Six Sigma Overview[1]

8/8/2019 Six Sigma Overview[1]

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Six Sigma - Overview

M e a s u r e

Def ine

A n

a l y z e

C o n t r o

l

I m p r o v e

BreakthroughMethodology

Y=f(X)

Presented by:

Ryan M. Ismail, M.Eng, MBA

Therapeutic Area Program Manager

Merck Research Labs



2

What is Six Sigma?

vA structured, methodical approach to process /product improvement and design robustness

v

vAll decisions are based on facts and datav

vA powerful “Tool Box” is used to identify andeliminate waste through the reduction of underlying process variability

v

v It is applicable in both Manufacturing andTransactional (Business) processes

v

v It is implemented through highly trained,motivated individuals called “Black Belts”and “Green Belts” from all functions

•



Six Elements of Six Sigma

1.Genuine focus on the customer

•The Voice of the Customer (VOC) is thefoundation of the methodology

2.Data- and fact-driven management •Use data to prove that solutions work and

gains are sustained

3.Process focus•Improving processes ensures competitive

advantage – delivering real value tocustomers

From The Six Sigma Way, by Pande, et al



4.Proactive management

•Set/track goals, establish priorities, reward fire prevention

6.Boundaryless collaboration•Customer-centric; processes transcend

departmental silos

8.Drive for perfection, tolerate failure•New ideas/approaches involve risk; overcome

fear of mistakes

Six Elements of Six Sigma



Determi e

custome need o besatisfied

Identif the

busines rocess

hatfulfill

theneed

tudy the,rocess dentify ariation

drivers

Optimi e theproces

s

nsure hat

ustomer eed is et and ix is

sustained

The Six Sigma

Approach

Customer Focus Throughout Process



What is the Definition of What is the Definition of

Six Sigma? Six Sigma?



7

Area Under Normal Curve

68% OF DATA FALL WITHIN 1 STANDARDDEVIATION OF THE MEAN



8


95% OF DATA FALL WITHIN 2 STANDARDDEVIATIONS OF THE MEAN



9


99.7% OF DATA FALL WITHIN 3 STANDARDDEVIATIONS OF THE MEAN



10

LSL

3 Sigma Process

PROCESS 6 σ

LSL USL

PERFORMANCE 6 σ

Cp = 1.00

Process

Performance



11

6 Sigma Process

LSL Cp = 2.00

PROCESS 6 σ

LSL USL

PERFORMANCE 12 σ

Cp = 2.00

Process

Performance



12

Process Capability

LCL UCL y

USLLSL

6s

12s

Process TolerancesPerformance (VOC) Tolerances

2

6

=−

=

s

LSLUSLC

p

Latitude

Process

Performance

The Tools DevelopThe Tools Develop

Latitude in ProcessLatitude in Process

CapabilityCapability



13

Major Sources of Variability

InsufficientProcess Capability

SkillsandBehaviors

Poor Design

Measurement SystemUnstable Partsand Material



Average AverageDelivery Delivery Cycle Cycle

Customer’s Expectations: 8 Day Order to Delivery Cycle

20 1715 230 510 125 4

16 Day 8 Day

Existing Process After ConventionalDelivery Cycle Process Improvement(days) Cycle (days)

2 5 8 12 17

Customer Want Date

Days Late(+9)

Days Early(-6)

15 Day Span

We are pleased with our 50% cycle improvement –however, our customers didn’t feel a thing!

7

9987

8 Day AverageDelivery Cycle

Customer Want Date

Days Early (-1)

2 7 8 9 17

2 Day Span

Days Late (+1)

6 Process ImprovementDelivery Cycle (Days)

By attacking variation and reducing span, wetruly met our customer’s expectation for cycle

time improvement!

Averages vs. Variation



15

•Effectiveness( ’ ):ustomer s view eeting customer requirements and

‘ ’reating delightØ ,us to m e r s f ee l V A R I A T I O N n o t a ve ra ge s

Ø ,i n b y p r e ve nt i n g f i re s no t

ig h t i ng t h e m

•Efficiency ( ):anagement view

,roviding streamlined processes

inimizing internal costs

ustomer & Management Views



16

Sigma or the Standard Deviation of the process distribution allows us todetermine and communicate the capability of the process.

The “Sigma Level” of a an in-control process is simply the number of standard deviationsof the process distribution that consume 1/2 the allowed tolerance band if the process were

centered around the target value.

The term “SIX SIGMA”

Target Output Acceptance

Limit

Acceptance

Limit

6 Sigma Performance3.4 defects / million

“World Class”

3 Sigma Performance66,807 defects / million“Historical Standard”

2 Sigma Performance308,537 defects / million“Major League Waste”

4 Sigma Performance6,210 defects / million“Current Standard”



What is a Six SigmaWhat is a Six Sigma

Project? Project?



18

"All improvement takes place

project by project and inno other way."

Dr. Joseph M. Juran

SIX SIGMA PROJECTS



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The overall goal of the Six Sigma Initiative

is to significantly improve customer

perceived value and company’s profitability.

Projects that fit that criteria are legitimate

projects. ØSix Sigma projects should be linked to the

highest levels of strategy and be in direct

support of specific WW business and core

process objectives.

Ø

ØSix Sigma projects should be definable and

manageable in scope with high probability of

completion in four to six months, or less.

Ø

ØA Six Sigma project should of fer a significant

opportunity for reduction in Cost of Poor Quality

(COPQ), in addition to improving such things as

What Is a Six Sigma Project?



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What Is a Six Sigma Project?

• There are five phases of Six Sigmamethodology:

•

1. Define (D)

2. Measure (M)3. Analyze (A)

4. Improve (I)

5. Control (C)

Together it is called DMAIC



21

Six Sigma Road Map – DMAIC

D e f i n e Pick the Right Projects

Ø Identify Potential ProjectsØ Evaluate ProjectsØ Prepare Problem and Mission StatementØ Goals and Objectives

M e

a s u r e

Characterize the Process and Measure the

PerformanceØ Cost of Poor Quality (COPQ)Ø Map the ProcessØ Define the Key Process Input Variables (KPIV)Ø Define the Key Process Output Variables (KPOV)

Ø Measurement System Analysis (MSA) to validate themeasurement system

Ø Identify Potential Failure Modes and Effects (FMEA)Ø Measure baseline performanceØ Defect ratesØ Process capability

A n a l y z e

Identify Critical Process VariablesØ Develop hypotheses for text – potential X’sØ Plan for Data CollectionØ Analyze DataØ Confirm Determinants of Process Performance

P r o c e s s C h

a r a c t e r i z a t i o n

I m p r o v e

Establish Prediction Model and Optimize

the ProcessØ Plan Design of ExperimentsØ Screen to Identify Critical Few CausesØ Establish Cause-Effect RelationshipØ Optimize Process

C o n t r o l Hold the Gains

Ø Design ControlsØ Document Improved ProcessØ Establish final control planØ Implement ControlsØ Monitor Effectiveness of Controls

P r o c e s s O p t i m i z a t i o n

H o l

d T h e

G a i n s

The Six Sigma Roadmap

A Structured Approach:

DMAIC

BreakthroughBreakthrough

SIX SIGMSIX SIGM

M e a s u r e

Def ine

A n a l y

z e

C o n t r o l

I m p r o v e

Breakthrough Breakthrough

Methodology Methodology

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



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What Is a Six Sigma Model?

• Taken together, they are referred to as the DMAICprocess of quality improvement.• The Six-Sigma methodology is based on simple

yet powerful model,

y=f(x)y=f(x)•

• where y represents the key process outputs• x represents key process inputs that strongly

effect the output

• function, “f” represents the relationship betweenthe inputs and outputs.



23

DEFINE

MEASURE

ANALYZE

IMPROVE

CONTROL

•Problem Statement•Mission Statement•Project Team•Initial COPQ

•Process Mapping•Cause and Effect Diagram•Cause and Effect Matrix•Process FMEA•List of Theories to Test•MSA•Data Collection Plan•Baseline Data

•Passive Data Collection:•Run Charts•Pareto Charts•Histograms and

Dotcharts•Box plots•Defect Concentration

Plots•Scatterplots and

Marginal Plots-

•

•Active Experimentation (DOE):•Factorial Designs•Factor Pareto

Charts•Main Effects

Charts•Interaction Charts

-

•Active Experimentation (DOE):•Response Surface

Designs•Method of

Steepest Ascent•Optimization

•Mistake Proofing•5s / TPM / PM•Validation (IQ, OQ, PQ)•Updated FMEA•Updated Process Map•Control Plan•SOP and Training•Statistical Process Control•Project Impact•Documented Savings

Six Sigma Toolbox



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M e a s u r e

Def ine

A n a l y

z e

C o n t r o l

I m p r o v e


Y=f(X)

•Purpose: To accurately describe theproblem, define project success, and tocommit the resources necessary to solvethe problem.

•

•Deliverables:•Problem statement

•Mission statement and project scope

•Project team•Approved COPQ

•Project plan and timeline

Phase 1: DEFINE



25

DEFINE

MEASUR

ANALYZ

IMPROV

CONTRO

•Problem Statement•Mission Statement

•Project Team•Initial COPQ

Six Sigma Toolbox – Define



26

Project Assignment / Selection

Definition of Six Sigma Projects•

•Definable and manageable•

•High probability of completion in less than six

months•

•Significant opportunity for reduction in Costof Poor Quality (COPQ)

•

•

Improve customer satisfaction, capacity, andtop-line growth

Prepare a Problem / Mission



27

Prepare a Problem / MissionStatement

•

Define the scope of your project in the Problem /mission statement•

•Example: Effective Problem Statement•Our company’s procedure for shipping replacement parts

takes ten days longer on average than our major

competitors take.•

•This statement is:•Specific: It names a particular process and states the

problem.

•Observable: Evidence of the problem can be obtained frominternal reports and customer feedback.

•Measurable: Shipping time is measured in days.

•Manageable: The problem is limited to one type of shippingprocedure.



28

Cost Of Poor Quality (COPQ)

Waste

Testing Costs

Rework

Customer Returns

Inspection CostsRejects

Recalls

Late Paperwork

Customer Allowances

Premium Freight CostsPricing or Billing Errors

Excessive FieldServices Expenses

Incorrectly CompletedSales Order

Lack of Follow-upon Current Programs

ExcessiveEmployee Turnover

Planning Delays

Development Costof Failed Product

Expediting Costs

Excess Inventory

ExcessiveSystem CostsOverdue Receivables

ComplaintHandling

Unused Capacity

Time with DissatisfiedCustomer

Excessive Overtime

Lost Sales

Theory of:“Tip of an Iceberg”

•

•A few costs are

easy to see likethe part above thewaterline

•

•

Many more costsare hidden belowthe water.

•



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Define COPQ

• COPQ are the costs that would disappear if everytask was always performed without deficiency (Source: Juran Institute Inc.)

•

• COPQ are the cost of failures including costs of

insuring quality in manufacturing, delivering,and servicing of the products.

•

• The three major COPQ categories:• Appraisal / Inspection Cost

• Internal Failure Costs• External Failure Costs



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•Purpose: •To characterize the process as it currently existsand to focus

the project by narrowing the range of potential causes. Toevaluate current measurement systems and ensuremeasurement capability. Define and develop a datacollection strategy.

•Deliverables:•Process Map

•Cause and Effect Diagram

•CE-Matrix of prioritized KPIV’s

•Process FMEA

•Data collection plan•Measurement system analyses (MSA)

•Baseline measurement data

•Process Capability

•List of Theories to test

•First draft of preliminary control plan

Phase 2: MEASURE

M e a s u r e

Define

A n a l y

z e

C o n t r o l

I m p r o v e


Y=f(X)





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Data Collection Plan

• Purpose: Generate data to learn about• The Process

• The Measurement System (Note: The measurementsystem must be suitable for the task at hand)

•

• Steps: • Develop forms/spreadsheets necessary to collect the data.

• Record the process inputs

• Measure and record the output (i.e; frequency or days)

• Present the data (graphically) and analyze the output (Why isthere so much variation?)



33

Define and Measure

Measurement Systems Analysis(MSA)

•

•Understanding how much variability comes from your gage or measuring device.

•

•Reducing the variation, if possible, so that variation

observed is from the process.



34

Measurement System

Examples•

• Weights Check (weight)

• Part tolerance (distance)

• UV measurement (absorbance)• Analytical tests (concentration)

• Torque testing (force)

• Visual inspection (labels, color, etc.)

• Functional performance (activity, days, etc.)• Others? ____________________

Where does Total System



35

Where does Total System

Variation Occur?

System Variation

Part to Part (Actual)Variation

Long TermProcessVariation

Short TermProcessVariation

Measurement VariationMeasurementVariation

Due toOperator Issues

Due to Gage

Lack of

Reproducibility

Lack of

Repeatability

Gage Bias

Lack of Stability

Non-Linearity





37

ACCURACY

•Biasis the difference between the observed averagemeasurement value and the “actual” or “true” value.Bias is a measure of “lack of accuracy”.

•It is typically the most common and easiest problemto fix.

Bad Accuracy,

Good Precision

TRUE

VALUE



38

Accurate but not

PreciseTRUEVALUE

PRECISION

•PRECISION is the ability to replicate measurements time

after time. LACK OF PRECISION implies VARIABILITY.

•All measurement systems should be repeatable, bothwithin and between evaluators.



39

STABILITY

• All instruments need to be periodically re-calibrated because ACCURACYDETERIORATES over time.

• A lack of stability implies a “creeping bias” over time. Need to run a standard on a regular basis

to ensure there is no degradation or bias in themeasurements.

•

May 2001

July 2001

Sept2001



40

•Purpose:•Through data analysis, narrowing down the trivial many

process variables (X's) to the significant few KeyProcess Input Variables (KPIVs / Vital X's).

•

•Deliverables:•List of Key Process Input Variables (KPIVs)

•Updated Preliminary Control Plan

•Updated list of Theories to Test

•

Phase 3: ANALYZE

M e a s u r e

Def ine

A n a l y

z e

C o n t r o l

I m p r o v e


Y=f(X)



41

DEFINE

MEASURE

ANALYZE

IMPROVE

CONTROL

Passive Data Collection:•Run Charts

•Pareto Charts•Histograms and Dotcharts•Box plots•Defect Concentration Plots

•Scatterplots and Marginal

Plots-

Active Experimentation (DOE):•Factorial Designs

•Factor Pareto Charts•Main Effects Charts•Interaction Charts

-

Six Sigma Toolbox - Analyze

Not all inputs are important



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Not all inputs are important…….Only a few will drive the process

Y = f ( X1, X5, X9 )

Y, X1, ……..,

X15

C

h a r a c

t e r i z a

t i o n

O p

t i m

i z a

t i o n

Y’sX’s

Unimportant X’sremoved

Process Dynamics Unpredictable

Important X’s (KPIVs)discovered and

controlled



43

How to determine the KPIV’s

Finding theFinding the

KPIV'sKPIV's

Passive DataPassive Data

Acquisition Acquisition

Active Active

ExperimentationExperimentation•From the Batch History Record•From Machine logs

•Historic data

•From lab experiments•From modification of business

process or manufacturingconditions



44

Analyze Phase

Finding KPIV’s through

•Passive Data Acquisition



45

08/1608/1108/10

0.06

0.05

0.04

0.03

0.02

0.01

0.00

Date/Time

P e r c e n t a g e R e j e c t s

Passive Data Analysis

O t h e

r s B A -

B C - D C A D

33710162839

2.82.86.69.415.126.436.8

100.097.294.387.778.363.236.8

100

50

0

100

80

60

40

20

0

Defect

Count

PercentCum %

P e r c e n t

C o u n t

Pareto Chart for Packaging Sh

170160150140130

Clare Dyad Cleanliness

Clean

Dirty

g o o d

b a d

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

lot

C T c o n c e n t r a t i o n

Boxplots of CT conce by lot

(means are indicated by solid circles)



46

Analyze Phase

Finding KPIV’s through•

•Active Data Acquisition•One Factor at a time

•Design of Experiment

•Fractional Factorial

Design



47

Active Data Acquisition

2.0

4.5

300300220220

8

7

6

5

4

3

2

1

Barrel Tempe

Injection Sp

M e a n

Interaction Plot (data means) for OD

3210

A

B

AB

E

BC

AE

DE

C

AD

BD

AC

CD

BE

D

CE

Pareto Chart of the Standardized Effects

(response is % C&S, Alpha = .10)

A: Hold TimB: MandrelC: Mold TemD: ForceE: Coil Pos

Barrel TempeInjection Sp

3 0 0

2 2 0

4. 5

2. 0

5.5

4.5

3.5

2.5

1.5

O D

Main Effects Plot (data means) for OD

1 2 3 4

1 2 1 2 1 2 1 2

0.248

0.249

0.250

0.251

0.252

Cavity

D i a m e t e r

Bottom

Middle

Top

Multi-Vari Chart for Diameter by Location - CavityPart

Location

Ph 4 IMPROVE



48

•

Purpose:•To optimize the process by determining the relationship

between the Key Process Input Variables (KPIV's) andthe Key Process Output Variables (KPOV's).

•

•Deliverables:

•Determine the f in Y=f(X)

•Updated preliminary control plan

•

Phase 4: IMPROVE

M e a s u r e

Def ine

A n a l y

z e

C o n t r o l

I m p r o v e


Y=f(X)



49

DEFINE

MEASURE

ANALYZE

IMPROVE

CONTROL

Active Experimentation (DOE):

•Response SurfaceDesigns

•Method of Steepest

Ascent•Optimization

Six Sigma Toolbox -

Improve

Ph 5 CONTROL



50

•Purpose:•To maintain the gains through control of the Key Process

Input Variables (KPIV's) and error detection-correctionmethods.

•Deliverables:•Error Proofing / Poka-Yoke

•Safety Issues / OSHA

•5S / TPM / Updated PM

•Validation (IQ, OQ, PQ)

•Updated FMEA

•Updated Process Map (Improved Process)

•Training

•Control Plan

•SPC

•Project Impact & Summary (e.g. updated COPQ anddocumented process improvement)

M e a s u r e

Def ine

A n a l y

z e

C o n t r o l

I m p r o v e


Y=f(X)

Phase 5: CONTROL

Si Si T lb C t l



51

DEFINE

MEASURE

ANALYZE

IMPROVE

CONTROL

•Mistake Proofing•5s / TPM / PM•Validation (IQ, OQ, PQ)•Updated FMEA

•Updated Process Map

•Control Plan

•SOP and Training

•Statistical Process Control

•Project Impact•Documented Savings

Six Sigma Toolbox - Control



52

Improve and Control

Poka-yoke•A Poka-Yoke device is mechanism that

either prevents a mistake from occurringor makes a mistake obvious at a glance

•

•‘Mistake-Proofing’ is the Anglicantranslation of this principle

•

•

Several basic principles are consistentlyused in Poka-Yoke efforts



53

Poka-yoke Device Categories

• Prevention• Engineer the process or product so that it is

impossible to make the mistake in the first place.

• 3 1/2” floppy disk example.

• Prevention devices eliminate the need to detect or correct a mistake

• Detection• A detection device cues the operator when a

mistake has been made. This enables a quick fix.

• Your car has some of these: door ajar, beeps when

key in ignition and door open, seat belt notfastened.

• Clutch in, or in park before it will start are examplesof prevention devices.

P k k D i



54

Poka-yoke Device

•

• Simple and cheap

•

• Part of the process

•

• Placed close to where the mistakes occur

Good Poka-yoke Device Characteristics:

E l f Mi t k P fi



55

Example of Mistake Proofing

Fueling area of car has three mistake-proofing devices:

1. Filling pipe insert keeps larger, leaded-fuelnozzle from being inserted

2. Gas cap tether does not allow the motorist todrive off without the cap

3. Gas cap is fitted with ratchet to signal propertightness and prevent over-tightening.

Every Day Examples used from John Grout. Go to his website atmistakeproofing.com for more examples.

E l f Mi t k P fi



56

Example of Mistake Proofing

The window in the envelopeis not only a labor savingdevice. It prevents thecontents of an envelopeintended for one personbeing inserted in anenvelope address to another.

Every Day Examples used from John Grout. Go to his website atmistakeproofing.com for more examples.



57

Hungry Jack syrup has a small window near the bottom of thecontainer that changes from black to clear when heated

revealing the word HOT. This signals that the syrup is warmand ready to serve.

Examples of Mistake

Proofing

Total Productive Maintenance



58

Total Productive Maintenance

• TPM is a process focused, team-based effort thatwill build quality into manufacturing or serviceprocess steps and by doing so will improve theoverall effectiveness.

• TPM . . .• Focuses on entire life cycle

• Coordinates all processes in a department

• Involves all associates

• Is implemented through teams

• Maximizes equipment/process effectiveness

Statistical Process Control



59

3x

σ 3x

σ

99.73% of X valueswill fall inside these limits

X

Statistical Process Control (SPC)

Upper control limit

Lower control limit

X

3x

σ

Six Sigma Quality Costs



60

Six Sigma Quality Costs

• The Benefits of higher quality are obvious.However, many believe it costs a lot to

achieve this.

•

• With Six Sigma, it can actually cost less.Six Sigma looks at attacking all the“hidden” components contributing tothe Cost of Quality.

•

(General Electric Company)



61

Any Questions, Please?

?

Project Management



Humor

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