Six Sigma PTO

8/6/2019 Six Sigma PTO

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WINTRODUCTION


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W SIGMA) ;

jIS A LETTER IN THE GREEK ALPHABET


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W SIGMA) ;jIS A LETTER IN THE GREEK ALPHABET

jIS A STATISTICAL MEASUREMENT UNIT


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WHAT DOES SIGMA LEVEL MEAN?

Quality level of product


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Quality level of productProcess performance


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Quality level of productProcess performance

Reliability for customer


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DPMO ;DPMO ;

jMEANS DEFECTS PER MILLION

OPPORTUNITIES


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DPMO ;DPMO ;

jMEANS DEFECTS PER MILLION

OPPORTUNITIES

jIS TRANSLATED INTO A SIGMA

NUMBER


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What is Six Sigma?Is an Organization-Wide Initiative to achieve zero defectsand reduce wastes (Muda) and variations in the processes

Top Management commitment and strong reviewmechanisms are the key to the success of the Six sigmaInitiative

Trained people who are skilled in undertaking the processesand also has the skill in the selection and application ofSixsigma tools to achieve zero defects are essential in thisinitiative

During the initial deployment phases, Black belts have tospend at-least 50% of the time in the projects

This is an initiative which will lead the organization in thelong run to achieve Six Sigma levels in each of theirmanufacturing/service processes

Successful Organization wide deployment ofSix Sigma willtake a minimum of three years.


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Origin

Six Sigma initiative was first developed by Mr. BillSmith, who was working as Quality Manager atMotorola

With a strong commitment from Mr. Bob Galvin, thenCEO of Motorola, the implementation of the initiativebegan in 1986

This initiative helped Motorola win the first MalcolmBaldrige Award in 1998

Several of the major companies in the world haveadopted Six Sigma since then

Texas Instruments, ABB, GE, Nokia Mobile phones,Sony, Dupont, Polaroid, American Express and Ford


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Birds eye view of Six Sigma

Data based decision making. No AtmosphericAnalysis

Structured troubleshooting done by cross functionalteams having Process Knowledge

Project selection done by Top Management


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Six Sigma Focus RolledThroughput Yield (RTY)

Y (RTY) = f(X) = Y1x Y2xY3xY4

RTY Objective (100%)

Methodology adopted is Funneling

Big Y = Main Response for the problem

X = Cause (s) that are not controllable. Theseas also called as Intermediate Ys

Root Xs = Root Cause (s) that arecontrollable by implementing processimprovement actions


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Q

THE NORMAL DISTRIBUTION CURVE


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Q !

! !

1 2 1 x x xx

n

i

i

n

n n

....

Q6 W 4 W5 W 3 W 2 W 1W 1W 2 W 3 W 4 W 5 W 6 W


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YIELD + DEFECT = 100%

YIELD

DEFECT


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Do you accept 1 % defect?j In every hour sending 22 000 cheques into the

wrong account


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wrong account

j Unsafe drinking water almost 1 hour in a month


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wrong account


j No electricity for 7 hours each month


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wrong account


j No electricity for 7 hours each month

j In a year your heart beat stops for 32 000 times, thismeans you are 100% surely100% surely100% surely DEAD!DEAD!DEAD!


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T

Z USL T !

W

6 W 4 W5 W 3 W 2 W 1W 1W 2 W 3 W 4 W 5 W 6 W g g

How Many Standard Deviations Are There Between USL and T?

LSL USL


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0. 0.000003

6 SI


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WHAT

WE DO A

S6

SIGMA TEAM ?

We

take measurements


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WHAT

WE DO A

S6

SIGMA TEAM ?

We

take measurements

calculate Sigma Level


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WHAT

WE DO A

S6

SIGMA TEAM ?

We

take measurements

calculate Sigma Levelanalyze the measurements


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WHAT

WE DO A

S6

SIGMA TEAM ?

We

take measurements


detect areas for improvement


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W

HATW

E DO AS

6S

IGMA TEAM ?We

take measurements



come up with recommendations


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W

HATW

E DO AS

6S

IGMA TEAM ?We

take measurements



come up with recommendations

implement


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WHAT WE DO AS 6 SIGMA TEAM ?

We

take measurements



come up with recommendations implement

control


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ClassificationofBlackBelt Projects

CTQ (Critical to Quality)

Scrap Reduction

Rework reduction

Variation Reduction Resolving customer complaints

CTS (Critical to Satisfaction)

No complaints from customer/user Project selected

only to enhance the performance of theproduct/service level

CTC (Critical to Cost)

Process Optimization projects


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Measure &Calculate Implement

ImproveAnalyze Control

FLOW CHART OF SIX SIGMA


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HOW THE MEASUREMENTS ARE

TAKEN?

BY A TRAINED 6 SIGMA TEAM, CALLED BLACKBELTS

WITH COOPERATION OF THE EMPLOYEE

S


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SIGMA LEVEL

S

6 SIGMA

5 SIGMA

4 SIGMA

3 SIGMA

2 SIGMA

6 SIGMA

OUR AIM IS

TO REACH 6S

IGMA LEVEL TOGETHER


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WHAT SIX SIGMA WILL DO FOR USWHAT SIX SIGMA WILL DO FOR US

HELPS IMPROVE :HELPS IMPROVE : First Pass Yield/Input OutputFirst Pass Yield/Input Output Delivery PromptnessDelivery Promptness

Cost of QualityCost of Quality

... BY REDUCING OUR :... BY REDUCING OUR : Defects Per UnitDefects Per Unit Throughput TimeThroughput Time

... WHICH SHOW UP IN OUR:... WHICH SHOW UP IN OUR:

Bottom Line ResultBottom Line Result CustomerSatisfactionCustomerSatisfaction


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W - M

1

10

1001

000

10000

100000

1000000

2 3 4 5 6

SIGMA

M

VALUES COME FROMVALUES COME FROM

SIX SIGMASIX SIGMA

TRANSFER KNOWLEDGE THROUGHTRANSFER KNOWLEDGE THROUGH- QUALITY IMPROVEMENT

- TROUBLESHOOTING

QUALITYQUALITY--COSTCOST--TIMETIME

BREAKTHROUGHBREAKTHROUGHSTRATEGYSTRATEGY

Phase 1Phase 1MeasurementsMeasurements

Phase 4Phase 4ControlControl

Phase 3Phase 3ImprovementImprovement

Phase 2Phase 2

AnalysisAnalysis

Benchmarking

AverageCompany

Best-in-Class

ppm


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TROUBLESHOOTINGTROUBLESHOOTING

SHORT TERM

THE BREAKTHROUGH STRATEGYBREAKTHROUGHBREAKTHROUGHSTRATEGYSTRATEGY

Phase 1Phase 1MeasurementsMeasurements

Phase 4Phase 4

ControlControl

Phase 3Phase 3ImprovementImprovement

Phase 2Phase 2AnalysisAnalysis

Processparameter

Productparameter

LSL

USL

Adjustmentrange

Distributionwithoutcontrollingtheprocessparameter

Distributionwithfixedprocessparameter

(reducedvariability)

Processparameter

Productparameter

LSL

USL

Adjustmentrange

Distributionwithoutcontrollingtheprocessparameter

Distributionwithfixedprocessparameter

(reducedvariability)

MEASUREMEASUREMEASURMENTS

Run 1

Run 2

Run 3

Run 4

Run 5

Run 6

Run 7

ANALYZEANALYZE

LSL TARGET USL

IMPROVEIMPROVE

CONTROLCONTROLNumber

f

ample

1 2 3 4 5 6 7 8 9 1 0 11 1 2 13 1 4 15 1 6 17 1 8 19 2 0

OKr

Bereic

OKB 1.800 1.800 1.800 1.800 1.800 1.800 1.800 1.800 1.800 1.800 1.800 1.800 1.800 1.800 1.800 1.800 1.800 1.800 1.800 1.800

OK

e Bereic

1.670 1.670 1.670 1.670 1.670 1.670 1.670 1.670 1.670 1.670 1.670 1.670 1.670 1.670 1.670 1.670 1.670 1.670 1.670 1.670

OKr

Bereic

1.170 1.170 1.170 1.170 1.170 1.170 1.170 1.170 1.170 1.170 1.170 1.170 1.170 1.170 1.170 1.170 1.170 1.170 1.170 1.170

OK

rBereic

C

1.545 1.545 1.545 1.545 1.545 1.545 1.545 1.545 1.545 1.545 1.545 1.545 1.545 1.545 1.545 1.545 1.545 1.545 1.545 1.545

OK

e Bereic

C

1.295 1.295 1.295 1.295 1.295 1.295 1.295 1.295 1.295 1.295 1.295 1.295 1.295 1.295 1.295 1.295 1.295 1.295 1.295 1.295

Gemessene

aten eff. 1.430 1.320 1.550 1.330 1.400 1.310 1.320 1.430 1.490 1.480 1.400 1.400 1.480 1.470 1.480 1.420 1.470 1.390 1.420 1.410

Tolleranz 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500 0.500

1/4Tolleranz 0.125 0.125 0.125 0.125 0.125 0.125 0.125 0.125 0.125 0.125 0.125 0.125 0.125 0.125 0.125 0.125 0.125 0.125 0.125 0.125

Number

fS

mple

1.000

1.100

1.200

1.300

1.400

1.500

1.600

1.700

1.800

1 2 3 4 5 6 7 8 9 1 0 11 12 13 14 15

USL

UPCL

LPCL

LSL


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SHORT TERM

MEASUREMEASURE

MEASURMENTS

Run 1

Run 2

Run 3

Run 4

Run 5

Run 6

Run 7

We dont know what we dont know

We cant act on what we dont know

We wont know until we search

We wont search for what we dont question

We dont question what we dont measure

Hence, We just dont know...

Dr Mikel Harry

IF WE CANT EXPRESSWHAT WE KNOW IN THE FORM OF NUMBERS,IF WE CANT EXPRESSWHAT WE KNOW IN THE FORM OF NUMBERS,

WE REALLY DONT KNOW MUCH ABOUT ITWE REALLY DONT KNOW MUCH ABOUT IT

Dr Mikel Harry

LET DATA BE THE BASE TO OUR ACTIONS!LET DATA BE THE BASE TO OUR ACTIONS!


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SHORT TERM

ANALYZEANALYZE

NORMAL DISTRIBUTIONNORMAL DISTRIBUTION

POINT OF DEFLECTION

QW

CUS

S

S

UCTI

N

SUPPLI

Or

er

O r

er

recep tion

W riting

purc!

aseor

ers

Break

own of

or

erPlanningof s upplies

Plann ingof s upplies

"

ece ipt ofplanned

supplies

W riting

purc!

as e

r rOrder

OrderOrder

con firmation

Order

con firmation

NG INEERING

PURCHASE

RECEPTI

N

PROCESS APPINGPROCESS APPING

Background Information

Company XXXX Product ENGINEFactory YYYY Product ID 12345Location VSTERS Recorder B . SMITHDepartment 11 D at e A UG -12-1995

Six Sigma Analysis

No. Description Ord er D e f ec t s U n i ts D P U O TOP DPO Z1 Winding diameterWiA leg 1 2 6 3 2.0002-001-0400 2,90E-01 1 2 , 90E-01 1 1 2,90E-01 2,052 Winding diameterWiA leg 2 2 6 3 2.0002-001-0400 1,85E-01 1 1 , 85E-01 1 1 1, 85E-01 2 , 403 Winding diameterWiB leg 1 2 6 3 2.0002-001-0400 4,00E-01 1 4,00E-01 1 1 4,00E-01 1 , 754 Winding diameterWiB leg 2 2 6 3 2.0002-001-0400 1,97E-01 1 1 , 97E-01 1 1 1, 97E-01 2 , 355 Winding diameterWiC leg 1 2 6 3 2.0002-001-0400 3,94E-01 1 3 , 94E-01 1 1 3, 94E-01 1 , 776 Winding diameterWiC leg 2 2 6 3 2.0002-001-0400 2,43E-01 1 2 , 43E-01 1 1 2, 43E-01 2 , 207 Winding diameterWiD leg 1 2 6 3 2.0002-001-0400 5,00E-01 1 5,00E-01 1 1 5,00E-01 1 , 508 Winding diameterWiD leg 2 2 6 3 2.0002-001-0400 3,78E-01 1 3 , 78E-01 1 1 3, 78E-01 1 , 819 Dirt 2632.0002-001-0400 0,00E+00 1 0,00E+00 1 1 0,00E+00 6,00

10 Winding diameterWiA leg 1 2 6 3 2.0002-001-0500 4,35E-01 1 4 , 35E-01 1 1 4, 35E-01 1 , 6611 Winding diameterWiA leg 2 2 6 3 2.0002-001-0500 4,91E-01 1 4 , 91E-01 1 1 4, 91E-01 1 , 5212 Winding diameterWiB leg 1 2 6 3 2.0002-001-0500 3,42E-01 1 3 , 42E-01 1 1 3, 42E-01 1 , 9113 Winding diameterWiB leg 2 2 6 3 2.0002-001-0500 5,00E-01 1 5,00E-01 1 1 5,00E-01 1 , 5014 Dirt 2632.0002-001-0500 5,88E-02 1 5 , 88E-02 1 1 5, 88E-02 3,0615 Common spacerring thickness 2632.0004-001-0120 1,03E-01 1 1,03E-01 1 1 1,03E-01 2 , 7716 Common spacerring thickness 2632.0004-001-0120 4,08E-04 1 4,08E-04 1 1 4,08E-04 4 , 8517 Common spacerring thickness 2632.0004-001-0120 2,51E-03 1 2 , 51E-03 1 1 2, 51E-03 4 , 3118 Common spacerring thickness 2632.0004-001-0120 1,05E-1 9 1 1 ,05E-19 1 1 1,05E-19 10,5119

2021

2223

24

2526

27

2829

3031

32

33

34

35

36

37

3839

404142

4344

45

Rolled = 5 18 0, 2 5 11 2 , 1 7

COMPUTE THE SIGMACOMPUTE THE SIGMA

7 QUALITY TOOLS7 QUALITY TOOLSCharts and Graphs

Check Sheets

Pareto Charts

Cause and Effect (Ishikawa/Fishbone) Diagrams

Scatter Diagrams

Histograms

Control Charts

* EVALUATE THE PROCESS* EVALUATE THE PROCESS

* DEFINE THE PROBLEM* DEFINE THE PROBLEM

*DEFINE THE GOAL

*DEFINE THE GOAL

* PLAN FOR IMROVEMENT* PLAN FOR IMROVEMENT


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SHORT TERM

IMPROVEMENTIMPROVEMENT* SELECT VARIABLES* SELECT VARIABLES

* DIAGNOSE PERFORMANCE* DIAGNOSE PERFORMANCE

*UNDERSTAND THE PROBLEM

*UNDERSTAND THE PROBLEM

* EXECUTE IMPROVEMENTS* EXECUTE IMPROVEMENTS

DESIGN OF EXPERIMENT

A

BC

Trial A B C

1 - - -

2 + - -

3 - + -

4 + + -

5 - - +

6 + - +

7 - + +

8 + + +

+

-

+

-

+-

PERFORMANCE TOLERANCING

Processparameter

Productparameter

LSL

USL

Adjustment range

Distributionwithout controlling the

process parameter

Distributionwithfixed process parameter

(reduced variability)

Processparameter

Productparameter

LSL

USL

Adjustment range

Distributionwithout controlling the

process parameter

Distributionwithfixed process parameter

(reduced variability)


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SHORT TERM

CONTROLCONTROL

Statistical Process ControlNumber of S amp le

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

O K r o#

ereich O K#

1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .8 00 1 .800

O K g e#

ereich U S L 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .6 70 1 .670

O K r o#

ereich LS L 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .1 70 1 .170

O K g r #

ereich U P$

L 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .5 45 1 .545

O K g e#

ereich L P$

L 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .2 95 1 .295

Ge messene Daten ef f . 1 .4 30 1 .3 20 1 .5 50 1 .3 30 1 .4 00 1 .3 10 1 .3 20 1 .4 30 1 .4 90 1 .4 80 1 .4 00 1 .4 00 1 .4 80 1 .4 70 1 .4 80 1 .4 20 1 .4 70 1 .3 90 1 .4 20 1 .410

T olleranz 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .5 00 0 .500

1 /4 Tolleranz 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .1 25 0 .125

Nu m b er o f S am p le

1 . 00 0

1 . 10 0

1 . 20 0

1 . 30 0

1 . 40 0

1 . 50 0

1 . 60 0

1 . 70 0

1 . 80 0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

US L

UP$

L

LP$

L

LSL

Precontrol (Preset Control Limits)

U S L U p p e r S p e c if ic a t io n L im it L S L L o w e r S p e c i f i c a t i o n L i m i t

U P C L U p pe r P re co ntro l L im it L PC L L ow er P re co ntro l L im it

* MONITOR PROCESS AFTER IMPROVEMENT* MONITOR PROCESS AFTER IMPROVEMENT

* ENSURE CAPABILITY* ENSURE CAPABILITY

LSL TARGET USL

Six Sigma PTO

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