8/8/2019 0010six Sigma Brown Bag1
1/19
Introduction to Six Sigma
8/8/2019 0010six Sigma Brown Bag1
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
8/8/2019 0010six Sigma Brown Bag1
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
8/8/2019 0010six Sigma Brown Bag1
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
8/8/2019 0010six Sigma Brown Bag1
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
8/8/2019 0010six Sigma Brown Bag1
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
8/8/2019 0010six Sigma Brown Bag1
7/19
Dispersion (sigma) vs. Spec
Process Capability Measures Chart
-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
8/8/2019 0010six Sigma Brown Bag1
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
8/8/2019 0010six Sigma Brown Bag1
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)
8/8/2019 0010six Sigma Brown Bag1
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?
8/8/2019 0010six Sigma Brown Bag1
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?
8/8/2019 0010six Sigma Brown Bag1
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
8/8/2019 0010six Sigma Brown Bag1
13/19
Use Data..but KISS!
Measure of central tendency
mean
medianMeasures of dispersion
range
sample variancesample deviation
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 = 1.063Cpk = 0.354
Cp = 0.3542
D.P.M. = 287961
Cp = USL - LSL
6
Cpk = USL - mean - shift
3
8/8/2019 0010six Sigma Brown Bag1
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
8/8/2019 0010six Sigma Brown Bag1
15/19
House of Quality
Wh
at
How
Wh
at
How
Wh
at
How
Wh
at
How
System
Product
Component
Process
8/8/2019 0010six Sigma Brown Bag1
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
8/8/2019 0010six Sigma Brown Bag1
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
8/8/2019 0010six Sigma Brown Bag1
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
8/8/2019 0010six Sigma Brown Bag1
19/19
Deployment
Roles
Champions
BlackbeltsGreenbelts
Change Management
CustomerTeamwork
Top Related