0010six Sigma Brown Bag1

8/8/2019 0010six Sigma Brown Bag1

1/19

Introduction to Six Sigma


2/19

What is Six Sigma?

A. A really small number

B. Flavor of the month program

C. Current incarnation of TQM

D. None of the above


3/19

Evolution of Six Sigma

Quality

Gurus 6 (manufacturing)

Lean

(manufacturing)

Lean

Aerospace

Initiative

Deming

Juran

IshikawaCosby

Motorola

TI

6 (parts, suppliers,

SW, process)

GE

Allied Signal

Raytheon

.

.

.

6 Business

Strategy

SW CMM

SE CM

(EIA731)

Cmmi


4/19

Foundations of Modern

Management PhilosophiesEdwards Demings 14 Points Create constancy of purpose

Reject defects

Reject inspection

Use quality criteria to award business

Constantly improve

Modernize training

Modernize management

Drive out fear

Break down functional barriers

Eliminate targets & slogans

Eliminate numerical quotas

Remove barriers from hourly workers

Train vigorously

Create a supportive management

structure

Joseph Jurans 10 Steps

Build awareness of the need and

opportunity for improvement

Set goals for improvement

Organize to reach the goals (have a

plan and an organizational structure)

Provide training

Carry out projects to solve problems

Report progress

Give recognition

Communicate results Keep score

Maintain momentum by making

annual improvement part of the

regular systems and processes of the

organization


5/19

Six Sigma: A Modern Definition

Six Sigma is a philosophy that underlies

efforts to improve business performance

and customer satisfactionUsing facts and data to eliminate waste and

variation

Eliminating activities that dont add value


6/19

Traditional Six Sigma

Process Capability Measures Chart

-300 -200 -100 0 100 200 300 400 500

Critical Measure

Mean = 112.725

StdDev = 106.13054

USL = 225.55

LSL = 0.

Sigma Level = 1.062

Sigma Capability = 1.063

Cpk = 0.354

Cp = 0.3542

D.P.M. = 287961

USLLSL

135 52

128 58

221 207

82 95

401 346

360 244

241 215130 112

252 195

220 54

112 48

29 39

57 31

28 57

41 20

27 33

33 19

7 6

17 7

94 56


7/19

Dispersion (sigma) vs. Spec


-300 -200 -100 0 100 200 300 400 500

Critical Measure

Mean = 112.725

StdDev = 106.13054

USL = 218.8

LSL = 6.6

Sigma Level = 0.999

Sigma Capability = 1.

Cpk = 0.3332

Cp = 0.3332

D.P.M. = 317450

6

3

12

45

USLLSL

Spec Limit

for a 6 process


8/19

Doing the math

6 Sigma = 3.4 defects per million

5 Sigma = 230 defects per million

4 Sigma = 6,210 defects per million

3 Sigma = 66,800 defects per million2 Sigma = 308,000 defects per million

1 Sigma = 690,000 defects per million


9/19

Its more than statistics

(much more)Asking the right question

Questions managers should ask

Questions managers should answerUsing data

Using the right tools

Using the right processSteps

Activities

Questions

Tools

OutputsInputs

(C,N,X)


10/19

Questions Managers ShouldAsk(Source:Knowledge Based Management (KBM), Air Academy Press) What activities are you responsible for? Who is the owner of these processes? Who are the team members?

How well does the team work together

Which processes have the highest priority for improvement? How did you come to this conclusion? Where is

the data that led to this conclusion?

How is the process performed?

What are your process performance measures? How accurate and precise is your measurement system?

What are the customer-driven specifications for all of your performance measures? How good or bad is the

current performance? Show me the data. What are the improvement goals for the process? What are all the sources of variability in the process?

Which sources of variability do you control?

Are any of the sources of variability supplier-dependent? If so, what are they, who is the supplier, and what are

we doing about it?

What are the key variables that affect the average and variation of the measures of performance?

What are the relationships between the measures of performance and the key variables?

Do any key variables interact? What setting for the key variables will optimize the measures of performance?

For the optimal settings of the key variables, what kind of variability exists in the performance measures?

How much improvement has the process shown in the past 6 months?

How much time and money have your efforts saved or generated for the company?


11/19

Questions Managers ShouldAnswer(Source:Knowledge Based Management (KBM), Air Academy Press)

What is your product or service and who are your customers?

What perception do your customers have of your product or service? How do you know?

Do you believe quality issues are important to your company? Why? Which ones?

What is the companys current share of the total market? Can quality improvement efforts assist you in

increasing the market share and/or increasing profits? How?

How many hours per week do you currently have scheduled that are devoted strictly to quality issues?

How often per week do you solicit feedback from the people you mange? What kind of feedback do yousolicit?

What are the right quality-oriented questions managers need to ask their people? What methods pr tools

can be used to answer them?

Are your people trained to successfully use the best quality improvement tools? What is your ROI for the

training?

Do you have a SOP for documenting quality improvement efforts?

What barriers do your people face when trying to do quality improvement? What are you doing toremove these barriers?

What metrics are you evaluated on that relate to quality issues? Are you held accountable for these

metrics? What are the specific improvement goals for these metrics?

How much waste does your company have? What is the cost of poor quality?

One year from now, what evidence will you have to show that you made a difference?


12/19

Questions form a Phased Strategy(Source:Knowledge Based Management (KBM), Air Academy Press)

Prioritize

Characterize

Optimize

Realize

Strategy

Measure

An

alyz

e Imp

rove

Co

ntro

l

Phase


13/19

Use Data..but KISS!

Measure of central tendency

mean

medianMeasures of dispersion

range

sample variancesample deviation


-300 -200 -100 0 100 200 300 400 500

Critical Measure

Mean = 112.725

StdDev = 106.13054

USL = 225.55

LSL = 0.

Sigma Level = 1.062

Sigma Capability = 1.063Cpk = 0.354

Cp = 0.3542

D.P.M. = 287961

Cp = USL - LSL

6

Cpk = USL - mean - shift

3


14/19

Use Tools..the right toolsQuality Function Deployment (QFD)

Pareto

Histograms

Run Charts

Control Charts

Design of Experiments (DOE)

Scatter Diagrams

Process Flow Diagrams

Nominal Group Techniques

Teamwork


15/19

House of Quality

Wh

at

How

Wh

at

How

Wh

at

How

Wh

at

How

System

Product

Component

Process


16/19

Run Chart

Range Chart 3 with Standard Deviations Control Limits

0

2

4

6

8

10

12

1 3 5 7 9 11 13 15

Run Number

Range

Series1

Center = 3.2308

UCL = 11.2763

LCL = 0

Zone A Above

Zone B Above

Zone A Below


17/19

Control ChartSymptoms of an out-of-control process

Upper Control Limit (UCL)

Lower Control Limit (LCL)

Zone A

Zone A

Zone B

Zone B

Zone C

Zone Cx=

1

2

3

3

2

1

One or more points outside

the control limits

7 consecutive points on one

side of the centerline

7 consecutive increasing ordecreasing intervals

2 out of 3 consecutive

points in a specific zone A

or beyond

4 out of 5 consecutive

points in a specific zone Bor beyond

14 consecutive points that

alternate up or down

14 consecutive points in

either zone C


18/19

Design of Experiments

Design of Experiments: A way of shifting

or reducing variation in a process by

carrying out a methodical sequence ofexperiments based on coded matrices. Each

combination of adjustments becomes an

equation that can either be solved as a matrix

or entered into a computer for solution. DOE

allows users to efficiently test a large number

of variables.

Factor A B C

Row # Mold Temperature Pour Time Vendor Y1 Y2 Y bar S

1 300 1 1 2.49 2.31 2.4 0.127279

2 300 1 2 2.39 2.3 2.345 0.06364

3 300 3 1 2.41 2.32 2.365 0.06364

4 300 3 2 2.27 2.23 2.25 0.028284

5 350 1 1 4.11 4.2 4.155 0.06364

6 350 1 2 4.33 4.26 4.295 0.049497

7 350 3 1 4.15 4.22 4.185 0.049497

8350 3 2 4.33 4.19 4.26 0.098995

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

AbsoluteCoeffi

Mold

Temperature

AC Pour Time AB BC Vendor ABC

Effect Name

Y-hat Paretoof Coeffs

Series1


19/19

Deployment

Roles

Champions

BlackbeltsGreenbelts

Change Management

CustomerTeamwork

0010six Sigma Brown Bag1

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