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6 s. 6-Sigma Program & Concepts Overview. Control. Project Phases:. Presenters: P. Pfaff H. Myrie K. Barker. Improve. Analyze. Measure. 6 s. Meet Larry. Larry is a golfer. His play is, shall we say, erratic? He wants to play more consistently. 6-Sigma Example - Measure Phase.

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6 sigma program concepts overview

6s

6-Sigma Program& Concepts Overview

Control

Project Phases:

Presenters:

P. Pfaff

H. Myrie

K. Barker

Improve

Analyze

Measure


6 sigma program concepts overview

6s

Meet Larry.

Larry is a golfer.

His play is,

shall we say,

erratic?

He wants to play

more consistently.


6 sigma example measure phase

6-Sigma Example - Measure Phase

Larry’s Golf Game

  • What is the output of Larry’s game?

    Specification: Larry wants to shoot between 80 and 100 this season, with a target average score of 90.


6 sigma example measure phase1

6-Sigma Example - Measure Phase

Cpk = -0.05 !!!

  • What is his process

    capability?

  • How does this relate to his ZLT (Long Term) and ZST (Short Term)?

    • ZLT = (Cpk x 3) = -0.15 s Process

    • ZST = (Cp x 3) = 5.64 s Process*

      *(Best Process Cp - Sources of Variation Eliminated)

  • Goal: Reduce the variation and move the average in Larry’s game.

Cp = 1.88


6 sigma example measure phase2

6-Sigma Example - Measure Phase

Larry is Here

3.0

  • How do we determine the opportunity for improvement for Larry’s Game?

Improve

Control

Control (Zshift)

1.5

Goal

ZST = 5.64

ZLT = -0.15

ZSHIFT = 5.79

(ZSHIFT = ZST - ZLT)

Improve

Skills

0

0

3.0

6.0

Technology/Skills (ZST)

  • This means:

    • Just by improving his control, Larry can achieve a 5.5 sigma game.

    • If he wants a 6 sigma game he will also have to improve his skills.


6 sigma example measure phase3

Larry’s Golf Game

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6-Sigma Example - Measure Phase

Let’s analyze his game by breaking down his score.

Where is the biggest opportunity in his overall game?

He takes more shots

in his short game (62.3%).


6 sigma example measure phase4

Larry’s Short Game

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6-Sigma Example - Measure Phase

Let’s continue analyzing his game by breaking it down further.

Where is the biggest opportunity in his short game?

He takes more shots

in his putting game (66.9%).


6 sigma example measure phase5

6-Sigma Example - Measure Phase

Cause & Effect Diagram - Larry’s Putting Game

Measurement

Material

Larry

Putting Score

Environment

Methods

Machine

  • What are the causes of variation in Larry’s Putting Game?


6 sigma program concepts overview1

6s

6-Sigma Program& Concepts Overview

Control

Project Phases:

Presenters:

P. Pfaff

H. Myrie

K. Barker

Improve

Analyze

Measure


6 sigma example analyze phase

6-Sigma Example - Analyze Phase

Cause & Effect Diagram - Larry’s Putting Game

Measurement

Material

Larry

>Cheat at Counting

> Can’t Remember

> Pencil has an eraser

> Grass Type

>Number of Drinks

> Eye Glasses Prescription Updated

> Properly Rested

Putting Score

> Golf Course

> Green Condition

> Time of Day

> Weather

> Playing Partners

> Betting of Hole

> Putting Style

- Stance

-Grip

- Swing

> Reading the Green

>Putter Type

> Ball Type

> Shoes

> Glove

Environment

Methods

Machine

  • What are the causes of variation in Larry’s Putting Game?


6 sigma example analyze phase1

6-Sigma Example - Analyze Phase

Is putting really a significant source of variation in the overall golf score?

ScatterPlot/Fitted Line Regression

1

3

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Yes!!!

1

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=

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1

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+

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X

1

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R-Squared = 0.906

9

0

The R-Squared value says

that 90.6% of the variation

in the Overall Score is

directly related to the

putting game.

3

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5

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P

u

t

t

s


6 sigma example analyze phase2

6-Sigma Example - Analyze Phase

Let’s figure out what is causing the variation in his putting game. . .

What did Larry do

differently during

this time frame?


6 sigma example analyze phase3

6-Sigma Example - Analyze Phase

If he gave up drinking, does the number of drinks directly affect his putting?

ScatterPlot/Fitted Line Regression

5

4

Yes!!!

s

4

4

t

t

u

P

Y

=

3

6

.

2

5

+

2

X

R-Squared = 0.872

3

4

The R-Squared value says

that 87.2% of the variation

in Putting is directly related

to the number of drinks he had.

0

1

2

3

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5

6

D

r

i

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s


6 sigma example analyze phase4

6-Sigma Example - Analyze Phase

Conclusions

  • Larry should putt, or drink, but not both!

  • If Larry gives up drinking while golfing he will have addressed 87.2% of the variation in his putting game.

  • By bringing his putting game under control he will achieve a 5-sigma game.

  • To achieve a 6-sigma game we will have to do further investigations.


6 sigma program concepts overview2

6s

6-Sigma Program& Concepts Overview

Control

Project Phases:

Presenters:

P. Pfaff

H. Myrie

K. Barker

Improve

Analyze

Measure


6 sigma example improve phase

6-Sigma Example - Improve Phase

Cause & Effect Diagram - Larry’s Putting Game

Measurement

Material

Larry

>Cheat at Counting

> Can’t Remember

> Pencil has an eraser

> Grass Type

>NUMBER OF DRINKS

> Eye Glasses Prescription Updated

> Properly Rested

Putting Score

> Golf Course

> Green Condition

> Time of Day

> Weather

> Playing Partners

> Betting of Hole

> Putting Style

- Stance

-Grip

- Swing

> Reading the Green

>Putter Type

> Ball Type

> Shoes

> Glove

Environment

Methods

Machine

  • Last time we determined drinks was a significant X.

  • What other sources also drive the Putting Score?


6 sigma example improve phase1

6-Sigma Example - Improve Phase

In order to improve his game above the 5-sigma level he has to improve his skills.

  • What skills does he need to improve?

    • After talking with Larry and the Golf Pro we

    • have concluded that there are three areas

    • that would most likely improve his putting

    • game. They are the putter type, stance

    • and grip during putting.

    • The Golf Pro wants to sell him the latest

    • high tech/high $$ putter (Big Bubba).

  • What does Larry have to do?


6 sigma example improve phase2

6-Sigma Example - Improve Phase

  • Larry was not sure, so he consulted with his trustworthy Black Belt, who uses data to help make decisions.

  • They then set up a Designed Set of Experiments with the following settings:


6 sigma example improve phase3

6-Sigma Example - Improve Phase

This is the Experiment Matrix that they decided to run!

This is a 23 DOE, which has eight conditions to test.


6 sigma example improve phase4

6-Sigma Example - Improve Phase

This is the Experiment Matrix after we randomized

the order that they will run!

Randomization is done to detect

the effect of other non-controlled variables.


6 sigma example improve phase5

6-Sigma Example - Improve Phase

We ran the experiments and these are the results.

p = .003

Interaction Plots for Putting Score

Main Effects Plot for Putting Score

1

1

-

1

1

1

40

38

36

34

32

Open Stance

Open Stance

p = .026

p = .873

p = .037

Stance

-

1

-

1

Putting Score

Close Stance

40

38

36

34

32

Close Stance

-

1

40

38

36

34

32

-

1

1

Old Reliable

1

Putter

Type

Big Bubba

Old Reliable

-

1

1

Big Bubba

1

Open

Interlock

Stance

Putter

Type

Open

Open

Grip

Grip

Close

Interlock

Big Bubba

Old Reliable

The Closed Stance with the Interlocked Grip gives Larry the Lowest Score!

(Verified statistically.)

Stance and Grip are significant factors.

(Verified statistically.)


6 sigma example improve phase6

6-Sigma Example - Improve Phase

DOE Conclusions

  • The high $$ putter made no difference!!

  • The interaction between Closed Stance and Interlocked Grip gives Larry the lowest score!

    • Just using the interlocked grip or closed stance by themselves will not achieve the lowest putting score.


6 sigma program concepts overview

6-Sigma Example - Improve Phase

So, What is Larry’s Improvement Plan?

  • Give up drinking . . . on the golf course!!

  • Continue to use “Old Reliable” putter, since the DOE showed that the “Big Bubba” made no difference.

  • Always use an interlocking grip and a closed stance when he putts.

  • Implement these improvements and collect some data! Play some golf!


6 sigma program concepts overview

Improve

Measure

6-Sigma Example - Improve Phase

Has Larry

improved?

USL

LSL

Yes! How much?

From Measure:

Zlt = -0.15DPMO = 820,000

Zst = 5.64

From Improve:

Zlt = 4.23DPMO = 12


6 sigma program concepts overview3

6s

6-Sigma Program& Concepts Overview

Control

Project Phases:

Presenters:

P. Pfaff

H. Myrie

K. Barker

Improve

Analyze

Measure


6 sigma example improve review

6-Sigma Example - Improve Review

Remember Larry’s Improve “Plan” . . .

  • Give up drinking . . . on the golf course!!

  • Use “Old Reliable” putter!!

  • Always use an interlocking grip and a closed stance when he putts!!

. . . and the Results

From Measure:

Zlt = -0.15DPMO = 820,000

Zst = 5.64

From Improve:

Zlt = 4.23DPMO = 12


6 sigma program concepts overview

6-Sigma Example - Control Phase

Larry Needs a Control Plan

  • What’s a good plan to insure that Larry sustains the improvements he has made?

  • Are there risks that could cause Larry to lose his improvement?

  • If so, how should Larry address those risks associated with changing his golf game?

  • Can Larry come up with a realistic drinking objective and maintain his improvement?


6 sigma program concepts overview

6-Sigma Example - Control Phase

So, What is Larry’s Control Plan?

Mistake - proofing

  • Alternate drinking plan

    • Leave wallet in car - only take enough $ for 1 beer

    • Lock and key on partners’ beer coolers

    • Unlimited supply of “Near Beer” in Red Dog bottles (shhh - Don’t tell Larry)

  • Put a Label on “Old Reliable” putter where he always sees it when putting

    • “Interlock grip, close stance”


6 sigma example control phase

6-Sigma Example - Control Phase

More of Larry’s Control Plan

  • SPC Control Chart

    • Use the mean +/- 3 sigma limits as calculated from the Improve Phase data

  • Continue Data Collection on Vital X’s

    • Larry to track drinks per round

Okay, he’s got a plan.

Is there any risk associated with it?


6 sigma example control phase1

6-Sigma Example - Control Phase

Risk Assessment

  • Identify the risk elements (schedule, cost, technical)

  • Assign ratings (high (3), med(2), low(1))

  • Prioritize elements (probability & impact)

  • Identify Risk Abatement plans

  • Incorporate into Larry’s Control plan

Giving up drinking is a risk!

Need an Abatement Plan


6 sigma example control phase2

6-Sigma Example - Control Phase

Abatement Planning

If he drinks moderately,

can he maintain an improvement?

ScatterPlot/Fitted Line Regression

5

4

s

4

4

t

t

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P

Y

=

3

6

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2

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+

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R-Squared = 0.872

Expected

Outcome

3

4

The Linear Regression predicts that 1 - 2 drinks will add only a few putts.

0

1

2

3

4

5

6

D

r

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k

s

Realistic

Tolerance


6 sigma program concepts overview

6-Sigma Example - Control Phase

Monitoring the SPC Chart

99! Out of Control!

UCL = 96.91

LCL = 83.23

What happened here?

Let’s look at the data!


6 sigma example control phase3

6-Sigma Example - Control Phase

Does Larry’s Control Plan Work?

  • How did Larry get four drinks?

  • Was this risk in the Risk Assessment / Abatement Plan?

    • Yes!

    • Is there an Abatement Plan?

    • Yes!

    • Then implement the Abatement Plan immediately.

ScoreDrinks

891

911

881

902

994

912

880

891

902

932

911

“Stuff” happens - so we do

Risk Assessment / Abatement!!


6 sigma example control phase4

6-Sigma Example - Control Phase

Did the Abatement Work?

UCL

Control Chart

says Yes!

LCL

Capability Analysis says Yes!

He has reached Zlt = 5.7 Sigma!

(Zst at Measure was 5.64)

Success!


Glossary of terms

Glossary of Terms

  • ZLT - Overall (Long Term) process capability, ZLTs process

  • ZST - Best (Short Term) process capability, ZSTs process

  • Zshift = ZLT - ZST

  • DPU - Defects Per Unit

  • DPO - Defects Per Opportunity

  • DPMO - Defects Per Million Opportunities

  • PPM - Parts Per Million

  • FTY - First Time Yield

  • Cp - Capability Index (best process capability)

  • Cpk - Actual Capability Index (measure of process shift)

  • CPU - Capability index for upper spec. limit

  • CPL - Capability index for lower spec. limit

  • CTQ - “Critical To Quality” characteristic

  • Gage R&R - Gage Repeatability & Reproducibility

  • QFD - Quality Functional Deployment

  • Sigma - is a measure of variability (standard deviation)

  • NPI/EDC - New Process Introduction/Engine Development Cycle