Six Sigma With R
(Springer, 2012)
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Six Sigma with R
Frontmatter
Statistical Engineering for Process
Mainmatter Improvement
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
Emilio L. Cano, Javier M. Moguerza
VII Further and Beyond
Backmatter
and Andr´s Redchuk
e
November 20, 2012
Facultad de Estudios Estad´
ısticos
Universidad Complutense de Madrid
Book Presentation UCM 1/59
Six Sigma With R
(Springer, 2012) Contenido
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e 1 Frontmatter
Frontmatter
Mainmatter
2 Mainmatter
I Basics
II Define I Basics
III Measure
IV Analyze
V Improve
II Define
VI Control
VII Further and Beyond
III Measure
Backmatter IV Analyze
V Improve
VI Control
VII Further and Beyond
3 Backmatter
Book Presentation UCM 2/59
Six Sigma With R
(Springer, 2012) Contents
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e 1 Frontmatter
Frontmatter
Mainmatter
2 Mainmatter
I Basics
II Define I Basics
III Measure
IV Analyze
V Improve
II Define
VI Control
VII Further and Beyond
III Measure
Backmatter IV Analyze
V Improve
VI Control
VII Further and Beyond
3 Backmatter
Book Presentation UCM 3/59
Six Sigma With R
(Springer, 2012) Publisher
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
http://www.springer.com/statistics/book/978-1-4614-3651-5
Book Presentation UCM 4/59
Six Sigma With R
(Springer, 2012) Book website
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
http://www.sixsigmawithr.com/
Book Presentation UCM 5/59
Six Sigma With R
(Springer, 2012) R Package
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
http://cran.r-project.org/web/packages/SixSigma/index.html
Book Presentation UCM 6/59
Six Sigma With R
(Springer, 2012) Frontmatter
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Foreword
Frontmatter
Preface
Mainmatter
Why Six Sigma with R
I Basics
II Define
Who is this book for
III Measure Conventions
IV Analyze
V Improve Production
VI Control
VII Further and Beyond Resources
Backmatter About the Authors
Acknowledgements
Contents
List of Tables and Figures
Acronyms
http://link.springer.com/book/10.1007/978-1-4614-3652-2//page/1
Book Presentation UCM 7/59
Six Sigma With R
(Springer, 2012) Contents
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e 1 Frontmatter
Frontmatter
Mainmatter
2 Mainmatter
I Basics
II Define I Basics
III Measure
IV Analyze
V Improve
II Define
VI Control
VII Further and Beyond
III Measure
Backmatter IV Analyze
V Improve
VI Control
VII Further and Beyond
3 Backmatter
Book Presentation UCM 8/59
Six Sigma With R
(Springer, 2012) 1. Six Sigma in a Nutshell
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter Herbert Spencer
Mainmatter
I Basics “Science is organised knowledge”
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 9/59
Six Sigma With R
(Springer, 2012) The DMAIC Cycle
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 10/59
Six Sigma With R
(Springer, 2012) Six Sigma Roles
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter In Six Sigma, everyone in the organization has
Mainmatter
I Basics a role in the project. Six Sigma methodology
II Define
III Measure
IV Analyze
uses an intuitive categorization of these roles.
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 11/59
Six Sigma With R
(Springer, 2012) Six Sigma Roles
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter In Six Sigma, everyone in the organization has
Mainmatter
I Basics a role in the project. Six Sigma methodology
II Define
III Measure
IV Analyze
uses an intuitive categorization of these roles.
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 11/59
Six Sigma With R
(Springer, 2012) 2. R from the Beginning
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter Linus Torvalds
Mainmatter
I Basics
“Software is like sex; it’s better when it’s free”
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 12/59
Six Sigma With R
(Springer, 2012) The R Project
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
http://www.r-project.org
Book Presentation UCM 13/59
Six Sigma With R
(Springer, 2012) The R Environment
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 14/59
Six Sigma With R
(Springer, 2012) 3. Process Mapping with R
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Charles Franklin Kettering
Mainmatter
I Basics
“A problem well stated is a problem half
II Define
III Measure
solved”
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 15/59
Six Sigma With R
(Springer, 2012) A Process Map
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e Six Sigma Process Map
Frontmatter operators
INPUTS
tools
Mainmatter X raw material
I Basics facilities
II Define
INSPECTION ASSEMBLY TEST LABELING
III Measure
sheets sheets helicopter helicopter
IV Analyze
...
INPUTS
INPUTS
INPUTS
INPUTS
V Improve
VI Control
VII Further and Beyond
Param.(x): width NC Param.(x): operator C Param.(x): operator C Param.(x): operator C
Backmatter operator C cut P throw P label P
Measure pattern P fix P discard P Featur.(y): label
discard P rotor.width C environment N
Featur.(y): ok rotor.length C Featur.(y): time
paperclip C
tape C
Featur.(y): weight
LEGEND
helicopter
(C)ontrollable OUTPUTS
(Cr)itical
(N)oise
Y
(P)rocedure
Paper Helicopter Project
Book Presentation UCM 16/59
Six Sigma With R
(Springer, 2012) 4. Loss Funtion Analysis with R
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter W. Edwards Deming
Mainmatter
I Basics
II Define
Defects are not free. Somebody makes them,
III Measure
IV Analyze
and gets paid for making them
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 17/59
Six Sigma With R
(Springer, 2012) A Loss Function Example
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e > ss . lfa ( ss . data . bolts , " diameter " , 0.5 , 10 , 0.001 ,
lfa . sub = " 10 mm . Bolts Project " ,
Frontmatter
lfa . size = 100000 , lfa . output = " both " )
Mainmatter
I Basics
II Define $ lfa . k
III Measure [1] 0.002
IV Analyze
V Improve
VI Control $ lfa . lf
VII Further and Beyond expression ( bold ( L == 0.002 %. % ( Y - 10) ^2) )
Backmatter
$ lfa . MSD
[1] 0.03372065
$ lfa . avLoss
[1] 6.74413 e -05
$ lfa . Loss
[1] 6.74413
Book Presentation UCM 18/59
Six Sigma With R
(Springer, 2012) A Loss Function Example (cont.)
November, 2012
Emilio L. Cano
Javier M. Moguerza Loss Function Analysis
Andr´s Redchuk
e
Frontmatter 5e−04 T
Data
Mainmatter
I Basics 4e−04 CTQ: diameter
II Define Y0 = 10
III Measure Cost of Poor Quality ∆ = 0.5
IV Analyze L0 = 0.001
3e−04
V Improve Size = 1e+05
VI Control
VII Further and Beyond
2e−04
Backmatter Mean = 10.0308
k = 0.002
1e−04 MSD = 0.0337
LSL USL Av.Loss = 1e−04
Loss = 6.7441
0e+00
9.6 9.8 10.0 10.2 10.4
Observed Value
L = 0.002 ⋅ (Y − 10)
2
10 mm. Bolts Project
Book Presentation UCM 19/59
Six Sigma With R
(Springer, 2012) 5. Measurement System Analysis
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Lord Kelvin
Mainmatter “If you cannot measure it,
I Basics
II Define you cannot improve it.”
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 20/59
Six Sigma With R
(Springer, 2012) Repeatability & Reproducibility
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
Repetible and Reproducible Repetible but non Reproducible Reproducible but non Repetible Non Repetible & Non Reproducible
II Define
q q
III Measure qq
q
q q q
q q q
IV Analyze q
q
V Improve q
qq
q
qq
VI Control
VII Further and Beyond q
q
q
q q
Backmatter
Book Presentation UCM 21/59
Six Sigma With R
(Springer, 2012) MSA with R
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e Six Sigma Gage R&R Study
Components of Variation Var by Part
1.8
Frontmatter 80
q
q
q
q
q
1.6
60
q
q
Percent
Mainmatter 1.4
var
40 q
q
q
q q
q
1.2
I Basics 20
q
q
q
q
q
1.0 q
0
II Define G.R&R Repeat Reprod Part2Part
q
prot #1 prot #2 prot #3
III Measure %Contribution %Study Var
IV Analyze R Chart by appraiser Var by appraiser
prot #1 prot #2 prot #3
V Improve 1.8
q
q
q
op #1 op #2 op #3
0.5 q
q q
q q
VI Control 1.6
0.4 q
q q
VII Further and Beyond q 1.4
var
0.3 q
var
q
q q q
q q q
q
0.2 1.2
q q q q
q
Backmatter 0.1
q q
q
1.0
q
q
q
q
prot #1 prot #2 prot #3 prot #1 prot #2 prot #3
op #1 op #2 op #3
part
x Chart by appraiser Part*appraiser Interaction
prot #1 prot #2 prot #3
1.7 q
op #1 op #2 op #3
1.7 q
1.6 q
1.6 q q 1.5
var
1.5 1.4
var
1.4 q
1.3
q q
1.3
q 1.2
1.2 q
q q
1.1 q q 1.1 q
q
prot #1 prot #2 prot #3
prot #1 prot #2 prot #3 prot #1 prot #2 prot #3
op #1 op #3
part op #2
Helicopter Project
Book Presentation UCM 22/59
Six Sigma With R
(Springer, 2012) 6. Pareto Analysis with R
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Ovidio
Mainmatter
I Basics
Causa latet: vis est notissima. [The cause is
II Define
III Measure
hidden, but the result is known.]
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 23/59
Six Sigma With R
(Springer, 2012) Pareto Principle (80/20 rule)
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
Examples
III Measure
IV Analyze
V Improve
20 % of customers make 80 % of incomes
VI Control
VII Further and Beyond 20 % of students get 80 % of good marks
Backmatter
80 % of cost of quality is due to 20 % of
the possible causes
Book Presentation UCM 24/59
Six Sigma With R
(Springer, 2012) Cause-and-effect diagram
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e Six Sigma Cause−and−effect Diagram
Frontmatter
Mainmatter
I Basics
Operator Environment Tools
operator #1 height scissors
II Define
operator #2 cleaning tape
III Measure operator #3
IV Analyze
V Improve
VI Control
VII Further and Beyond
Flight Time
Backmatter
paperclip
model marks rotor.width2
calibrate thickness rotor.length
Measure.Tool Raw.Material Design
Paper Helicopter Project
Book Presentation UCM 25/59
Six Sigma With R
(Springer, 2012) Pareto Chart
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e Pareto Chart for b.vector
q
Frontmatter q
q
q
q
Mainmatter q
80%
q
60
I Basics
Cumulative Percentage
q
II Define
q
III Measure
IV Analyze Frequency
40
V Improve
q
VI Control
VII Further and Beyond
Backmatter
20
q
0
Delays
Materials
Customer
Training
Rework
Errors
Rain
Wind
Permissions
Inadequate
Temperature
Book Presentation UCM 26/59
Six Sigma With R
(Springer, 2012) 7. Process Capability Analysis
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Johann Wolfgang von Goethe
Mainmatter One cannot develop taste from what is of
I Basics
II Define
III Measure
average quality but only from the very best.
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 27/59
Six Sigma With R
(Springer, 2012) Capability Analysis Output
November, 2012
Emilio L. Cano
Javier M. Moguerza Six Sigma Capability Analysis Study
Andr´s Redchuk
e
Histogram & Density Density Lines Legend
Frontmatter Target Density ST
Theoretical Dens. ST
Mainmatter Density LT
Theoretical Density LT
I Basics
II Define
III Measure LSL USL Specifications
IV Analyze LSL: 740
Target: 750
V Improve
USL: 760
VI Control
VII Further and Beyond
Backmatter Short Term Process Long Term
740 745 750 755 760 Mean: 749.7625 Mean: 753.7239
Check Normality SD: 2.1042 SD: 2.6958
n: 20 n: 40
Shapiro−Wilk Test Zs: 3.14 Zs: 2.33
q
p−value: 0.07506 DPMO: 9952.5
q Short Term Indices Long Term
qq Lilliefors (K−S) Test Cp: 1.5841 Pp: 1.2365
qq
qqq p−value: 0.2291 CI: [1.4,1.7] CI: [1.1,1.3]
qq
qqq
qq
qq Cpk: 1.5465 Ppk: 0.7760
q
q
CI: [1.4,1.7] CI: [0.7,0.8]
Normality accepted when p−value > 0.05
Winery Project
Book Presentation UCM 28/59
Six Sigma With R
(Springer, 2012) 8. Charts with R
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
John Tukey
Frontmatter
Mainmatter
“The greatest value of a picture is when it
I Basics
II Define
forces us to notice what we never expected to
III Measure
IV Analyze see.”
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 29/59
Six Sigma With R
(Springer, 2012) Multi-vari chart
November, 2012
Emilio L. Cano Multi−vari chart for Volume by color and operator
Javier M. Moguerza
Andr´s Redchuk
e
batch
1 q 2 q 3 q 4 q
1 2 3
Frontmatter
3 3
Mainmatter
B C
I Basics 18
II Define 17
III Measure 16 q q
q q
q q
q q
q
IV Analyze 15 q
q q
q q
q
q q q q
q q q q
V Improve 14
VI Control 2 2
VII Further and Beyond B C
q q 18
q
Backmatter
Volume
q q 17
q q
q q q
q
q 16
q q q q
q q
q q 15
q q
q
14
1 1
B C
q
18 q q
q
17 q q q q
q
q
16 q
q
q q
q q q
15 q q
q q
14 q
1 2 3
Filler
Book Presentation UCM 30/59
Six Sigma With R
(Springer, 2012) 9. Statistics and Probability with R
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter Aaron Levenstein
I Basics
II Define “Statistics are like bikinis. What they reveal is
III Measure
IV Analyze
V Improve
suggestive, but what they conceal is vital.”
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 31/59
Six Sigma With R
(Springer, 2012) Distributions
November, 2012
Emilio L. Cano Hypergeometric Geometric Negative Binomial Poison
Javier M. Moguerza
Probability
Probability
Probability
Probability
0.06
0.15
0.00 0.10
Andr´s Redchuk
e
0.3
0.00
0.00
0.0
Frontmatter 0 1 2 3 4 0 10 30 10 20 30 40 0 5 10 20
Elements in class A Items extracted until first success Number of trials until 3 events
Number of successful experiments per unit
Mainmatter
I Basics Exponential Lognormal Uniform Gamma
Probability Density
Probability Density
Probability Density
Probability Density
II Define
0.0 0.4 0.8
0.0 0.6 1.2
0.0 0.2 0.4
III Measure 0.6
IV Analyze
0.0
V Improve
0 1 2 3 4 5 0 2 4 6 −0.5 0.5 1.5 0 2 4 6 8
VI Control
Random Variable X Random Variable X>0 Random Variable X Random Variable X
VII Further and Beyond
Backmatter Beta Weibul t−Student Chi−squared
Probability Density
Probability Density
Probability Density
Probability Density
0.0 1.0 2.0
0.0 0.3 0.6
0.06
0.3
95%
5% 95% 5%
0.00
0.0
1.73 30.14
0.0 0.4 0.8 0 2 4 6 −4 0 2 4 10 30 50
Random Variable X Random Variable X Random Variable X Random Variable X
F
Probability Density
0.6
95%
5%
0.0
2.34
0 1 2 3 4
Random Variable X
Book Presentation UCM 32/59
Six Sigma With R
(Springer, 2012) 10. Statistical Inference with R
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
George E.P. Box
Frontmatter
Mainmatter
“All models are wrong; some models are
I Basics
II Define
useful.”
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 33/59
Six Sigma With R
(Springer, 2012) Confidence Interval Example
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e Confidence Interval for the Mean
Frontmatter
Mean: 950.016
95% CI: [949.967, 950.064]
Mainmatter StdDev: 0.267
P−Var: unknown
I Basics n: 120
t: 1.98
II Define Missing: 0
III Measure
IV Analyze
V Improve
VI Control Histogram & Density Plot Shapiro−Wilks
1.5
VII Further and Beyond Normality Test
Backmatter 0.985
p−value: 0.19
1.0
density
Normal q−q Plot
0.5 q
qq q
qq
qq qq q
qq q
qq
qq
qq
qq
qq
qq
qq
qq
qq
qq
qq
qq
qq
qq
q
q
qq
qq
qq
qq
qq
qq
qq
q
0.0 qq
qq
qqqq
qq
qq
qq
q
qq
qq
qq
qq
q
qq
qq
qq
949.0 949.5 950.0 950.5 q
q
q
q
Value of len q
qq
Book Presentation UCM 34/59
Six Sigma With R
(Springer, 2012) 11. Design of Experiments with R
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
R.A. Fisher
Mainmatter “Sometimes the only thing you can
I Basics
II Define do with a poorly designed
III Measure
IV Analyze
V Improve
experiment is to try to find out what
VI Control
VII Further and Beyond
it died of”
Backmatter
Book Presentation UCM 35/59
Six Sigma With R
(Springer, 2012) The Importance of Experimenting
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
“An engineer who does not know
Mainmatter experimental design is not an
I Basics
II Define
III Measure
engineer”
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Comment made by to one
of the authors [of “Statistics
for experimenters” by an
]
executive of the Toyota
Motor Company.
Book Presentation UCM 36/59
Six Sigma With R
(Springer, 2012) 12.Process Control with R
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
Walter A. Shewhart
I Basics
II Define
“Special causes of variation may be found and
III Measure
IV Analyze eliminated.”
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 37/59
Six Sigma With R
(Springer, 2012) Control Chart Plotting
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e p Chart
for stockouts
0.25
Frontmatter q
q
UCL
Mainmatter q
q
0.20
I Basics
Group summary statistics
II Define
q
III Measure
0.15
q q
q q
IV Analyze
q
V Improve q q
VI Control
0.10
q
q
CL
q
VII Further and Beyond
q
q
Backmatter q q
0.05
q
q q
q
LCL
0.00
1 3 5 7 9 11 13 15 17 19 21
Group
Number of groups = 22
Center = 0.1212294 LCL is variable Number beyond limits = 1
StdDev = 0.3263936 UCL is variable Number violating runs = 0
Book Presentation UCM 38/59
Six Sigma With R
(Springer, 2012) 13. Other Tools and
November, 2012
Emilio L. Cano
Javier M. Moguerza
Methodologies
Andr´s Redchuk
e
Frontmatter
Mainmatter
Johann Wolfgang von Goethe
I Basics
II Define Instruction does much, but encouragement
III Measure
IV Analyze
V Improve
everything.
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 39/59
Six Sigma With R
(Springer, 2012) Other topics
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
Failure Mode, Effects, and Criticality
II Define
III Measure
Analysis
IV Analyze
V Improve
VI Control
Design for Six Sigma
VII Further and Beyond
Backmatter
Lean
Gantt Chart
Some Advanced R Topics
Book Presentation UCM 40/59
Six Sigma With R
(Springer, 2012) Contents
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e 1 Frontmatter
Frontmatter
Mainmatter
2 Mainmatter
I Basics
II Define I Basics
III Measure
IV Analyze
V Improve
II Define
VI Control
VII Further and Beyond
III Measure
Backmatter IV Analyze
V Improve
VI Control
VII Further and Beyond
3 Backmatter
Book Presentation UCM 41/59
Six Sigma With R
(Springer, 2012) Case Study
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 42/59
Six Sigma With R
(Springer, 2012) Helicopter Template
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
> ss . heli ()
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instructions
Book Presentation UCM 43/59
Six Sigma with R | Paper Helicopter template
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Six Sigma With R
(Springer, 2012) Enjoy the Case Study!
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 45/59
Six Sigma With R
(Springer, 2012) Enjoy the Case Study!
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 45/59
Six Sigma With R
(Springer, 2012) So what?
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 46/59
Six Sigma With R
(Springer, 2012) So what?
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e The Scientific Method
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 46/59
Six Sigma With R
(Springer, 2012) The Scientific Method and Six
November, 2012
Emilio L. Cano
Javier M. Moguerza
Sigma
Andr´s Redchuk
e
Frontmatter
Mainmatter DMAIC Cycle Scientific Method
I Basics
II Define Ask a question
III Measure Define
IV Analyze
V Improve Do some background
VI Control
Measure research
VII Further and Beyond
Backmatter
Construct a hypothesis
Analyze
Test the hypothesis
with an experiment
Improve
Analyze the data and
draw conclusions
Control
Communicate results
Book Presentation UCM 47/59
Six Sigma With R
(Springer, 2012) The Key to Success
November, 2012
Emilio L. Cano
Javier M. Moguerza
“Six Sigma speaks the language of business”
Andr´s Redchuk
e
Frontmatter ISO 13053-1:2011
Mainmatter
I Basics
II Define
III Measure
IV Analyze
Six Sigma methodology is a quality paradigm
V Improve
VI Control
that translates the involved scientific
VII Further and Beyond
Backmatter
methodology into a simple way to apply the
scientific method within every organization.
Book Presentation UCM 48/59
Six Sigma With R
(Springer, 2012) Opportunities
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
For Today’s Graduate, Just One Word: Statistics
Mainmatter (The New York Times, August 2009)
I Basics
II Define “I keep saying that the sexy job in the
III Measure
IV Analyze next 10 years will be statisticians”
V Improve
VI Control
VII Further and Beyond
Backmatter Data Scientist: The Sexiest Job of the 21st
Century (Harvard Business Review, October 2012)
. . . the “data scientist.” It’s a
high-ranking professional with the
training and curiosity to make
discoveries in the world of big data . . .
Book Presentation UCM 49/59
Six Sigma With R
(Springer, 2012) Opportunities (cont.)
November, 2012
Emilio L. Cano Gartner Sees 4.4M Big Data Jobs by 2015
Javier M. Moguerza
Andr´s Redchuk
e (Information Management, October 2012)
Frontmatter Lack of data scientists could derail big data
Mainmatter
I Basics
projects: IBM (CIO, October 2012)
II Define
III Measure
IV Analyze
Son las matem´ticas, est´pido (El Pa´
a u ıs,
V Improve
VI Control
Noviembre 2012)
VII Further and Beyond
Backmatter
La econom´ del conocimiento exige
ıa
una educaci´n sustentada en tres
o
fundamentos: un nivel avanzado en
matem´tica y estad´
a ıstica, una
capacidad elevada para escribir un
argumento y un nivel avanzado de
ingl´s
e
Book Presentation UCM 50/59
Six Sigma With R
(Springer, 2012) R Final Remarks
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
kdnuggets.com
Backmatter (2012) link
Book Presentation UCM 51/59
Six Sigma With R
(Springer, 2012) R Final Remarks (cont.)
November, 2012
Emilio L. Cano
Javier M. Moguerza
Community
Andr´s Redchuk
e
4131 packages at CRAN (18/11/2012)
Frontmatter
Mainmatter Task views
I Basics
II Define
III Measure
Manuals
IV Analyze
V Improve Publications
VI Control
VII Further and Beyond
Backmatter http:
//cran.r-project.org/web/packages/
Book Presentation UCM 52/59
Six Sigma With R
(Springer, 2012) R Final Remarks (cont.)
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Customization
A company can develop a package that fits its
Frontmatter
Mainmatter
inner procedures and methods.
I Basics
II Define
III Measure
IV Analyze
V Improve
Innovation
VI Control
VII Further and Beyond
A company can develop and deploy an
Backmatter innovative method from its R&D department,
or from the result of other published
researches.
Book Presentation UCM 53/59
Six Sigma With R
(Springer, 2012) R Final Remarks (cont.)
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter Business
Mainmatter
I Basics
http:
II Define
III Measure
//www.revolutionanalytics.com/
IV Analyze
V Improve
VI Control
http://www.openanalytics.eu/
VII Further and Beyond
Backmatter
http://www.fellstat.com/
http://www.rstudio.com/ide/
http://www.datanalytics.com/
...
Book Presentation UCM 54/59
Six Sigma With R
(Springer, 2012) R Final Remarks (cont.)
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
GUI, IDE
II Define
III Measure
RStudio
IV Analyze
V Improve
VI Control
Eclipse + StatET
VII Further and Beyond
Backmatter
EMACS + EES
Deducer
...
Book Presentation UCM 55/59
Six Sigma With R
(Springer, 2012) R Final Remarks (cont.)
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
Book Presentation UCM 56/59
Six Sigma With R
(Springer, 2012)
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
http://r-es.org/
Book Presentation UCM 57/59
Six Sigma With R
(Springer, 2012)
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter
http://www.r-project.org/useR-2013
Book Presentation UCM 58/59
Six Sigma With R
(Springer, 2012) Discussion
November, 2012
Emilio L. Cano
Javier M. Moguerza
Andr´s Redchuk
e
Thanks !
Frontmatter
Mainmatter
I Basics
II Define
III Measure
IV Analyze
V Improve
VI Control
VII Further and Beyond
Backmatter emilio.lopez@urjc.es
@emilopezcano
http://www.sixsigmawithr.com
Book Presentation UCM 59/59