1 Six Sigma Achieving Our Objectives 指導教授 : 盧淵源第二組組長 : 蔡孟行組員 : 詹美琴陳文德吳宗啟周永宏簡總益

1

Six Sigma

Achieving Our Objectives指導教授 : 盧淵源

第二組組長 : 蔡孟行組員 : 詹美琴陳文德

吳宗啟周永宏簡總益

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The Focus of Six SigmaThe Focus of Six Sigma Identifying critical aspects of the business with

problems or opportunities for improvement.

Targeting those critical areas and designating improvement efforts as Six Sigma Black Belt projects.

Selecting top people to work on the projects--full time.

Ensuring these people have the time, tools, and resources they need to succeed.

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What Types of Problems Should We Target?What Types of Problems Should We Target?

High Defect Rates Low Yields Excessive Cycle Time Excessive Machine Down Time High Maintenance Costs Bottlenecks

4

What Types of Problems Should We Target?What Types of Problems Should We Target?

High Defect Rates Low Yields Excessive Cycle Time Excessive Machine Down Time High Maintenance Costs Bottlenecks

Non-Conformance

5

Cost Of Poor Quality (COPQ)

Traditional Quality Costs

(tangible)

Engineering change orders

Lost Opportunity

Hidden Factory

Lost salesLate delivery

Long cycle times

Expediting costs

Excess inventory

Additional Costs of Poor Quality

(intangible)

(Difficult or impossible to measure)Lost Customer Loyalty

More Setups

ScrapRework

InspectionWarranty

Rejects

Administration / DispositionConcessions

Average COPQ approximately 15% of Sales

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What is Cost of Poor Quality?What is Cost of Poor Quality?

In addition to the direct costs associated with finding and fixing defects, “Cost of Poor Quality” also includes:

• The hidden cost of failing to meet customer expectations the first time

• The hidden opportunity for increased efficiency

• The hidden potential for higher profits

• The hidden loss in market share

• The hidden increase in production cycle time

• The hidden labor associated with ordering replacement material

• The hidden costs associated with disposing of defects

For most companies today, the cost of poor quality is likely to be 25 % of sales. For Seagate, that’s over $1 billion each year.

In almost every company where the COPQ is unknown, the COPQ exceeds the profit margin.

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The Role of MeasurementThe Role of Measurement

Certainty +

Known +

Belief +

Confidence +

Yield +

Uncertainty

Unknown

Disbelief

Risk

Defect Rate

= 100%

= 100%

= 100%

= 100%

= 100%

If we cannot express what we know in the form of numbers, we really don’t know much about it.

If we don’t know much about it, we cannot control it.

If we cannot control it, we are at the mercy of chance.

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Customer Focus: A Model For SuccessCustomer Focus: A Model For Success

TechnologyTechnology

CapabilityCapability

OrganizationOrganization

PeoplePeople

ProcessesProcesses

• Business survival is dependent upon how well we satisfy our customers.

• Customer satisfaction is a function of quality, price, and delivery.

• Quality, cost, and prompt delivery are dependent upon capability.

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The Customer Supplier InteractionThe Customer Supplier Interaction

Delivery

Price

Quality

CustomerSupplier

NeedNeed

Cycle Time

Cost

Defects

DoDo

We strive for Six Sigma capability on Cycle Time, Cost, and Conformance to meet customer expectations on Delivery, Price, and Quality.

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How Does Six Sigma Make the Difference?How Does Six Sigma Make the Difference?

Vision Philosophy Aggressive goal Metric (standard of measurement) Method Vehicle for:

» Customer focus» Breakthrough improvement» Continuous improvement» People Involvement

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Six Sigma VisionSix Sigma Vision

The Vision of Six Sigma is to delight customers by delivering world-class quality products through the achievement of Six Sigma levels of performance in everything we do.

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Six Sigma PhilosophySix Sigma Philosophy

The philosophy of Six Sigma is to apply a structured, systematic approach to achieve breakthrough improvement across all areas of our business.

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Sigma is a statistical unit of measure that reflects process capability. The sigma scale of measure is perfectly correlated to such characteristics as defects-per-unit, parts-per million defective, and the probability of a failure/error.

2 308,5373 66,8074 6,2105 2336 3.4

PPMPPM

ProcessCapability

ProcessCapability

Defects per Million Opp.

Six Sigma - Aggressive GoalSix Sigma - Aggressive Goal

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Statistical Definition of Six SigmaStatistical Definition of Six Sigma

LSLLSL USLUSL

Process Width

Design Width

- 3st + 3st

TT

.001 ppm > USL.001 ppm < LSL

scale

LSLLSL USLUSLscale

TT

+ 6st

scale

- 6st

Point of Inflection

11

TTUSLUSL

p(d)

p(d)

1 2 3 4 5 6

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This is a 6 Sigma Process

The Standard Deviation

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3 Sigma

6 Sigma

5 Sigma

4 Sigma

93.32 %

99.379 %

99.9767 %

99.99966 %

Historical

Current

Intermediate

Long-Run

Sigma Long-Term Yield Standard

Six Sigma - Performance TargetSix Sigma - Performance Target

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99.99966% Good (6 Sigma)

20,000 lost articles of mail per hour

Unsafe drinking water for almost 15 minutes each day

5,000 incorrect surgical operations per week

Two short or long landings at most major airports each day

200,000 wrong drug prescriptions each year

No electricity for almost seven hours each month

Seven articles lost per hour

One unsafe minute every seven months

1.7 incorrect surgical operations per week

One short or long landing every five years

68 wrong prescriptions per year

One hour without electricity every 34 years

99% Good (2.8 Sigma)

Six Sigma -- Practical MeaningSix Sigma -- Practical Meaning

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Characterize

Optimize

Breakthrough

USL

T

LSL

USL

T

LSL

T

USLLSL

USL’LSL’

The StrategyThe Strategy

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BreakthroughStrategy

Characterization

Phase 1:Measurement

Phase 2:Analysis

Optimization

Phase 3:Improvement

Phase 4:Control

The Breakthrough PhasesThe Breakthrough Phases

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Six Sigma--MethodologySix Sigma--Methodology

Optimized Process

30 - 50

10 - 15

4-8

Key Process InputVariables (KPIVs )

8 - 10 KPIVs

Critical KPIVs

3-6 Key Leverage KPIVs

Inputs VariablesProcess Map

Multi-Vari Studies,Correlations

Screening DOE’s

DOE’s , RSM

C&E Matrix and FMEA

Gage R&R, Capability

T-Test, ANOM, ANOVA

Quality Systems

SPC, Control Plans

Measure

Analyze

Improve

Control

Narrow the scope of input variables --> ID leveraged KPIV’s

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If we are so good at X, why do we constantly test and inspect Y?

Y Dependent Output Effect Symptom Monitor

X1 . . . XN

Independent Input-Process Cause Problem Control

To get results, should we focus our behavior on the Y or X?

f (X)f (X)Y=Y=

Focus on X rather than Y, as done historicallyFocus on X rather than Y, as done historically

The Focus of Six SigmaThe Focus of Six Sigma

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The Breakthrough StrategyThe Breakthrough Strategy

A B C D E F G

1 Select Output Characteristic2 Define Performance Standards3 Validate Measurement System4 Establish Product Capability5 Define Performance Objectives6 Identify Variation Sources7 Screen Potential Causes8 Discover Variable Relationships9 Establish Operating Tolerances

10 Validate Measurement System11 Determine Process Capability12 Implement Process Controls

Application ProjectsBreakthrough Cookbook

Recognize

Define

Y i = f X 1 , ... , XNGoal:

MeasureMeasure

AnalyzeAnalyze

ImproveImprove

ControlControl

ProductCapabilityAnalysis

ProcessCapabilityAnalysis

Focus on the Y’s

Focus on the X’s

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Time

Pe

rfo

rma

nc

e

GOOD

BAD 3 Sigma

6 Sigma

This Drives Breakthrough ImprovementThis Drives Breakthrough Improvement

Six SigmaBreakthrough

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Data is derived from objects, situations, orphenomenon in the form of measurements.

Data is used to classify, describe, improve , orcontrol objects, situations, or phenomenon.

1. We only use experience, not data.2. We collect data, but just look at the numbers.3. We group the data so as to form charts and graphs.4. We use census data with descriptive statistics.5. We use sample data with descriptive statistics.6. We use sample data with inferential statistics.

Levels of Analysis:

What level are you at?What level are you at?

The Foundation of the Six Sigma ToolsThe Foundation of the Six Sigma Tools

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Impact of Variation on CostImpact of Variation on Cost

UpperSpecification

Limit

LowerSpecification

Limit

LossNo Loss

Target

The Traditional View

UpperSpecification

Limit

LowerSpecification

Limit

LossLoss

Target

The Enlightened View

Goal Post

Mentality

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CTX’s(Cost, Quality, Delivery, Satisfaction)Defects Per UnitComplexityDefects Per Million OpportunitiesRolled Throughput YieldRolled Throughput Yield NormalizedSigma ScoreProcess BaselineProcess EntitlementProcess BenchmarkingKPIV’sKPOV’sShift & Drift

Six Sigma MetricsExisting Metrics

YieldScrapRework?????

Leadership Must Ask the Right Questions

What Gets Measured Gets Managed

Six Sigma Metrics

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Six Sigma Metrics - Six Sigma Metrics - DefinitionsDefinitions

CTx’s:» Critical to Customer Satisfaction parameters. Typically, these

include, but are not limited to, cost, quality and delivery

KPOV’s:» Key Process Output Variables. The results of the collective

action of KPIV’s in a process on a product

KPIV’s:» Key Process Input Variables. Those process variables that

directly and/or in conjunction with other KPIV’s, drive a change in an output variable

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CTX’sCTX’s

CT = “Critical To…”

» CTS - Critical To achieving customer Satisfaction. Typically, this includes, but is not limited to, those parameters which are

• CTQ - Critical to Quality• CTD - Critical to Delivery• CTC - Critical to Cost

» Six Sigma Leads you to the “Critical” to Increase the Efficiency of the Improvement Process…..Work on What is Important

CT = “Critical To…”

» CTS - Critical To achieving customer Satisfaction. Typically, this includes, but is not limited to, those parameters which are

• CTQ - Critical to Quality• CTD - Critical to Delivery• CTC - Critical to Cost

» Six Sigma Leads you to the “Critical” to Increase the Efficiency of the Improvement Process…..Work on What is Important

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Key Process VariablesKey Process Variables

KPOV’s: Key Process Output Variables

» The process outputs critical to achieving the CTX’s, • In Golf as an Example

» Distance hit or degrees off line from tee to hole

KPIV’s: Key Process Input Variables» Those process variables that directly or in combination with

other input variables produce a direct effect in a KPOV• Club selection, stance, back swing velocity, club face angle, wrist

action, follow-through

» Six Sigma Leads you to the “Criticals” to Increase the Efficiency of the Improvement Process…..Work on What is Important

KPOV’s: Key Process Output Variables

» The process outputs critical to achieving the CTX’s, • In Golf as an Example

» Distance hit or degrees off line from tee to hole

KPIV’s: Key Process Input Variables» Those process variables that directly or in combination with

other input variables produce a direct effect in a KPOV• Club selection, stance, back swing velocity, club face angle, wrist

action, follow-through

» Six Sigma Leads you to the “Criticals” to Increase the Efficiency of the Improvement Process…..Work on What is Important

30


Process Baseline:» The average, long term defect level of a process when all input

variables in the process are running in an unconstrained fashion

Process Entitlement:» The best case, short term defect level of a process when all

input variables in the process are centered and in control

Process Benchmark:» The defect level of the process deemed by comparison to be

the best process possible

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Process BaselineProcess Baseline

Process Baseline: The average, long term defect level of a process when all input variables in the process are running in an unconstrained fashion

Process Baseline: The average, long term defect level of a process when all input variables in the process are running in an unconstrained fashion

Long-term Baseline

Long-term Baseline

32

Process EntitlementProcess Entitlement

Process Entitlement: The best case, short term defect level of a process when all input variables in the process are centered and in control

Process Entitlement: The best case, short term defect level of a process when all input variables in the process are centered and in control

33

Process BenchmarkProcess Benchmark

Process Benchmark: The defect level of the process deemed by comparison to be the best process possible

Process Benchmark: The defect level of the process deemed by comparison to be the best process possible

Factory AFactory A

Factory BFactory B

Factory CFactory C

34


Shift:» Step function change in the mean or average of a

population, often driven by a special cause or movement in a key process input variable

» Sudden

Drift:» Sustained trend in a mean or average of a population,

often due to a progressive change to an key process input variable

» Gradual

35

Shift & DriftShift & Drift

Shift: Step function change in the mean or average of a population, often driven by a special cause or movement in a key process input variable

Shift: Step function change in the mean or average of a population, often driven by a special cause or movement in a key process input variable

36

Shift & DriftShift & Drift

Drift: Sustained trend in a mean or average of a population, often due to a progressive change to an key process input variable

Drift: Sustained trend in a mean or average of a population, often due to a progressive change to an key process input variable

37


Defects per Unit:» The total number of defects observed on a unit of output

Opportunities:» The number of possibilities for defect creation in a process or

sequence of processes.

DPMO:» Defects per million opportunities

38

Manufacturing Variation Causes A "Hidden Factory"Increased Cost - Lost Capacity

Yield After Inspection or Test

Each defect must be detected, repaired and placed back in the process. Each defect

costs time and money.

ScrapScrap

ReworkReworkHidden Factory

NOTOK

OperationOperationInputsInputs InspectInspect First Time First Time YieldYield

OK

• Wasted Time• Wasted Money• Wasted Resources• Wasted Floor space

90% 90% Customer QualityCustomer Quality

Defects and the Hidden FactoryDefects and the Hidden Factory

39

RTY Versus FTYRTY Versus FTY

66% 66% 90% 90%

... ... why not?why not?

ScrapScrap

90% 90% Customer QualityCustomer Quality

ReworkRework

Hidden FactoryNOTOK

Yield After Inspection or Test

OperationOperationInputsInputs InspectInspect First TimeFirst TimeYieldYield =

OK

ProcessA B C

90%90%YieldYield

90%90%YieldYield

90%90%YieldYield

Rolled Yield 81 % 73 %

90%90%YieldYield

Final TestD

66 %

Using “final test (or first time) yield” ignores the hidden factory. Final test performance is a function of inspection & test not actual defect data.

Rolled-Throughput Yield Classical First-Time Yield

40

Two Types of Defect ModelsTwo Types of Defect Models

Uniform Defect: The same type of defect appearswithin a unit of product; e.g., wrong type of steel.

Random Defect: The defects are intermittent andunrelated; e.g., flaw in surface finish.

Conclusion: The use of a randommodel to describethe occurrence ofdefects is plausible.

Conclusion: The use of a randommodel to describethe occurrence ofdefects is plausible.

Random

Uniform

Universe of DefectsUniverse of Defects

41

Defects per UnitDefects per Unit

Defects per Unit (DPU): Average number of defects per unit producedDefects per Unit (DPU): Average number of defects per unit produced

DPU: 7 Defects / 5 Units = 1.4 Defects per UnitDPU: 7 Defects / 5 Units = 1.4 Defects per Unit

1 2 3 4 51. OD Dimension x2. ID Dimension x3. Flatness4. Roughness x x5. Coercivity6. Carbon Thickness x x7. Lube Thickness8. Glide Height xTotal Defects per Disc 3 1 2 1 0

Disc Number

42

OpportunitiesOpportunities

Opportunities: The number of possibilities for defect creation in any unit of product, process or sequence of processes.


1. OD Dimension2. ID Dimension3. Flatness4. Roughness5. Coercivity6. Carbon Thickness7. Lube Thickness8. Glide Height

8 Opportunities8 Opportunities

43

1. OD Dimension2. ID Dimension3. Flatness4. Roughness5. Coercivity6. Carbon Thickness7. Lube Thickness8. Glide Height

OpportunitiesOpportunities



8 x 5 = 40 Opportunities8 x 5 = 40 Opportunities

DPMO: Defects per Million Opportunities DPMO: Defects per Million Opportunities

44


Classical Yield:» The number of good units divided by the number of units

tested or inspected

Rolled Throughput Yield (RTY):» The probability of a unit going through all process steps with

zero defects. This is used to identify and quantify the “Hidden Factory”

Hidden Factory:» The amount of work above and beyond the requirements

necessary to produce a unit of output

45

Classical YieldClassical Yield

FactoryIn Out

Scrap

Yield =Out

In

The number of good units produced which have no defects, divided by the number of units started, tested or inspected.

The number of good units produced which have no defects, divided by the number of units started, tested or inspected.

46


Factory A100 85

15Scrap

Factory B100 85

Not all Yields are alike!Not all Yields are alike!

47


Factory A100 85

15Scrap

Factory B100 85

15 Scrap

ReworkFactory C: The Hidden Factory


50 35

48


Factory A100 85

15Scrap

Factory B100 85

15 Scrap

ReworkFactory C: The Hidden Factory


50 35

Equal Yields … Unequal Costs

Classical Yield does not correlate to cost, cycle time or inventory levels

Equal Yields … Unequal Costs

Classical Yield does not correlate to cost, cycle time or inventory levels

49

Rolled Throughput YieldRolled Throughput Yield

Process 11000 950

Process 2 930

Process 3 820

Process 4 810

Rework 90

50

20

11010

900

95.0%

47.4%

97.9%

88.2%

98.8%

90.0%

The probability of going through all process steps with zero defects


50


Process 11000 950

Process 2 930

Process 3 820

Process 4 810

Rework 90

50

20

11010

900

95.0%

47.4%

97.9%

88.2%

98.8%



Yrt = (.950)*(.979)*(.882)*(.988) = 81.0%Yrt = (.950)*(.979)*(.882)*(.988) = 81.0%

90.0%

51


Process 11000 950

Process 2 930

Process 3 820

Process 4 810

Rework 90

50

20

11010

900

95.0%

47.4%

97.9%

88.2%

98.8%



Yrt = (.950)*(.979)*(.882)*(.988) = 81.0%

90.0%

Correlates to cost, cycle time, and inventory levels

Correlates to cost, cycle time, and inventory levels

52

Yield ComparisonYield Comparison

Final Classical Yield

- Rolled Throughput Yield

Final Classical Yield

- Rolled Throughput Yield

Hidden FactoryHidden Factory=

53

An Average MeasureAn Average Measure

How do we measure the relative performance of a process?How do we measure the relative performance of a process?

Factory A

Yrt = 80.1%

Factory B

Yrt = 77.3%

Which factory is Better?

Which factory is Better?

54

An Average MeasureAn Average Measure

It’s a TRICK QUESTIONIt’s a TRICK QUESTION

Factory A

Yrt = 80.1%

Factory B

Yrt = 77.3%

95%

94%

96%

98%

92%

90%

89%

Factory B runs higher average

yields at each step

Factory B runs higher average

yields at each step

55


Normalized Throughput Yield:» The yield for a total process averaged over all process steps

Complexity:» A measure of how complicated a process or product is…the

more opportunities for defects a process or product has, the more complex it is.

56

Normalized Thruput YieldNormalized Thruput Yield

Factory A

Yrt = 80.1%

Factory B

Yrt = 77.3%

95%

94%

96%

98%

92%

90%

89%

The yield for a total process averaged over all process steps (Yna)The yield for a total process averaged over all process steps (Yna)

Yna = (Yrt)1/nYna = (Yrt)1/n

Yna = (.801)1/2 = 89.5%Yna = (.801)1/2 = 89.5%

Yna = (.773)1/5 = 95.0%Yna = (.773)1/5 = 95.0%

57

Normalized Throughput YieldNormalized Throughput Yield

Factory A

Yrt = 80.1%

Factory B

Yrt = 77.3%

95%

94%

96%

98%

92%

90%

89%

The yield for a total process averaged over all process steps (Yna)The yield for a total process averaged over all process steps (Yna)

Yna = (Yrt)1/nYna = (Yrt)1/n

Yna = (.801)1/2 = 89.5%Yna = (.801)1/2 = 89.5%

Yna = (.773)1/5 = 95.0%Yna = (.773)1/5 = 95.0%

“n” is the COMPLEXITY. As process steps or the number of features/functions increase

• the opportunities for defects usually increase linearly

• Rolled Thruput Yield decreases

“n” is the COMPLEXITY. As process steps or the number of features/functions increase

• the opportunities for defects usually increase linearly

• Rolled Thruput Yield decreases

58


Sigma Value (Z- Score):» The sigma value is derived from the probability of a defect

in a process and is used to compare performance across

products or processes » z-Score is most accurately determined by using the

equation of z = e(-DPU)

59

Z Score» The universal metric used to

compare performance across products or processes

» Derived from the probability of producing a defect

• Based upon Normalized Throughput Yield for complex processes

• Related to comparable Sigma value of an equivalent normal distribution

Z Score» The universal metric used to

compare performance across products or processes

» Derived from the probability of producing a defect

• Based upon Normalized Throughput Yield for complex processes

• Related to comparable Sigma value of an equivalent normal distribution

Z ScoreZ Score

scale scale 3

Normalized Thruput

Yield

Normalized Thruput

Yield

DefectiveDefective

Z

60

Conversion to Std Normal» i.e ~N(0,1)

Conversion to Std Normal» i.e ~N(0,1)

Z ScoreZ Score

3Z

~N(20,10)

~N(0,1)

61

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Sweet FruitSweet Fruit Design for Manufacturability

Bulk of FruitBulk of FruitProcess Characterization and Optimization

Low Hanging FruitLow Hanging FruitSeven Basic Tools

Ground FruitGround FruitLogic and Intuition

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

We don't know what we don't know

We can't act on what we don't know

We won't know until we search

We won't search for what we don't question

We don't question what we don't measure

Hence, We just don't know

3 Wall, Beat Up Suppliers3 Wall, Beat Up Suppliers

4 Wall, Improve Processes4 Wall, Improve Processes

5 Wall, Improve Designs5 Wall, Improve Designs

© 1994 Dr. Mikel J. Harry - V4.0

Harvesting the Fruit of Six SigmaHarvesting the Fruit of Six Sigma

62

Potential Project Deliverables: Measure PhasePotential Project Deliverables: Measure Phase Project definition

» Problem description

» Project Metrics Project Exploration

» Process Flow Diagram

» C&E Matrix, Process FMEA, Fishbone Diagrams

» Data Collection System Measurement System Analysis

» Attribute/Variable Gage Studies Capability Assessment (on each Y)

» Cp, Cpk, Pp, Ppk, level, DPU, RTY Graphical & Statistical Tools Project Summary

» Conclusions

» Issues and Barriers

» Next Steps Completed local Project Review

63

企業經營循環企業經營循環企業之生存在於不斷地追求成長。成長主要決定於顧客滿意度。顧客滿意取決於交期、品質及價格。交期、品質及價格是由製程能力所掌握。製程能力為變異數所影響。製程變異數因不良率、成本與時程增加而變差。為了消除變異數，我們需要運用正確的知識。想要運用正確的知識，我們必須先學會它。唯有不斷地學習與運用新知識，企業才能永續經營。

成長即是硬道理

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Documents

1 Six Sigma Achieving Our Objectives 指導教授 : 盧淵源 第二組 組長 : 蔡孟行 組員 : 詹美琴 陳文德 吳宗啟 周永宏 簡總益

1 Six Sigma Achieving Our Objectives 指導教授 : 盧淵源第二組組長 : 蔡孟行組員 : 詹美琴陳文德吳宗啟周永宏簡總益