasures for A

Points to note


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Table Actual Defect Data

Replacement/repaircost (yen)

Defect itemNumber of

defective parts

Cost per

partTotal

Mislocation 110 300 33,000

Terminal deformation 75 1,800 135,000

Terminal backout 43 200 8,600

Incorrect crimping 31 2,000 62,000

Part missing 15 400 6,000

Others 26 300 7,800

Total 300 252,400


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Number of defects Cumulative rate (%)

100

90

80

70

60

50

40

30

20

10

0


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Cost of loss Cumulative rate (%)

100

90

80

70

60

50

40

30

20

10

0 0


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Incurred cost

Defect itemNumber of defective

parts

Accumulated number

of defective parts

Ratio of accumulated

number of defective partsMislocation 110 110 36.7%

Terminal deformation 75 185 61.7%

Terminal backout 43 228 76.0%

Incorrect crimping 31 259 86.3%

Part missing 15 274 91.3%

Others 26 300 100.0%

Number of defective parts

Defect itemAmount of incurred

costs

Accumulated amount

of incurred costs

Ratio of accumulated

amount of incurred costs

Terminal deformation 135000 135000 53.5%

Incorrect crimping 62000 197000 78.1%

Mislocation 33000 230000 91.1%

Terminal backout 8600 238600 94.5%

Part missing 6000 244600 96.9%

Others 7800 252400 100.0%


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0

50

100

150

200

250

300

Terminal

deformation

Incorrect

crimping

Mislocation Terminal

backout

Part missing Others

0%

20%

40%

60%

80%

100%

0

50

100

150

200

250

300

Mislocation Terminal

deformation

Terminal

backout

Incorrect

crimping

Part missing Others 0%

20%

40%

60%

80%

100%Number of defective parts

Incurred cost (unit: 1,000 yen)

Ratio Accumulation

Terminal deformation

:25% of defective parts p 54% of total cost

[No.ofdefects(pcs

.)]

[Costofloss(1,000yen)]

[Cumulativerate(%

)]

[Cumulativerate(%)]


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Defect A of product a

produced with equipment(1)

Visual observation

[Defect type]

[Product type]

[Equipment]

y Three Paretodiagrams and

one eye

For defect reduction

a b c d e

(1) (2) (3) (4) (5)


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1 R

1R

Examples of Pareto Diagrams Used for W/H Assembly Process

1 R

1R

1 R

July August September October November

In-house occurrence

Occurrence other than in-house

Classified by

subassembly No.

(home worker)

Classified by defect item

Classified by

subassembly No.

- connector

Classified

by

connector

Secondary classification

for mislocation


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}

}

07/6

3.4%

115171

07/11

2.5%

171

770/

}

}

07/6

3.4%

115171

07/11

2.5%

171

770/

}

}

07/6

3.4%

115171

07/11

2.5%

171

770/

(Case 1) Factor Identification Using Pareto Diagrams

Focused on

incorrect

dimension

Based on defect items

Frequently

occurred in

115 and 171

Defect rate3.4% in

June 2007

Defect rate2.5% in Nov.

2007Reduced

Incorrect dimension of

unique block 171

eliminated

(7l0 case/month)

Incorrect

dimension

Incorrect

dimension

Partdamaged

Partdamaged

Mis

location

Mis

location

Taping

omitted

Terminal

deformation

Terminal

deformation

Taping

omitted

Terminal

backout

Terminal

backout

Lock

omitted

Lock

omitted

Defectivepart

atta

chment

Defectivepart

atta

chment

Others

Others

Others

Others

In-depth identification on unique

blocks of defect occurrence


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171mm

A

U

A

A

A

A

171mm

A

U

A

U

A

A

A

A

(Case 1)

Case of improvement:Unique block bent in L-shape changed to be

placed straight on clamp board

Fig. 3 (1)

Before

improvementAfter

improvement

Fig. 3 (2)

Fig. 3 (3)On clampboard

Dimension of171 mm on

board

Clamp

U-jig

Connector

The shape of

this unique

block ischanged to

straight.

Depending on wiringconditions

Displaced outward

in U-jig

Displaced inward

in U-jig

Dimensional accuracy

improved.

Dimensions

between

clamps are

different.


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Investigate the important item and classify it by secondary and tertiary

categories to narrow down activity targets.

Summary of Pareto Diagram Analysis

For W/H (example)

y Classify by defect item p by number of connector ways p by connector No.p by address

Investigate to the level where you cancheck the facts with actual productsand at the actual worksite.

This is the beginning of 5-Why Analysis.

Why has mislocation occurred at addressXX in connector No. ##?

Observing the actual products at the

actual worksite enables the

identification of root causes.

Why has mislocation occurred forsimilar red wires?

Since there are many similar colors,

further classification is required to identify

the root causes by using actual products

at the actual worksite.


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284. STEP 2: Phenomenon Analysis (Qualitative Facts)

STEP 3: Cause Analysis and Measure Planning

STEP 4

Permanent solution

(maintenance and

control)

Narrow down target

items using Pareto

diagrams.

(1) Understand the

facts based on the

principles of actualwork site, actual


Develop 5-why

analysis based on

the facts and plan

and implement

measures.

(1)Standardization

and observance ofstandards

(2) Daily control

based on control

charts


measure planning



Control critical

factors.

Find defect items

from which the

largest effect can

be expected.

(2)Analysis using

histograms and time

series graphs

STEP 1

Determining defect

items subject to

activities


analysis


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Root Cause Identification- Understanding Facts and 5-Why Analysis -


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Problem solution (root cause identification) is difficult.

Importance of Root Cause Identification

Example 1: Conversation between boss and employee

at a plant

Boss: Another same claim!

You have taken the measure, havent you?

Why did it happen again?

Employee : The measure might not be appropriate.

Boss: You mean that root cause analysis was

inadequate?

Employee: Yes, I suppose so What should we do?


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Why does the problem reoccur?

The cause determined was not the real cause.

The measure taken was not appropriate.

The problem reoccurred.

That is,

How to find solution for the problem = real cause

is the key point.

5-Why Analysis is a methodto help identify the root cause


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Familiar Stories

Defect details: Incorrect product number label

y The label was damaged during assembly.y A non-Japanese inspector found this, replaced the label with

another, and shipped the product.

Familiar stories???

Cause: The non-Japanese inspector did not observe the abnormalityhandling rule.

[Rule] Inspectors must inform the leader or substitute

before replacing the label, and follow his/her

instructions.

[Fact] The inspector replaced the label by him/herself.

pAgainst the rulesMeasure:

1) Prepare operation instructions that non-Japanese people can

understand (only in Japanese until now).

2) Conduct thorough training regarding abnormality handling rules.


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Familiar Stories What is the reality?

Defect details: Incorrect product number label

y The label was damaged during assembly.y A non-Japanese inspector found this, replaced the label with another, and shipped the product.

Cause: The non-Japanese inspector did not observe the abnormality handling rule.

p It is a rule that they must inform the leader or substitute.Measure:Prepare operation instructions that non-Japanese people can understand, and

conduct thorough training regarding abnormality handling rules.

When we investigated the reason why the inspector did not observe the

abnormality handling rule.

The inspector knew this rule! However

Unless measures are taken against this problem, the same problem may reoccureven if rules are thoroughly instructed.Preparation of operation instructions and training for abnormality handling rules are notthe measures against the root cause.

* Measures must also be taken at the assembly process where the label was damaged.

y The leader was not close by.

y Action to be taken when the leader is absentwas not determined.y It was almost shipment time.

The rule

was notobserved.


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-- See the facts. --

Key Points of Root Cause Identification

1) 3-Gen (Real Place, Real Thing, Reality) Principle

To eliminate preconceived ideas, learn how to see the facts.

p Make a habit of looking at the facts by yourself!

2) 5-Why Analysis

To avoid leaps in logic, connect Cause and

Effect with Why.

p Make a habit of thinking about physical phenomena!


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Ones own

knowledge

(1) Self-reflectionExperience, instincts, ideas,

thoughts (principles)

(2) RecallKnowledge and experience

related to external matters

accumulated in the head

External

information

Being told by someone,reading, sorting previous

data, discussions

(4) Seeking direct

information

Observation (qualitative),

measurement (quantitative)

Top priority

When a defect has occurred in a process, stop the line, immediately go to the actualwork site, immediately take a look at the actual item, immediately check thesituation (actual phenomenon), and take action or implement measures.

How to Look at Facts: Methods to Collect Information

Amountofinformation

Reliability

(3) Seeking indirectinformation

3-Gen Principle

(Actual-Worksite-Actual-Item Principleand 3-Immediate & 3-Gen Principle

HAI-Q:When a defect occurs, the line is stopped and persons concerned

immediately gather on the spot to share facts.


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A scene from typical detective drama:

Anthony, I am sure he is the criminal. Now, go and get him.

Make him come clean!

Despite the senior detectives order, the leading character

Anthony carefully observes the actual site of the crime, and

collects facts by asking around until he find the real criminal.

Facts or preconceived ideas?

Distorted common sense.

Should be and should not be.

Presumption goes around...

Seeing the Facts Is Really Difficult


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(Question) Where was the post box ?

(Answers) y I dont know 35 %

y No answer. 3%

y Answered with a guess. 62 %(Breakdown) y Uncertainly answered

(I think ) 23 %

y Certainly answered(It was at ) 39 %

40% assertively answered the question, which they were not sure of


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5-Why Analysis Connects Causes and Effects

Effect

Cause = Effect

Cause = Effect

Cause = Effect

Why?

Why?

Phenomenon occurred. Why?

Because phenomenon occurred.

To avoid leaps in logic

This systematic development is

5-Why Analysis.

Location of wires O and R for

connector No. 160 was incorrect.

Confused wire O with wire R.

(Why)

Operators determined which wire

they had in their hands based on

the wire length, without

confirming the wire color.

(Why)

Operators felt pressed because

operation was delayed.

(Why)

Time was taken to untangle

subassemblies because they got

tangled.


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Generally, there may be

several possible causes

for a single phenomenon. Confused wire Owith wire R.

The wires were seen

incorrectly.

Both wires were of the

same color, so it was

difficult to distinguish

them.

Location of wires O and R for connector No. 160 was incorrect.

The top and bottom

of the connector lock

was incorrect.

Wires O and R were in his/her

hand. The operator had a

preconceived idea that thelonger wire was wire O (did not

check the wire color).

Arrangement

before minor

changes wasapplied.

The arrangement drawing

on the assembly board

was incorrect.

Did not check

the top and

bottom.

As you analyze why and why,

branches of possible causes spreadfurther and further.

qWe suggest the basic method of5-

Why Analysis.

[5-Why Analysis STEP 1]Collect Facts and Analyze Phenomenon before ThinkingWhy

Did not check for

changes made to

arrangement.

Since wire R was off the

U jig, wire R was longerin his/her hand.

Determining which wire the

operator had in his/her hand

based on the length is faster than

confirming the color.

The operator felt

pressed because


Time was taken to

untanglesubassemblies

because they got

tangled.


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Confused wire Owith wire R.

The wires were seen

incorrectly.

Both wires were the same

hue, so it was difficult to

distinguish them.


The top and bottom


was incorrect.

Wires O and R were in his/her

hand. The operator had a

preconceived idea that the

longer wire was wire O (did not


Arrangement

before minorchanges was

applied.

The arrangement drawing

on the assembly board

was incorrect.

Did not check

the top and

bottom.

Did not check for

changes made to

arrangement.


U jig, wire R was longer

in his/her hand.



based on the length was faster

than confirming the color.

The operator felt

pressed becauseoperation was delayed.

Time was taken to

untanglesubassemblies

because they got

tangled.

Dont Start with Why

Collect the facts andclarify the phenomenon,and then narrow downthe scope.

For example, if the operation

method (fact) caused confusion of

wires can be made clearer by

asking the operator

.

You dont have to analyze

why for the otherwhys.

4W1H except for WhyCarefully collect the

relevant facts in terms

of Who, When, Where,

What, and How. Analyze the

phenomenon before

analyzing the cause!!

Wire O

Wire R


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[Step 2] Identify Causes Based on Facts--- Streamlining with facts to cut branches

Why was the

arrangement incorrect?

Confused wire O

with wire R.



The top and bottom


was incorrect.X

Confused wire O

with wire R.



The top and bottom


was incorrect.XThe wires were seen

incorrectly.Wires O and R were in his/her hand. The

operator had a preconceived idea that the

longer wire was wire O (did not check the wire

color).

Since wire R was off the U jig,

wire R was longer in his/her hand. X

Branching is

acceptable when thereare multiple causes.

5-Why Analysis

is a repeat ofthese steps.

It is not necessary to

analyze why for cutbranches.

Were these facts? (1) is a fact and (2) is not a fact.

(2)(1)

p Whys?


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Identify Root Cause Based on Facts Stepwise

Confused wire O

with wire R.

Saw the wires

incorrectly.


The top and bottom


was incorrect.

The arrangement

drawing on the

assembly board was

incorrect.

XX

XWires O and R were in his/her

hand. The operator had apreconceived idea that the



Since wire R was off theU jig, wire R was longer

in his/her hand.



based on the length was faster

than confirming the color.

The operator felt

pressed because


Time was taken tountangle

subassemblies

because they got

tangled.

Dont skip, go

stepwise.

To avoid leaps in logic, move

down the stairs one by one.


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Retrace branches for any leaps in

logic and confirm that items areconnected with Because.

A leap in logic exists in sections not

connected with Because.

[Step 3] Connect with Why and Verify with Because

Confused wire O

with wire R.

The wires were seenincorrectly.


The top and bottom


was incorrect.

Wires O and R were in his/herhand. The operator had a

preconceived idea that the



The arrangement

drawing on the

assembly board was

incorrect.


U jig, wire R was longerin his/her hand.



based on the length is faster than

confirming the color.

The operator felt

pressed because


Time was taken to

untangle

subassemblies

because they got

tangled.

XXX

Why

Because

4


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When conducting 5-Why Analysis for mistakes at the worksite where manymanual operations are performed:

y It is difficult to collect the facts.y There are many cases where decisive factors are not found.p Check the facts based on the Actual-Worksite-Actual-Item Principle, and

extract factors that may cause defects. We may have to conduct 5-WhyAnalysis based on assumptions to some extent.

[Mislocation] When: Did something occur then?

Operation was delayed, so the operator became nervous?p Why? p Operator had to untangle a tangled subassembly.This delayed operation.

Where: Is the insertion position and direction of the connectorappropriate? Is the color of these wires the same?

y Assume all factors that may cause or induce mistakes.y Examine the factors assumed ultimately and take measures!

p However, this is difficult work.Therefore understanding phenomenon of the defect is important.

Mistakes in Manual Operations

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46

(Operation rules that may cause mistakes)

y There are many items operators mustdetermine or check by themselves.

y Setting depends on the skill of operators.y Operators must conduct multiple

operations simultaneously.

Operation system

Standardize operations.

Simplify operations.

Implement hardware measures(including fool-proof devices)

Flow production, one-piece

production and flow, one

operation for one product

number, First-In First-Out

(Not always perfect)

y See or hear incorrectlyy Forget easilyy Action (hands/feet) differs from

thinking (mind).

Human behavior

Education, training, OJT

training, reminders/cautions,

award system

Human Error Factors and Measures

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47

Human Error Factors and Measures

Indirect factors

Operational and environmental

rules that may induce:

Ideal root cause identification

y Mistakesy Feeling of pressure

Extract the defect occurrence possibility

based on the Actual-Worksite-Actual-Item

Principle, and take measures

Direct factors

Conventional root cause identification

Education, training,

OJT training,

reminders/cautions

y Omit checksy See or hear incorrectly

y Misunderstandy Forget easily

48


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48

Company Standard Proactive and RecurrencePrevention of Human-Error Quality Problems

QC-CW-114 (Established on March 1, 2007)

Elimination of elements that may lead to human-error quality problems

(proactive prevention)

Eliminate elements that may lead to human-error quality problems by improving

processes and standards.

Eliminate elements related to indirect factors

(P.33).Company standard

5-1. Items to implement in production preparation stage

5-2. Items to implement in process control

Points of view to identify the

elements that may cause a

problem

Items to implement upon occurrence of human-error quality problems

(recurrence prevention)

When such a quality problem occurs, trace back to the management factors to

remove the root of the problem, including indirect factors.

Company standard 6. Items to implement after a quality

defect occurs

Root Cause Identification

Sheet

49


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49Review Sheet for Zero Defects in Human-Involved Operation

Regarding each item

in 5-1 and 5-2.

Extract issues by checks

(actual worksite and object)

Summarize measures and

actions (plan)

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50

Factors that induce human errors (1)

[Operation method and details]

(1) Operations that may cause defects

1) Operations determined by operators

2) Operations relying on operators experience and skills

3) Operations performed with operation/inspection procedures entrusted to operators

(standards not arranged)

4) Difficult operations

5) Operations that are not realistic (cannot be performed or observed)

6) Operations with elements of Muri (overburden), Mura (unevenness), and Muda

(waste), that hamper smooth operation

7) Multiple operations (assembly and transfer, handling multiple lines, supervising and

operation, etc.)

8) Operations that require mutual cooperation between adjacent processes

[Infrastructure (1)](1) Operational environment that may cause defects

1) Normal/abnormal cannot be determined due to insufficient 4S.

2) Storage location and inventory standard are unclear.

3) Similar components or finished products are stored adjacently.

4) Operators cannot be viewed due to stacked returnable containers or high equipment.

5) Operation areas are dark or dirty.

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51


[Infrastructure (2)]

(2) Processes that may cause defects

1) Confusion with similar products is not adequately assumed in process design, and

number control is not performed.

2) Actual operation situation and past problems are not reflected in process design

(difficult-to-work process layout and equipment structure).

3) Continuous normal operation is difficult due to frequent stoppage.

4) Machines in use cannot assure conforming products (insufficient process capabilities,

machine deterioration, etc.).

5) Foolproof devices are not installed (important characteristics, defects rarely found in

subsequent processes, defects that cannot be avoided by human determination, etc.).

6) Foolproof devices lack reliability (incorrect detection, frequent malfunction).

(3) Inadequacy of standards, gages, and jigs

1) Operation procedures, quality check standards, and pass/fail criteria are not prepared(including preparation for non-Japanese operators).

2) Inspection devices, jigs, and gages are not controlled.

3) Reliability of inspection is insufficient (inadequate operation procedures, insufficient

inspection time, poor operation environment, inadequate inspection tools, inspection

relying on visual check).

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52


[Management and training (1)]

(1) Rules not established1) No rules for handling abnormalities

2) No rules for handling defective products

3) No rules when leaving the operation line

4) No rules for FIFO (first-in, first-out)

5) No rules for inspecting the initial and last products in a lot, and others

(2) Worksite environment that may cause defects

1) Worksite where 4S are not thoroughly conducted2) Worksite where rules for handling abnormalities are not observed

3) Worksite unable to control changes

4) Worksite constantly exposed to changes (equipment failure, change of personnel, delivery period, etc.)

5) Worksite management with insufficient personnel (operators, supervisors)

6) Worksite unable to respond to drastic increase in production volume

7) Worksite where operators are exhausted due to high load or overtime work

8) Worksite full with complaints of operators

(3) Training system not established1) Allocation of inadequate personnel

2) Assignment of new operators without training

3) Only verbal training

4) Training system in which subjects to be taught are not determined (no training materials)

5) Training without checking understanding level (the purpose is simply doing)

6) Lack of operators awareness and quality (evaluation remains the same even if done or not done)

7) No check system after new operators are assigned

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53


[Management and training (1)]

(4) Inadequate management

1) Inadequate daily management by managers/supervisors/leaders

(control items unknown)

2) Periodical operation observation not implemented by managers/supervisors/leaders

3) Changes not controlled

4) Worksite management without discipline

(overlooked even when rules are not observed)

5) Management materials not prepared (defect data, map of dropped products,

production results, etc.)

6) No system to collect opinions from worksites and reflect them in operations

7) State of worksites not visual (lack of visualization, state of objects unknown)

(5) Inadequate maintenance

1) Periodic checks not conducted2) Daily check not conducted (including check of foolproof devices)

3) Scheduled maintenance not implemented

[Others]

1) Startup of new product without operation training and check (no milestone control)

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54

Company Standard Proactive and RecurrencePrevention of Human-Error Quality Problems

QC-CW-114 (Established on March 1, 2007)

Elimination of elements that may lead to human-error quality problems

(proactive prevention)

Eliminate elements that may lead to human-error quality problems by improving

processes and standards.

Eliminate elements related to indirect factors

(P.33).Company standard

5-1. Items to implement in production preparation stage

5-2. Items to implement in process control

Points of view to identify the

elements that may cause a

problem

Items to implement upon occurrence of human-error quality problems

(recurrence prevention)

When such a quality problem occurs, trace back to the management factors to

remove the root of the problem, including indirect factors.

Company standard 6. Items to implement after a quality

defect occurs

Root Cause Identification

Sheet

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55

Root Cause Identification Sheet for Human-Error Problems

Standards

Keywords to identify root cause

(1) Were there any similar defects in the past?

(2) Were there any difficult operations in the past?(3) Have you ever experienced close calls?

(4) Were any difficult operations reported?

(5) Were there any operations conducted without fullyunderstanding procedures or rules?

(6) Were there any changes (5M) immediately before aproblem occurred?

To identify root cause

All the persons mentioned below must identify the root cause:

y The person who made the mistakey Persons involved that could not prevent the mistakey Persons involved that could not find the mistake

Defective products orcomponents

Equipment failure, temporary

stoppage

Defective tools and jigs

Change in environment (shelves,

indications, illumination, etc.)

Change in system or tooling

(emergency response, etc.)

Operation delay

Helping for other operators

Talked to by someone during

operation

Preconceived ideas

Insufficient concentration

Incorrect determination

Incorrect operation

Carelessness

Incorrect memory

Poor physical condition

Physical factors

Human factors

Physical factors

Human factors

(1st step) (2nd step ) (3rd step ) (4th step ) (5th step )There arestandards.

Defective products or componentsEquipment failure, temporary

stoppageDefective tools and jigs

Change in environment (shelves,indications, illumination, etc.)

Change in system or tooling

(emergency response, etc.)

Operation delay

Help for other operators

Talked to by someone during operation

Preconceived ideas

Insufficient concentration

Incorrect determination

Incorrect operationCarelessness

Incorrect memoryPoor physical condition

Operators didnot know the

standards

Instructor didnot teach

operators

Had no time to teach subject

Does not know how to teach subject

Had no intention of teaching subject

Forgot to teach subject

Did not know they had to teach subject

Assumed subject had been taught

Importance placed on production(no time allowance, etc.)

There is no teaching sys tem (or it is not known)

There are no teaching materials

Not clear who they should teach

Did not teach comprehensively.

Did not teach certain people.

Instructortaught

operators

Operators were taught butthey forgot

Operators could notunderstand

Operators were taughtincorrectly

Does not feel necessary. Reasons were not explainedDid not understand reas ons

Insufficientunderstanding

Did not teach according tothe operators level

Insufficient supportafter teaching

Misunderstood

Insufficient teaching time

Made mistakes

Insufficient understanding

Teaching was not specific

Teaching skill was poor.

Instructors understanding was incorrect

Poor teaching skillsHad preconceived ideas

Operators

knew the

standards

Observed

but caused

defect

Deficiency in standards or system Omission of operation points Insufficient pre-examination

Faulty tools and jigs Not reported

Reported but only tentative

measures were taken

Reported but not accepted

Insufficient communication

There were difficult orhard-to-judge operations Not reported

Reported but only tentativemeasures were taken

Reported but not accepted

Insufficient communication

Did not observe With external influences

(situation wherestandards could not beobserved)

Without externalinfluences

(standards could havebeen observed)


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57


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57

STEP 4

Permanent solution(maintenance and

control)

Narrow down target

items using Pareto

diagrams.

(1) Understand the

facts based on the

principles of actual

work site, actual


Develop 5-whyanalysis based on

the facts and plan

and implement

measures.

(1)Standardization

and observance ofstandards

(2) Daily control

based on control

charts


measure planning



Control critical

factors.

Find defect items

from which the

largest effect can

be expected.

(2)Analysis using

histograms and time

series graphs

4-2. STEP 2: Phenomenon Analysis (Quantitative Data)

STEP 1

Determining defectitems subject to

activities


analysis

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58

What Are the QC 7 Tools?

1. Pareto diagrams2. Cause-and-effect

diagrams3. Graphs4. Check sheets5. Histograms6. Scatter diagrams

7. Control charts

QC 7 tools -- the statistical analysis tools

using graphs

Variance in quality

Cause of variance(production 5Ms)ManMaterialMachine

MethodMeasurement

Manufacturing process

Datasampling

It is important to select the adequate tool(s) for the purpose

Analysis

7 QC tools

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59

QC 7 Tools - Comprehensive Drill

You belong to the coated wire extruding process group.

There are several kinds of defectives, and those are gettingserious quality issues. Now you are assigned to reduce thenumber of defectives.

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60

Pareto diagram showing amount of loss

10

20

Flaw

Pullout

force

Lump

Bad

winding

Cumulativerate

(%)

0

50

100Reel produced in Jan. 07

Loss(1,000ye

n)

0

Conductor

Insulation

Flaw

Lump

Pullout forceinspection

Surface

inspectionAppearance

inspection

Bad winding

Example Problem: Reduction of Loss from

Defects in Wire Extrusion Process

Pullout force defect

(standard: 85 - 115 N/cm2)

Pullout force defect

determined to be an

activity target

70% of

loss

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61

62Q7: Histogram


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62

Standard value:

85 - 115 N

The table on the

right is data of

pullout capacity.

The standard

value is 85 N or

larger and smallerthan 115 N.

Minimum measuring unit: 0.1

Histogram Analysis

Create a histogram

and analyze pulloutforce data.

(1) Does the average

deviate?

(2) Is the dispersion

excessive?

Q7: Histogram

N = 65

Manufactured in

Jan. 2007

Determined to

improve pullout

force defects.

Lot No. Pullout force Defective Lot No. Pullout force Defective Lot No. Pullout force Defective

63Q7: Histogram


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63

HistogramHistogram

Column (class)Column (class)

Class boundary valueClass boundary value

Class intervalClass interval hh

yy Histograms are a tool to:Histograms are a tool to:

yy Terminology of histogramsTerminology of histograms

yy Point in preparationPoint in preparationDivide data from the maximum value to the minimum into several classes to make the distributionDivide data from the maximum value to the minimum into several classes to make the distribution

easy to read.easy to read.

Maximum valueMaximum value

hh

Minimum valueMinimum value

Make it possible to overview the distribution of large volumes ofMake it possible to overview the distribution of large volumes of

data at a glance;data at a glance;

Make it easy to calculate the average and standard deviation; andMake it easy to calculate the average and standard deviation; and

Understand the relationships between the data and standards.Understand the relationships between the data and standards.

Q7: Histogram

64Procedure for making a Histogram


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Collect data (done) Number of bars: B = 65 8

Largest value: L = 121.8 Smallest value: S = 80.3 Class interval: h = (L-S) / B = (121.8 - 80.3) / 8 =5.14

rounded to 5.1 (decimals point 1 place)Decidenumber of intervals

interval rangeclass boundary value

Procedure for making a Histogram

Make graphsthat can also beunderstood by

the others

e.g.# of intervals: 9

Class interval : 5.0

Lower limit specification value

Upper limit specification value

Class boundary value=Specification value

Easy to comprehend!

Interval

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Make a frequency table

///

//// /

//// //// /

////

////

////

////

////

////

////

///

/

///

///

/

Class Mid. frequency

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Specification lower limitSL85

Specification upper limitSU115

N=65Manufactured

in March 2004Out of SL and SU;both are the problem!

Average value isexactly the

target value!

Priority must beput on improving

the deviation.

Average value 99.87Standard deviation 8.62

Make a histogram

frequency

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Normal distribution

type

(Process under control)

Plateau type or

double-peak typeSmall isolated

island type

Outliers resulting from

unexpected causes

Data of two different groups

is mixed

JNeeds to be stratified

The upper or lower limit is purposefully aimed at.

Data is skewed toward the lower specification limit.

Sub-standard products are removed by inspection.

Shapes of Histograms and Presumed Causes

Trailing skirt shape

type or cliff shape type

68How to Read HistogramsHow to Read Histograms


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How to Read HistogramsHow to Read Histograms1.1. Find the characteristics of distributions.Find the characteristics of distributions.

2.2. Compare distributions against the specification.Compare distributions against the specification.

3.3. Stratify and compare them to determine differences according to stratifications.Stratify and compare them to determine differences according to stratifications.

Normal distribution type Toothless type Skewed-to-the-right type

Cliff shape type Double-peak type Small isolated island type

The process is under control.

(Commonly seen)

This case results from incorrect orinconsistent measurement readings.

y Data is skewed toward the lower specificationlimit.

yThere are none under a certain value, in theory.

Sub-standard products were

removed by 100% sorting.

Two distributions with different

average values are mixed.

Outliers resulting from

unexpected causes

69Average value and standard deviation


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Average value and standard deviation

(1) Average value

(2) Deviation sum of squares

(3) Unbiased variance

(4) Standard deviation

X Assumed onnormal

distribution

i

X

)X(X

i

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What is Normal Distribution?

Example:Actual dimensions of

products manufactured to a certain

dimension range

Normal

distribution

Bilaterally symmetrical distribution with

sloping data dispersion curves, for

processes under stable conditions*

*Only genuine and inevitable dispersions occur.

Frequency

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What is Normal Distribution?What is Normal Distribution?

yy Shape of distributionShape of distribution

yy Numerical expressionNumerical expression

yy The normal distribution of the averageThe normal distribution of the average QQ and theand thestandard deviationstandard deviation WW is represented as N (is represented as N (QQ,, WW 22).).

Probability density functionProbability density function

As the total amount of dataAs the total amount of data

(N) increases and the class(N) increases and the class

intervals become narrower,intervals become narrower,

the ultimate measuredthe ultimate measuredvaluesvalues f (x)f (x) mostly formmostly form

normal distributions.normal distributions.

22

22

22

))((

22

11))((

WWQQ

WW

----

==

xx

eexxff

aa bb ggxxQQ

WW

))(( xxffyy ==

gg

TT

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Population Parameters and StatisticsPopulation Parameters and Statistics

PopulationPopulation

PopulationPopulation

parametersparameters

QQ22WW

WW

11xx

22xx

nnxx

StatisticsStatistics

SpeculationSpeculation

(Populationparameters)

(Statistics)

Average

Dispersion

Standard

deviation

QQ

22WW

WW

xx

VVss

xxVV

ss

V!

V!

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Meaning ofMeaning ofQQ andand WW

In a distribution,In a distribution, QQ indicates the median position andindicates the median position and WW indicates the dispersionindicates the dispersiondegree (or width).degree (or width).

11QQ

22QQ

WW

11WW

22WW

The dispersion degreeThe dispersion degree WW did not change, but the averagedid not change, but the average QQ changed.changed.

The averageThe average QQ did not change, but the dispersion degreedid not change, but the dispersion degree WW changed.changed.

WW

QQ

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W W W

Characteristics of Normal Distribution (1)

s1W 68%

s2W 95%

s3W 99.7%

When a measure ofdispersion degree W(standard deviation) is used

99.7% of all of the data exists in the range ofs3W from the average.

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N=65Average value 99.8 7

Standard deviation 8.62

s1W 68%

99.87s8.62

s2W 95%

99.87s2 x 8.62

s3W 99.7%

99.87s3 x 8.62

V

X

Characteristics of Normal Distribution (2)

Frequency

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What Is Process Capability?

When a process is under control, its capabilities can be

understood from the relationship between the range ofspecification values and the standard deviation.

Lower

specificationlimit

(SL)

Upper

specificationlimit

(SU) Defects rarelyoccur.

Defectsfrequently occur.

Range of

specification value

W

6W

W

6W

Range ofspecification

value > 6W


value < 6W

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Concept of Process Capability (1)

V6

x

Process capability index

V6SSCp LU

Range of specification value

x

Large CP value = High

process capability

LSLS

US US

Process capability index:

CP (for specification with upper and lower limits)


value


value

Dispersion

V6

In our company, we often assume that a

process with CP 1.33 generally has

sufficient process capability.

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USLS

V4

V6

V8

x

x

x

V

V

V

5/100p:rateDefect

0.67Cp

V4SSWhere LU

!

!

!

p:rateDefect

1.33Cp

VSSWhere LU

!

(5%)

(0.3%)

(0.006%)


3/1000p:rateDefect

.001Cp

V6SSWhere LU

!

!

!

79


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1.5/1000p:rateDefectCp

V36XorXSWhere(1) LU

!

100000/3p:rateDefect,

33.1Cp

VSXorXSWhere(2) LU

V3

US

xx

LS

The defect rate is 1/2

of the specificationwith upper andlower limits.


CP (for specification with either limit)

x x

V3

(0.15%)

(0.003%)

V3

X-S

Cp

U!

V3

S-X

CpL

!

With upper

specification limitWith lower

specification limit


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V6

x

US

LS

x

M

Mean specification value = M(SU+SL)/2

Extent of deviation ( = | |

V3

)S(S21

CpkLU

!

Half the range of specification value Extent of deviation

Dispersion

Cp u Cpk

(Where ( = 0, CP

= CPK

)

y Process capability index withdistribution bias assessed

y Same concept as CP forspecification with either limit

When the deviation ( is large, the Cpkvalue more accurately represents the

process capability.


Cpk (for specification with upper and lower limits)

M x


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Which reduces the process capability,the average deviation or dispersion?

This can be determined by the values for Cp and Cpk for each process.

Cp

Cpk

0.67

0.67

Cp

Cpk

1.00

0.67

Cp

Cpk

1.33

0.67

Process 1 Process 2 Process 3

To improve the Cpk of processes 1 to 3 from 0.6

7to 1.33 or higher

Improve

dispersion.

Improve average

deviation.

Improve dispersion.

Improve average

deviation.

Prepare histograms, instead of determining by the values of Cp and Cpk only.


82

Sorting out the causes using Cause and effect diagram


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Dispersion ofthe strip force

MaterialMachine(extruder)

Man Method

Materialfife

plasticizerlot

extrusionpressure

coolingwatertemp.

Polyethylenelot

testmachine

skill

wrongprocedure preheat

operation

mistakeMaterialmixing

Sorting out the causes using Cause-and-effect diagram

Sort out by breaking the causes into 5M

83Problems in factor organization using


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Cause-and-effect diagrams are very useful as a tool to organize factors in

many different peoples minds and share the same recognition; however,inappropriate use of them can result in a leap in logic.

Factors have been organized!

Lets think about measures

now!

The listed factors are no more than assumptions, so it is

necessary to check the facts before considering measures.

Problems in factor organization using

cause-and-effect diagrams

This is

the

cause!

This must be acause!

Machine Material

Measurement Man Method

Pro

blem,defect,and

trouble

84Analysis Based on Time Series Graphs

Q7: Graph


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Analysis Based on Time Series Graphs

Equipment

stoppage

(weekend)

Equipment

stoppage

(weekend)

Equipment

stoppage

(weekend)

Cooling

water

problem

Enter changes on a time

series graph for analysis

(event analysis).

Pullout force

N/cm2

Pullout force is weak

immediately afterequipment start-up.

85Relational analysis betweenh t i ti l d t t


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characteristic value and potent cause

In the case of analysis the relation between two parametersScatter Diagram

Draw Scatter Diagram from

this data

86

Comprehending the relationship betweenh d d h ff i S di


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Scatter Diagrambetween Extrude pressure & Strip force test

0.870 1.0 1.2 1.4 1.6 1.8 2.0 2.2

80

90

100

110

120

130

Strip

force

(kgf)

Extrude Pressure (kg/mm )2

the presumed causes and the effects using Scatter diagram

No correlation

87

Comprehending the relationship betweenth d d th ff t i S tt di


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Scatter Diagrambetween Cooling water temperature & Strip force test

130

70 12 14 16 18 20 22

80

90

100

110

120

Strip

force

(kgf)

Cooling water temp. ( )24 26 28

Negative correlation when the water temp. goes high,the strip force goes down.

the presumed causes and the effects using Scatter diagram

88

Controlled range of the causes


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70 12 14 16 18 20 22

80

90

100

110

120

Strip

fo

rce

(kgf)

Cooling water temp. ( )24 26 28

Specificationrange

Controlled range of the causes

895. STEP 4: Permanent Solution (Maintenance and Control)


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5-1. Standardization and observance of standards

STEP 4


control)

Narrow down target

items using Pareto

diagrams.

(1) Understand the

facts based on the



(2) Analysis using

histograms and time

series graphs


the facts and plan

and implement

measures.

(1) Standardization

and observance of

standards

STEP 3

Cause analysis and

measure planning



Control critical

factors.

Find defect items

from which the

largest effect can

be expected.

(2)Daily control

based on control

charts

STEP 1


activities

STEP 2

Condition/Status

analysis

90

Need for Standardization


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Need for Standardization

To make it possible for anyone to do the same task without overburden,

waste, and inconsistency at any time

Even though rules are standardized, we dont use them in reality.

Standardization would create 100 fools (loss of creativity).

Standardization in our department is impossible, because our work varies for every job.

y Implementable y Easy to observey Easy to understand y Followed by improvement

Familiar stories often heard in relation to standardization

y Standardization that disregarded wishes of people who actually use

the standard (dissociation from real situations at work sites)y Standardization for standardization

Where did these ideas come from?

Conditions for standardization

Purpose of standardization

Standardization is not completed by the establishment of standards, but has meaning in

observance and utilization of these. It is important to keep improving the standards.

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Promoting enforcement of observing basic rules

Building workplace climate of sticking with the basics

y Strictly observe anything specified.y Always follow predetermined procedures when changing rules.

Establish

standards

properly

Extract andsuggest

operations

difficult to

perform or

observe the

rules

Strictlyobserving

standards

(check whether

strictly

observed)

Review

Improvement

Unfailing quality

building

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Five questions to facilitate observing standards

(1) Are rules properly established?

(2) Are the standards easily observed?

(3) Does the system help you tell that standards are observed?

(4) Are you actively trying to find discrepancies?

(5) Do you modify these items?

Are there standards that specify important items properly?

Can operators observe or implement the standards easily?

Is it clearly apparent to anyone whether standards are observed?

Do you walk around the site and actively try to find items difficult to be observed?

Do you quickly respond to (or improve) items difficult to carry out?

No human errors

Establish

ObserveModify

Observe

93

Blunders and standard observance promotion activities


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Blunders and standard observance promotion activities

Blunder True blunder

Work environment where mistakes are

likely to occur

Necessary rules not established

Nonobservance of rules

1. Operation difficult to perform

2. Frequent occurrences of brief stops

and minor trouble

1. Simultaneous multiple operations

2. Suspension during cycle operation

1. Operation in ones own way

2. Regular jigs not used

Promotion activities for

observing standards

True blunders

are limited

94Solve problems by gathering the

f

Solve problems by gathering the

f


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AwareOperator

Leader PerformedNot

performed

Not aware

Aware

Not aware

Performed

Not

performed

0 36 47

33

12

328

0 8

Cases of defects

0 ( 0%)

76 (43%)

88 (50%)

12 ( 7%)

176 (100%)

wisdom of many people!

Stratification of defects according

to the New Johari Window

wisdom of many people!

Stratification of defects according

to the New Johari Window

95


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It is important that leaders teach rules and instruct operators to

observe them, when

(1) Operators do not observe the rules. (36 + 32 = 68 cases)

(2) Operators do not know the rules. (47 + 33 = 80 cases)

Do not overlook operators nonobservance!

(1) Operators do not observe the rules.

To eliminate this situation, it is important to not only teach

them the standards and rules, but also the reasons forobserving them.

y Why do they have to follow this procedure to do this task?y What kind of defects may occur if they do not follow it?

To avoid this,a system to help you

tell that standards are observed is

necessary.

965. STEP 4: Permanent Solution (Maintenance and Control)


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5-2. Daily control using control chart

STEP 4


control)

Narrow down target

items using Pareto

diagrams.

(1) Understand the

facts based on the



(2)Analysis using

histograms and time

series graphs


the facts and plan

and implement

measures.

(1)Standardization

and observance of

standards

STEP 3

Cause analysis and

measure planning



Control critical

factors.

Find defect items

from which the

largest effect can

be expected.

(2) Daily control

based on control

charts

STEP 1


activities

STEP 2

Condition/Status

analysis

97Q7: Control chart


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(Defect) Sub-standard items or

nonconformance

(Irregularity) Something wrong with aprocess (unusual condition);

different from defect or failure

Defect and Irregularity

Using Control ChartUsing Control Chart

Explain the meaning of defect and

irregularity, including the difference

between them.

98

To Maintain Good Conditions in ProcessesTo Maintain Good Conditions in Processes


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Control limitControl limit

Specification limitSpecification limit

Specification limitSpecification limit

Control limitControl limit

AbnormalityAbnormality

Take actions here.

NonconformanceNonconformance Something wrong with a process; different from defect or failureSomething wrong with a process; different from defect or failure

Process

diagnosis

TakeTake

measuresmeasures

before defectsbefore defects

occuroccur

Abnormality inAbnormality in

processprocess

EarlyEarly

restorationrestoration Good conditionsmaintained

[Control chart][Control chart]

(Abnormality example in control chart)(Abnormality example in control chart)

For process maintenance, measures for abnormalities in the processFor process maintenance, measures for abnormalities in the process

are required.are required.

Control charts are a tool for detecting abnormalities in the process. Control charts are a tool for detecting abnormalities in the process.

Point!Point!

Defe

ct

Easy detection of an abnormality

allows actions to be taken to prevent

defect occurrence.

99



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When control charts are likened to a human medical checkupWhen control charts are likened to a human medical checkup

Hospitalization andHospitalization and

major surgery; deathmajor surgery; death

in the worst casein the worst case

Levelofbloodclotinb

rain

Levelofbloodclotinb

rainpp

Sick

Sick

Periodic medical checkupPeriodic medical checkup

Control chartControl chart

==

Health maintenanceHealth maintenance

==

=

Levelofabnormality

Levelofabnormality

pp

Defect

Defect

T (Time)T (Time)

Abnormality detectionAbnormality detection

MedicationMedication

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Irregularity is:

Different from defects, but anunusual state where a certain part is not normal

or something is wrong.

(1) Irregularities listed as control items Relatively easy to detect

(2) Irregularities not listed as control items Must be detected with senses

Operators should report something they feel is unusual as abnormality,likeOh, somethings different, about products or equipment.

Sense Example of sense

Hands

1) The parts surface is usually slick, but is sticky today.

2) Parts can be inserted easier than usual.

3) When held, products feel lighter than usual.

Eyes1) The bolt head is protruding more than usual.

2) The parts surface is less glazed than usual.

Ears1) The sound of the press is louder than usual.

2) The sound heard when parts are inserted is different from the usual sound.

101

(Reference)


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(Reference) Case Example of Detection with Senses

Operation of cutting the gate on synthetic resin parts

The operator engaged in the operation felt the cutting wasLess sticky!

This operator reported the unusual feeling to the supervisor.

It is less

sticky! Different

than usual.

SWS

102

Control ChartQ7: Control chart


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Used to visualize the status of a process to check whether it is stable, and

enables quick detection and prompt action upon abnormality occurrence.

n = 5UCL = 172.0

LCL = 158.0

CL = 165.0

UCL = 25.7

CL = 12.1

Range R(maximum minimum)

Average value x

Upper control limit: UCL

Center line: CL

Lower control limit: LCL

Example of -R control chartx

Date

103

ff

Concept of Control ChartConcept of Control Chart


103/134

Use quality for process control.Use quality for process control.

Quality building in process

Process control by quality

Process Quality performance

y Quality building in process: Standardization

Critical points are selected from the factors responsible for a certainresult and standardized as control points so that products arecontrolled to not deviate from the standard.

y Process control by quality:Quality check, abnormality handling

If any abnormality is found when the variation of dispersed resultsis compared to the standards and targets, the cause must beinvestigated and removed.

Environment Material Machine

Measurement Method Man

Control charts are

a tool for process

control.

104Concept of Control ChartConcept of Control Chart


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Setting control limitsSetting control limits (concept of Shewhart control charts)(concept of Shewhart control charts)

Control limits:s3W from center line 3 sigma rule

W3

(1) Abnormalities are difficult to notice

by only looking at data variation.

Establish an abnormality

determination standard to detect it.

(2) Take measures to prevent recurrence every time an abnormality is

detected to stabilize the dispersion.

Dispersion due toabnormal cause

Dispersion due to uncontrollable cause

Upper control limit (UCL)

Center line(CL)

Lower control limit (LCL)

105

What Are Control Limits, UCL and LCL? (1)What Are Control Limits, UCL and LCL? (1)


105/134

W W W

, ( ), ( )

Process under controlProcess under control

(genuine and inevitable dispersions)(genuine and inevitable dispersions)

Bilaterally symmetrical distributionBilaterally symmetrical distribution

with sloping data dispersionwith sloping data dispersion

+3W-3W Average

99.7% of all data exists in99.7% of all data exists in

the control limit range.the control limit range.

Normal

distribution

Control limitControl limit Control limitControl limit

The process is (basically)The process is (basically)under controlunder control (only(only

genuine and inevitable dispersions occur).genuine and inevitable dispersions occur).

When data isWhen data is beyondbeyond thethe

control limit rangecontrol limit range

When data isWhen data is containedcontained

within the control limit rangewithin the control limit range

The process isThe process is not under controlnot under control (some(some

abnormal cause is assumed to exist).abnormal cause is assumed to exist).

106

Concept of Abnormality Determination fromConcept of Abnormality Determination from


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Concept of Abnormality Determination fromConcept of Abnormality Determination from

Control ChartControl Chartj

99.7% of data exists within

s3W from the average(0.3% outside).

jDots between UCL and LCL are dispersions due touncontrollable causes.

jDots deviated from UCL and LCL are different from those in

the population mean value .

0W

0Q

x

0W

0Q

x

Distribution ofx)(0 xQ

W3s

W

(Conventional distribution)(Use new data for a test.)

Determined as abnormality

107

What Are Control Limits UCL and LCL? (2)What Are Control Limits UCL and LCL? (2)


107/134

With small dispersionWith small dispersion With large dispersionWith large dispersion

Defects hardly occur.Defects hardly occur. Defects occur.Defects occur.

The control limits are inside theThe control limits are inside theproduct specification.product specification. The control limits are outside theThe control limits are outside theproduct specification.product specification.

Upper specification limitUpper specification limit

66WW 11

WW 11

UCL

UCL

LCL

LCL

Lower specification limitLower specification limit

66WW 22

WW 22

UCL

UCL

LCL

LCL

Upper specification limitUpper specification limitLower specification limitLower specification limit

What Are Control Limits, UCL and LCL? (2)What Are Control Limits, UCL and LCL? (2)

108

Wh i l h ?Wh i l h ?

How to Prepare and Use Control ChartsHow to Prepare and Use Control Charts


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What is an control chart?What is an control chart?

j Basic control chart for control chart method

j Arbitrary intervals can be set as a group.

For example, to check the stability of quality characteristics for a

whole day, set one day as a group.

j Samples of4 or5 units (sample size: ) are taken from each group.

j These control the statistic (average and range ).

n

1x 2x 3x 4x

1R 2R 3R 4R

1x 2x 3x 4x

1R 2R 3R 4R

Average

Range

Rx

Rx

Group No. 1

109

Example of Dot Position Calculation for Control Chart

Calculate and plot


109/134

20 groups x 5 samples

GroupSample No.

Averagex RangeR

and R values

for each groupx

Overall mean

110

Supplement 1

Supplement 1: How to Prepare Control Chart


110/134

How to prepare xHow to prepare x--R control chart (for process analysis)R control chart (for process analysis)

Calculate control limits from the data for the process (statistic).

Step 1: Collectdata for20to25consecutive groups.

DatasheetSample size

Number of groups

Characteristic value

of sample

Individual value

5!n

20!k

x

.,, 21 xx

Supplement 1

Date and time GroupNo.

Measurement value

111Supplement 1: How to Prepare Control Chart


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Step2: Calculatetheaverageof

samples foreach group.

Step 3: Calculatetherangeof

samples foreach group.

n

xxxx

n!

.21

x)(minimal-x)(maximalR!

Datasheet

Date and timeGroup

No.

Measurement value Total Average Range

112

Control chart



112/134

g

x

R

5!n

g

x

R

5!n

Horizontal axis: Group No.

Vertical axis: Rx and

Step5: Plot

Control chart

Step 4: Formatthe

controlchart

form.

Rx and

Sample size of group

Plot dots.

Group No. Group No.

113

S



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Step 6: Calculatethecontrollines.

Formula for calculating control lines

x

kxx !

RAx 2

RAx 2

xcontrol chart

Center line (CL)

Upper control limit (UCL)

Lower control limit (LCL)

999.52

20

98.1059

groupsofNumber

ofTotal

!!

!x

x

322.53

56.0577.0999.52

2

!

v!

! RAxUCL

676.52

56.0577.0999.52

2

!

v!

! RAxLCL

A2

is a control chart

coefficient determined by n.

Control line x control chart

Center line (CL)

Upper control limit

(UCL)

Lower control limit

(LCL)

114Supplement 1: How to Prepare Control Chart


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Figure 3: Table of x-R control chart coefficien

Documents

0606-02 Quality Improvement Procedure Rev7-2